WorldWideScience

Sample records for ontology recognition semantic

  1. Word add-in for ontology recognition: semantic enrichment of scientific literature

    Directory of Open Access Journals (Sweden)

    Naim Oscar

    2010-02-01

    Full Text Available Abstract Background In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles. Results The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at http://www.codeplex.com/UCSDBioLit. Conclusions The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata.

  2. Word add-in for ontology recognition: semantic enrichment of scientific literature.

    Science.gov (United States)

    Fink, J Lynn; Fernicola, Pablo; Chandran, Rahul; Parastatidis, Savas; Wade, Alex; Naim, Oscar; Quinn, Gregory B; Bourne, Philip E

    2010-02-24

    In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles. The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at http://www.codeplex.com/UCSDBioLit. The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata.

  3. Ontology Matching with Semantic Verification.

    Science.gov (United States)

    Jean-Mary, Yves R; Shironoshita, E Patrick; Kabuka, Mansur R

    2009-09-01

    ASMOV (Automated Semantic Matching of Ontologies with Verification) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.

  4. Semantator: annotating clinical narratives with semantic web ontologies.

    Science.gov (United States)

    Song, Dezhao; Chute, Christopher G; Tao, Cui

    2012-01-01

    To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. With a loaded free text document and an ontology, Semantator supports the creation/deletion of ontology instances for any document fragment, linking/disconnecting instances with the properties in the ontology, and also enables automatic annotation by connecting to the NCBO annotator and cTAKES. By representing annotations in Semantic Web standards, Semantator supports reasoning based upon the underlying semantics of the owl:disjointWith and owl:equivalentClass predicates. We present discussions based on user experiences of using Semantator.

  5. Semantic similarity between ontologies at different scales

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qingpeng; Haglin, David J.

    2016-04-01

    In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.

  6. Introduction to Semantic Web Ontology Languages

    NARCIS (Netherlands)

    Antoniou, Grigoris; Franconi, Enrico; Van Harmelen, Frank

    2005-01-01

    The aim of this chapter is to give a general introduction to some of the ontology languages that play a prominent role on the Semantic Web, and to discuss the formal foundations of these languages. Web ontology languages will be the main carriers of the information that we will want to share and

  7. Ontological semantics in modified categorial grammar

    DEFF Research Database (Denmark)

    Szymczak, Bartlomiej Antoni

    2009-01-01

    Categorial Grammar is a well established tool for describing natural language semantics. In the current paper we discuss some of its drawbacks and how it could be extended to overcome them. We use the extended version for deriving ontological semantics from text. A proof-of-concept implementation...

  8. Core Semantics for Public Ontologies

    National Research Council Canada - National Science Library

    Suni, Niranjan

    2005-01-01

    ... (schemas or ontologies) with respect to objects. The DARPA Agent Markup Language (DAML) through the use of ontologies provides a very powerful way to describe objects and their relationships to other objects...

  9. Semantic Activity Recognition

    OpenAIRE

    Thonnat , Monique

    2008-01-01

    International audience; Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia Antipolis. Our main objective is to analyse in real-time video streams captured by static video cameras and to recogniz...

  10. Semantic Similarity between Web Documents Using Ontology

    Science.gov (United States)

    Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

    2018-06-01

    The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

  11. Semantic Similarity between Web Documents Using Ontology

    Science.gov (United States)

    Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

    2018-03-01

    The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

  12. Ontology-based Metadata Portal for Unified Semantics

    Data.gov (United States)

    National Aeronautics and Space Administration — The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS) will extend the prototype Ontology-Driven Interactive Search Environment for Earth Sciences...

  13. Product line based ontology development for semantic web service

    DEFF Research Database (Denmark)

    Zhang, Weishan; Kunz, Thomas

    2006-01-01

    Ontology is recognized as a key technology for the success of the Semantic Web. Building reusable and evolve-able ontologies in order to cope with ontology evolution and requirement changes is increasingly important. But the existing methodologies and tools fail to support effective ontology reuse...... will lead to the initial implementation of the meta-onotologies using design by reuse and with the objective of design for reuse. After that step new ontologies could be generated by reusing these meta-ontologies. We demonstrate our approach with a Semantic Web Service application to show how to build...

  14. Handbook of metadata, semantics and ontologies

    CERN Document Server

    Sicilia, Miguel-Angel

    2013-01-01

    Metadata research has emerged as a discipline cross-cutting many domains, focused on the provision of distributed descriptions (often called annotations) to Web resources or applications. Such associated descriptions are supposed to serve as a foundation for advanced services in many application areas, including search and location, personalization, federation of repositories and automated delivery of information. Indeed, the Semantic Web is in itself a concrete technological framework for ontology-based metadata. For example, Web-based social networking requires metadata describing people and

  15. Ontology Based Resolution of Semantic Conflicts in Information Integration

    Institute of Scientific and Technical Information of China (English)

    LU Han; LI Qing-zhong

    2004-01-01

    Semantic conflict is the conflict caused by using different ways in heterogeneous systems to express the same entity in reality.This prevents information integration from accomplishing semantic coherence.Since ontology helps to solve semantic problems, this area has become a hot topic in information integration.In this paper, we introduce semantic conflict into information integration of heterogeneous applications.We discuss the origins and categories of the conflict, and present an ontology-based schema mapping approach to eliminate semantic conflicts.

  16. Ontology alignment architecture for semantic sensor Web integration.

    Science.gov (United States)

    Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

    2013-09-18

    Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  17. Ontology Alignment Architecture for Semantic Sensor Web Integration

    Directory of Open Access Journals (Sweden)

    Bernardo Alarcos

    2013-09-01

    Full Text Available Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity. Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  18. Ontology based heterogeneous materials database integration and semantic query

    Science.gov (United States)

    Zhao, Shuai; Qian, Quan

    2017-10-01

    Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

  19. A semantic medical multimedia retrieval approach using ontology information hiding.

    Science.gov (United States)

    Guo, Kehua; Zhang, Shigeng

    2013-01-01

    Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users' query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of this approach are cross-type retrieval support and semantic information preservation. Experimental results indicate a good precision and efficiency of our approach for medical multimedia retrieval in comparison with some traditional approaches.

  20. Ontology modularization to improve semantic medical image annotation.

    Science.gov (United States)

    Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

    2011-02-01

    Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results. Copyright © 2010 Elsevier Inc. All rights reserved.

  1. Determining the semantic similarities among Gene Ontology terms.

    Science.gov (United States)

    Taha, Kamal

    2013-05-01

    We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where each term in S' is semantically related to each term in S. Most current research is focused on determining the semantic similarities among GO ontology terms based solely on their IDs and proximity to one another in the GO graph structure, while overlooking the contexts of the terms, which may lead to erroneous results. The context of a GO term T is the set of other terms, whose existence in the GO graph structure is dependent on T. We propose novel techniques that determine the contexts of terms based on the concept of existence dependency. We present a stack-based sort-merge algorithm employing these techniques for determining the semantic similarities among GO terms.We evaluated GoSE experimentally and compared it with three existing methods. The results of measuring the semantic similarities among genes in KEGG and Pfam pathways retrieved from the DBGET and Sanger Pfam databases, respectively, have shown that our method outperforms the other three methods in recall and precision.

  2. IBRI-CASONTO: Ontology-based semantic search engine

    Directory of Open Access Journals (Sweden)

    Awny Sayed

    2017-11-01

    Full Text Available The vast availability of information, that added in a very fast pace, in the data repositories creates a challenge in extracting correct and accurate information. Which has increased the competition among developers in order to gain access to technology that seeks to understand the intent researcher and contextual meaning of terms. While the competition for developing an Arabic Semantic Search systems are still in their infancy, and the reason could be traced back to the complexity of Arabic Language. It has a complex morphological, grammatical and semantic aspects, as it is a highly inflectional and derivational language. In this paper, we try to highlight and present an Ontological Search Engine called IBRI-CASONTO for Colleges of Applied Sciences, Oman. Our proposed engine supports both Arabic and English language. It is also employed two types of search which are a keyword-based search and a semantics-based search. IBRI-CASONTO is based on different technologies such as Resource Description Framework (RDF data and Ontological graph. The experiments represent in two sections, first it shows a comparison among Entity-Search and the Classical-Search inside the IBRI-CASONTO itself, second it compares the Entity-Search of IBRI-CASONTO with currently used search engines, such as Kngine, Wolfram Alpha and the most popular engine nowadays Google, in order to measure their performance and efficiency.

  3. Usage of semantic representations in recognition memory.

    Science.gov (United States)

    Nishiyama, Ryoji; Hirano, Tetsuji; Ukita, Jun

    2017-11-01

    Meanings of words facilitate false acceptance as well as correct rejection of lures in recognition memory tests, depending on the experimental context. This suggests that semantic representations are both directly and indirectly (i.e., mediated by perceptual representations) used in remembering. Studies using memory conjunction errors (MCEs) paradigms, in which the lures consist of component parts of studied words, have reported semantic facilitation of rejection of the lures. However, attending to components of the lures could potentially cause this. Therefore, we investigated whether semantic overlap of lures facilitates MCEs using Japanese Kanji words in which a whole-word image is more concerned in reading. Experiments demonstrated semantic facilitation of MCEs in a delayed recognition test (Experiment 1), and in immediate recognition tests in which participants were prevented from using phonological or orthographic representations (Experiment 2), and the salient effect on individuals with high semantic memory capacities (Experiment 3). Additionally, analysis of the receiver operating characteristic suggested that this effect is attributed to familiarity-based memory judgement and phantom recollection. These findings indicate that semantic representations can be directly used in remembering, even when perceptual representations of studied words are available.

  4. Automated Predictive Big Data Analytics Using Ontology Based Semantics.

    Science.gov (United States)

    Nural, Mustafa V; Cotterell, Michael E; Peng, Hao; Xie, Rui; Ma, Ping; Miller, John A

    2015-10-01

    Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and considerable expertise which might not always be readily available. In this paper, we propose to use semantic technology to assist data analysts and data scientists in selecting appropriate modeling techniques and building specific models as well as the rationale for the techniques and models selected. To formally describe the modeling techniques, models and results, we developed the Analytics Ontology that supports inferencing for semi-automated model selection. The SCALATION framework, which currently supports over thirty modeling techniques for predictive big data analytics is used as a testbed for evaluating the use of semantic technology.

  5. Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS

    Science.gov (United States)

    Liu, Ying; Xiao, Han; Wang, Limin; Han, Jialing

    2017-07-01

    Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.

  6. Toward semantic interoperability with linked foundational ontologies in ROMULUS

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-06-01

    Full Text Available A purpose of a foundational ontology is to solve interoperability issues among ontologies. Many foundational ontologies have been developed, reintroducing the ontology interoperability problem. We address this with the new online foundational...

  7. ONTOLOGY BASED MEANINGFUL SEARCH USING SEMANTIC WEB AND NATURAL LANGUAGE PROCESSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    K. Palaniammal

    2013-10-01

    Full Text Available The semantic web extends the current World Wide Web by adding facilities for the machine understood description of meaning. The ontology based search model is used to enhance efficiency and accuracy of information retrieval. Ontology is the core technology for the semantic web and this mechanism for representing formal and shared domain descriptions. In this paper, we proposed ontology based meaningful search using semantic web and Natural Language Processing (NLP techniques in the educational domain. First we build the educational ontology then we present the semantic search system. The search model consisting three parts which are embedding spell-check, finding synonyms using WordNet API and querying ontology using SPARQL language. The results are both sensitive to spell check and synonymous context. This paper provides more accurate results and the complete details for the selected field in a single page.

  8. The Influence of Semantic Neighbours on Visual Word Recognition

    Science.gov (United States)

    Yates, Mark

    2012-01-01

    Although it is assumed that semantics is a critical component of visual word recognition, there is still much that we do not understand. One recent way of studying semantic processing has been in terms of semantic neighbourhood (SN) density, and this research has shown that semantic neighbours facilitate lexical decisions. However, it is not clear…

  9. Semantics and metaphysics in informatics: toward an ontology of tasks.

    Science.gov (United States)

    Figdor, Carrie

    2011-04-01

    This article clarifies three principles that should guide the development of any cognitive ontology. First, that an adequate cognitive ontology depends essentially on an adequate task ontology; second, that the goal of developing a cognitive ontology is independent of the goal of finding neural implementations of the processes referred to in the ontology; and third, that cognitive ontologies are neutral regarding the metaphysical relationship between cognitive and neural processes. Copyright © 2011 Cognitive Science Society, Inc.

  10. CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives.

    Science.gov (United States)

    Tao, Cui; Wei, Wei-Qi; Solbrig, Harold R; Savova, Guergana; Chute, Christopher G

    2010-11-13

    Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.

  11. An Ontological Approach to Developing Information Operations Applications for use on the Semantic Web

    National Research Council Canada - National Science Library

    Clarke, Timothy L

    2008-01-01

    .... By expressing IO capabilities in a formal ontology suitable for use on the Semantic Web, conditions are set such that computational power can more efficiently be leveraged to better define required...

  12. An Ontological Approach to Developing Information Operations Applications for Use on the Semantic Web

    National Research Council Canada - National Science Library

    Clarke, Timothy L

    2008-01-01

    .... By expressing IO capabilities in a formal ontology suitable for use on the Semantic Web, conditions are set such that computational power can more efficiently be leveraged to better define required...

  13. The use of web ontology languages and other semantic web tools in drug discovery.

    Science.gov (United States)

    Chen, Huajun; Xie, Guotong

    2010-05-01

    To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

  14. Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

    Science.gov (United States)

    Uthayan, K R; Mala, G S Anandha

    2015-01-01

    Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

  15. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  16. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Science.gov (United States)

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  17. Fish Ontology framework for taxonomy-based fish recognition

    Science.gov (United States)

    Ali, Najib M.; Khan, Haris A.; Then, Amy Y-Hui; Ving Ching, Chong; Gaur, Manas

    2017-01-01

    Life science ontologies play an important role in Semantic Web. Given the diversity in fish species and the associated wealth of information, it is imperative to develop an ontology capable of linking and integrating this information in an automated fashion. As such, we introduce the Fish Ontology (FO), an automated classification architecture of existing fish taxa which provides taxonomic information on unknown fish based on metadata restrictions. It is designed to support knowledge discovery, provide semantic annotation of fish and fisheries resources, data integration, and information retrieval. Automated classification for unknown specimens is a unique feature that currently does not appear to exist in other known ontologies. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1,830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users. PMID:28929028

  18. Fish Ontology framework for taxonomy-based fish recognition

    Directory of Open Access Journals (Sweden)

    Najib M. Ali

    2017-09-01

    Full Text Available Life science ontologies play an important role in Semantic Web. Given the diversity in fish species and the associated wealth of information, it is imperative to develop an ontology capable of linking and integrating this information in an automated fashion. As such, we introduce the Fish Ontology (FO, an automated classification architecture of existing fish taxa which provides taxonomic information on unknown fish based on metadata restrictions. It is designed to support knowledge discovery, provide semantic annotation of fish and fisheries resources, data integration, and information retrieval. Automated classification for unknown specimens is a unique feature that currently does not appear to exist in other known ontologies. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1,830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users.

  19. The Semantic Mapping of Archival Metadata to the CIDOC CRM Ontology

    Science.gov (United States)

    Bountouri, Lina; Gergatsoulis, Manolis

    2011-01-01

    In this article we analyze the main semantics of archival description, expressed through Encoded Archival Description (EAD). Our main target is to map the semantics of EAD to the CIDOC Conceptual Reference Model (CIDOC CRM) ontology as part of a wider integration architecture of cultural heritage metadata. Through this analysis, it is concluded…

  20. THE PRINCIPLES AND METHODS OF INFORMATION AND EDUCATIONAL SPACE SEMANTIC STRUCTURING BASED ON ONTOLOGIC APPROACH REALIZATION

    Directory of Open Access Journals (Sweden)

    Yurij F. Telnov

    2014-01-01

    Full Text Available This article reveals principles of semantic structuring of information and educational space of objects of knowledge and scientific and educational services with use of methods of ontologic engineering. Novelty of offered approach is interface of ontology of a content and ontology of scientific and educational services that allows to carry out effective composition of services and objects of knowledge according to models of professional competences and requirements being trained. As a result of application of methods of information and educational space semantic structuring integration of use of the diverse distributed scientific and educational content by educational institutions for carrying out scientific researches, methodical development and training is provided.

  1. Domain XML semantic integration based on extraction rules and ontology mapping

    Directory of Open Access Journals (Sweden)

    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  2. Self-adaptation of Ontologies to Folksonomies in Semantic Web

    OpenAIRE

    Francisco Echarte; José Javier Astrain; Alberto Córdoba; Jesús Villadangos

    2008-01-01

    Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at...

  3. Ontology-based semantic information technology for safeguards: opportunities and challenges

    International Nuclear Information System (INIS)

    McDaniel, Michael

    2014-01-01

    The challenge of efficiently handling large volumes of heterogeneous information is a barrier to more effective safeguards implementation. With the emergence of new technologies for generating and collecting information this is an issue common to many industries and problem domains. Several diverse information‑intensive fields are developing and adopting ontology‑based semantic information technology solutions to address issues of information integration, federation and interoperability. Ontology, in this context, refers to the formal specification of the content, structure, and logic of knowledge within a domain of interest. Ontology‑based semantic information technologies have the potential to impact nearly every level of safeguards implementation, from information collection and integration, to personnel training and knowledge retention, to planning and analysis. However, substantial challenges remain before the full benefits of semantic technology can be realized. Perhaps the most significant challenge is the development of a nuclear fuel cycle ontology. For safeguards, existing knowledge resources such as the IAEA’s Physical Model and established upper level ontologies can be used as starting points for ontology development, but a concerted effort must be taken by the safeguards community for such an activity to be successful. This paper provides a brief background of ontologies and semantic information technology, demonstrates how these technologies are used in other areas, offers examples of how ontologies can be applied to safeguards, and discusses the challenges of developing and implementing this technology as well as a possible path forward.

  4. Using ontology-based semantic similarity to facilitate the article screening process for systematic reviews.

    Science.gov (United States)

    Ji, Xiaonan; Ritter, Alan; Yen, Po-Yin

    2017-05-01

    Systematic Reviews (SRs) are utilized to summarize evidence from high quality studies and are considered the preferred source of evidence-based practice (EBP). However, conducting SRs can be time and labor intensive due to the high cost of article screening. In previous studies, we demonstrated utilizing established (lexical) article relationships to facilitate the identification of relevant articles in an efficient and effective manner. Here we propose to enhance article relationships with background semantic knowledge derived from Unified Medical Language System (UMLS) concepts and ontologies. We developed a pipelined semantic concepts representation process to represent articles from an SR into an optimized and enriched semantic space of UMLS concepts. Throughout the process, we leveraged concepts and concept relations encoded in biomedical ontologies (SNOMED-CT and MeSH) within the UMLS framework to prompt concept features of each article. Article relationships (similarities) were established and represented as a semantic article network, which was readily applied to assist with the article screening process. We incorporated the concept of active learning to simulate an interactive article recommendation process, and evaluated the performance on 15 completed SRs. We used work saved over sampling at 95% recall (WSS95) as the performance measure. We compared the WSS95 performance of our ontology-based semantic approach to existing lexical feature approaches and corpus-based semantic approaches, and found that we had better WSS95 in most SRs. We also had the highest average WSS95 of 43.81% and the highest total WSS95 of 657.18%. We demonstrated using ontology-based semantics to facilitate the identification of relevant articles for SRs. Effective concepts and concept relations derived from UMLS ontologies can be utilized to establish article semantic relationships. Our approach provided a promising performance and can easily apply to any SR topics in the

  5. Computing an Ontological Semantics for a Natural Language Fragment

    DEFF Research Database (Denmark)

    Szymczak, Bartlomiej Antoni

    tried to establish a domain independent “ontological semantics” for relevant fragments of natural language. The purpose of this research is to develop methods and systems for taking advantage of formal ontologies for the purpose of extracting the meaning contents of texts. This functionality...

  6. Using semantic distances for reasoning with inconsistent ontologies

    NARCIS (Netherlands)

    Huang, Zhisheng; van Harmelen, Frank

    2009-01-01

    Re-using and combining multiple ontologies on the Web is bound to lead to inconsistencies between the combined vocabularies. Even many of the ontologies that are in use today turn out to be inconsistent once some of their implicit knowledge is made explicit. However, robust and efficient methods to

  7. A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

    Science.gov (United States)

    El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

    2015-11-01

    Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Ontology Language to Support Description of Experiment Control System Semantics, Collaborative Knowledge-Base Design and Ontology Reuse

    International Nuclear Information System (INIS)

    Gyurjyan, Vardan; Abbott, D.; Heyes, G.; Jastrzembski, E.; Moffit, B.; Timmer, C.; Wolin, E.

    2009-01-01

    In this paper we discuss the control domain specific ontology that is built on top of the domain-neutral Resource Definition Framework (RDF). Specifically, we will discuss the relevant set of ontology concepts along with the relationships among them in order to describe experiment control components and generic event-based state machines. Control Oriented Ontology Language (COOL) is a meta-data modeling language that provides generic means for representation of physics experiment control processes and components, and their relationships, rules and axioms. It provides a semantic reference frame that is useful for automating the communication of information for configuration, deployment and operation. COOL has been successfully used to develop a complete and dynamic knowledge-base for experiment control systems, developed using the AFECS framework.

  9. The next generation of similarity measures that fully explore the semantics in biomedical ontologies.

    Science.gov (United States)

    Couto, Francisco M; Pinto, H Sofia

    2013-10-01

    There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current effort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this effort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although beneficial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of finding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that efficiently and fully explore the semantics present in biomedical ontologies.

  10. GeoSciGraph: An Ontological Framework for EarthCube Semantic Infrastructure

    Science.gov (United States)

    Gupta, A.; Schachne, A.; Condit, C.; Valentine, D.; Richard, S.; Zaslavsky, I.

    2015-12-01

    The CINERGI (Community Inventory of EarthCube Resources for Geosciences Interoperability) project compiles an inventory of a wide variety of earth science resources including documents, catalogs, vocabularies, data models, data services, process models, information repositories, domain-specific ontologies etc. developed by research groups and data practitioners. We have developed a multidisciplinary semantic framework called GeoSciGraph semantic ingration of earth science resources. An integrated ontology is constructed with Basic Formal Ontology (BFO) as its upper ontology and currently ingests multiple component ontologies including the SWEET ontology, GeoSciML's lithology ontology, Tematres controlled vocabulary server, GeoNames, GCMD vocabularies on equipment, platforms and institutions, software ontology, CUAHSI hydrology vocabulary, the environmental ontology (ENVO) and several more. These ontologies are connected through bridging axioms; GeoSciGraph identifies lexically close terms and creates equivalence class or subclass relationships between them after human verification. GeoSciGraph allows a community to create community-specific customizations of the integrated ontology. GeoSciGraph uses the Neo4J,a graph database that can hold several billion concepts and relationships. GeoSciGraph provides a number of REST services that can be called by other software modules like the CINERGI information augmentation pipeline. 1) Vocabulary services are used to find exact and approximate terms, term categories (community-provided clusters of terms e.g., measurement-related terms or environmental material related terms), synonyms, term definitions and annotations. 2) Lexical services are used for text parsing to find entities, which can then be included into the ontology by a domain expert. 3) Graph services provide the ability to perform traversal centric operations e.g., finding paths and neighborhoods which can be used to perform ontological operations like

  11. Ontology-Based Information Visualization: Toward Semantic Web Applications

    NARCIS (Netherlands)

    Fluit, Christiaan; Sabou, Marta; Harmelen, Frank van

    2006-01-01

    The Semantic Web is an extension of the current World Wide Web, based on the idea of exchanging information with explicit, formal, and machine-accessible descriptions of meaning. Providing information with such semantics will enable the construction of applications that have an increased awareness

  12. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology

    OpenAIRE

    Caniza, Horacio; Romero, Alfonso E.; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-01-01

    Summary: We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve...

  13. Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

    Directory of Open Access Journals (Sweden)

    Mingxin Gan

    2014-01-01

    Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

  14. Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

    Science.gov (United States)

    Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

    2014-01-01

    The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

  15. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  16. An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

    Science.gov (United States)

    Gao, Wenlong

    2012-01-01

    The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

  17. Ontology-based Semantic Search Engine for Healthcare Services

    OpenAIRE

    Jotsna Molly Rajan; M. Deepa Lakshmi

    2012-01-01

    With the development of Web Services, the retrieval of relevant services has become a challenge. The keyword-based discovery mechanism using UDDI and WSDL is insufficient due to the retrievalof a large amount of irrelevant information. Also, keywords are insufficient in expressing semantic concepts since a single concept can be referred using syntactically different terms. Hence, service capabilities need to be manually analyzed, which lead to the development of the Semantic Web for automatic...

  18. SISTEM ONTOLOGI E-LEARNING BERBASIS SEMANTIC WEB

    Directory of Open Access Journals (Sweden)

    Bernard Renaldy Suteja

    2012-05-01

    Full Text Available E-learning content being a barrier for e-learning is no longer true on today’s Internet. The current concerns are how to effectively annotate and organize the available content (both textual and non-textual to facilitate effective sharing, reusability and customization. In this paper, we explain a component-oriented approach to organize content in an ontology. We also illustrate our 3-tier e-learning content management architecture and relevant interfaces. We use a simple yet intuitive example to successfully demonstrate the current working prototype which is capable of compiling personalized course materials. The e-learning system explained here uses the said ontology.

  19. VuWiki: An Ontology-Based Semantic Wiki for Vulnerability Assessments

    Science.gov (United States)

    Khazai, Bijan; Kunz-Plapp, Tina; Büscher, Christian; Wegner, Antje

    2014-05-01

    The concept of vulnerability, as well as its implementation in vulnerability assessments, is used in various disciplines and contexts ranging from disaster management and reduction to ecology, public health or climate change and adaptation, and a corresponding multitude of ideas about how to conceptualize and measure vulnerability exists. Three decades of research in vulnerability have generated a complex and growing body of knowledge that challenges newcomers, practitioners and even experienced researchers. To provide a structured representation of the knowledge field "vulnerability assessment", we have set up an ontology-based semantic wiki for reviewing and representing vulnerability assessments: VuWiki, www.vuwiki.org. Based on a survey of 55 vulnerability assessment studies, we first developed an ontology as an explicit reference system for describing vulnerability assessments. We developed the ontology in a theoretically controlled manner based on general systems theory and guided by principles for ontology development in the field of earth and environment (Raskin and Pan 2005). Four key questions form the first level "branches" or categories of the developed ontology: (1) Vulnerability of what? (2) Vulnerability to what? (3) What reference framework was used in the vulnerability assessment?, and (4) What methodological approach was used in the vulnerability assessment? These questions correspond to the basic, abstract structure of the knowledge domain of vulnerability assessments and have been deduced from theories and concepts of various disciplines. The ontology was then implemented in a semantic wiki which allows for the classification and annotation of vulnerability assessments. As a semantic wiki, VuWiki does not aim at "synthesizing" a holistic and overarching model of vulnerability. Instead, it provides both scientists and practitioners with a uniform ontology as a reference system and offers easy and structured access to the knowledge field of

  20. Deriving ontological semantic relations between Arabic compound nouns concepts

    Directory of Open Access Journals (Sweden)

    Imen Bouaziz Mezghanni

    2017-04-01

    Experiments carried out on Arabic legal dataset showed that the proposed approach reached encouraging performance through achieving high precision and recall scores. This performance affects positively the retrieval results of legal documents based on a powerful ontology, which presents our main objective.

  1. OntoPop: An Ontology Population System for the Semantic Web

    Science.gov (United States)

    Thongkrau, Theerayut; Lalitrojwong, Pattarachai

    The development of ontology at the instance level requires the extraction of the terms defining the instances from various data sources. These instances then are linked to the concepts of the ontology, and relationships are created between these instances for the next step. However, before establishing links among data, ontology engineers must classify terms or instances from a web document into an ontology concept. The tool for help ontology engineer in this task is called ontology population. The present research is not suitable for ontology development applications, such as long time processing or analyzing large or noisy data sets. OntoPop system introduces a methodology to solve these problems, which comprises two parts. First, we select meaningful features from syntactic relations, which can produce more significant features than any other method. Second, we differentiate feature meaning and reduce noise based on latent semantic analysis. Experimental evaluation demonstrates that the OntoPop works well, significantly out-performing the accuracy of 49.64%, a learning accuracy of 76.93%, and executes time of 5.46 second/instance.

  2. Taxonomy, Ontology and Semantics at Johnson Space Center

    Science.gov (United States)

    Berndt, Sarah Ann

    2011-01-01

    At NASA Johnson Space Center (JSC), the Chief Knowledge Officer has been developing the JSC Taxonomy to capitalize on the accomplishments of yesterday while maintaining the flexibility needed for the evolving information environment of today. A clear vision and scope for the semantic system is integral to its success. The vision for the JSC Taxonomy is to connect information stovepipes to present a unified view for information and knowledge across the Center, across organizations, and across decades. Semantic search at JSC means seemless integration of disparate information sets into a single interface. Ever increasing use, interest, and organizational participation mark successful integration and provide the framework for future application.

  3. Semantic similarity from natural language and ontology analysis

    CERN Document Server

    Harispe, Sébastien; Janaqi, Stefan

    2015-01-01

    Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli.In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances def

  4. Developmental Anatomy Ontology of Zebrafish: an Integrative semantic framework

    Directory of Open Access Journals (Sweden)

    Belmamoune Mounia

    2007-12-01

    Full Text Available Integration of information is quintessential to make use of the wealth of bioinformatics resources. One aspect of integration is to make databases interoperable through well annotated information. With new databases one strives to store complementary information and such results in collections of heterogeneous information systems. Concepts in these databases need to be connected and ontologies typically provide a common terminology to share information among different resources.

  5. Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

    Science.gov (United States)

    Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

    2018-01-01

    Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

  6. Agent Based Knowledge Management Solution using Ontology, Semantic Web Services and GIS

    Directory of Open Access Journals (Sweden)

    Andreea DIOSTEANU

    2009-01-01

    Full Text Available The purpose of our research is to develop an agent based knowledge management application framework using a specific type of ontology that is able to facilitate semantic web service search and automatic composition. This solution can later on be used to develop complex solutions for location based services, supply chain management, etc. This application for modeling knowledge highlights the importance of agent interaction that leads to efficient enterprise interoperability. Furthermore, it proposes an "agent communication language" ontology that extends the OWL Lite standard approach and makes it more flexible in retrieving proper data for identifying the agents that can best communicate and negotiate.

  7. IBRI-CASONTO: Ontology-based semantic search engine

    OpenAIRE

    Awny Sayed; Amal Al Muqrishi

    2017-01-01

    The vast availability of information, that added in a very fast pace, in the data repositories creates a challenge in extracting correct and accurate information. Which has increased the competition among developers in order to gain access to technology that seeks to understand the intent researcher and contextual meaning of terms. While the competition for developing an Arabic Semantic Search systems are still in their infancy, and the reason could be traced back to the complexity of Arabic ...

  8. Ontology-based Information Retrieval

    DEFF Research Database (Denmark)

    Styltsvig, Henrik Bulskov

    In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information...... retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use......, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun...

  9. PENCARIAN BUDAYA MENGGUNAKAN ONTOLOGI DAN ATURAN BERBASIS SEMANTIC WEB UNTUK SISWA SD

    Directory of Open Access Journals (Sweden)

    Rendra Husni Thamrin

    2016-10-01

    Full Text Available Internet users every year have increased rapidly. One function of the Internet is that it is used as a source of information. Keywords used in search engine will help to find information. Semantic Web technologies can be used to help make the search more effective system either globally or specifically. Certain material in this study could use material about Indonesian art and culture taught in social studies class IV Elementary School in the odd semester.  Ontology bridges the differences in perception between humans with a machine that generally break the words then looking into the query. In addition SWRL (Semantic Web Rule Language is used by Ontology which has already made.

  10. A Novel Mobile Video Community Discovery Scheme Using Ontology-Based Semantical Interest Capture

    Directory of Open Access Journals (Sweden)

    Ruiling Zhang

    2016-01-01

    Full Text Available Leveraging network virtualization technologies, the community-based video systems rely on the measurement of common interests to define and steady relationship between community members, which promotes video sharing performance and improves scalability community structure. In this paper, we propose a novel mobile Video Community discovery scheme using ontology-based semantical interest capture (VCOSI. An ontology-based semantical extension approach is proposed, which describes video content and measures video similarity according to video key word selection methods. In order to reduce the calculation load of video similarity, VCOSI designs a prefix-filtering-based estimation algorithm to decrease energy consumption of mobile nodes. VCOSI further proposes a member relationship estimate method to construct scalable and resilient node communities, which promotes video sharing capacity of video systems with the flexible and economic community maintenance. Extensive tests show how VCOSI obtains better performance results in comparison with other state-of-the-art solutions.

  11. Semantic relations differentially impact associative recognition memory: electrophysiological evidence.

    Science.gov (United States)

    Kriukova, Olga; Bridger, Emma; Mecklinger, Axel

    2013-10-01

    Though associative recognition memory is thought to rely primarily on recollection, recent research indicates that familiarity might also make a substantial contribution when to-be-learned items are integrated into a coherent structure by means of an existing semantic relation. It remains unclear how different types of semantic relations, such as categorical (e.g., dancer-singer) and thematic (e.g., dancer-stage) relations might affect associative recognition, however. Using event-related potentials (ERPs), we addressed this question by manipulating the type of semantic link between paired words in an associative recognition memory experiment. An early midfrontal old/new effect, typically linked to familiarity, was observed across the relation types. In contrast, a robust left parietal old/new effect was found in the categorical condition only, suggesting a clear contribution of recollection to associative recognition for this kind of pairs. One interpretation of this pattern is that familiarity was sufficiently diagnostic for associative recognition of thematic relations, which could result from the integrative nature of the thematic relatedness compared to the similarity-based nature of categorical pairs. The present study suggests that the extent to which recollection and familiarity are involved in associative recognition is at least in part determined by the properties of semantic relations between the paired associates. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

    Science.gov (United States)

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2015-01-01

    There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

  13. A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism

    Directory of Open Access Journals (Sweden)

    Mohamed FRIKHA

    2015-12-01

    Full Text Available Tunisia is well placed in terms of medical tourism and has highly qualified and specialized medical and surgical teams. Integrating social networks in Tunisian medical tourism recommender systems can result in much more accurate recommendations. That is to say, information, interests, and recommendations retrieved from social networks can improve the prediction accuracy. This paper aims to improve traditional recommender systems by incorporating information in social network; including user preferences and influences from social friends. Accordingly, a user interest ontology is developed to make personalized recommendations out of such information. In this paper, we present a semantic social recommender system employing a user interest ontology and a Tunisian Medical Tourism ontology. Our system can improve the quality of recommendation for Tunisian tourism domain. Finally, our social recommendation algorithm is implemented in order to be used in a Tunisia tourism Website to assist users interested in visiting Tunisia for medical purposes.

  14. The chemical information ontology: provenance and disambiguation for chemical data on the biological semantic web.

    Science.gov (United States)

    Hastings, Janna; Chepelev, Leonid; Willighagen, Egon; Adams, Nico; Steinbeck, Christoph; Dumontier, Michel

    2011-01-01

    Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA).

  15. The chemical information ontology: provenance and disambiguation for chemical data on the biological semantic web.

    Directory of Open Access Journals (Sweden)

    Janna Hastings

    Full Text Available Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA.

  16. The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web

    Science.gov (United States)

    Hastings, Janna; Chepelev, Leonid; Willighagen, Egon; Adams, Nico; Steinbeck, Christoph; Dumontier, Michel

    2011-01-01

    Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA). PMID:21991315

  17. A sensor and video based ontology for activity recognition in smart environments.

    Science.gov (United States)

    Mitchell, D; Morrow, Philip J; Nugent, Chris D

    2014-01-01

    Activity recognition is used in a wide range of applications including healthcare and security. In a smart environment activity recognition can be used to monitor and support the activities of a user. There have been a range of methods used in activity recognition including sensor-based approaches, vision-based approaches and ontological approaches. This paper presents a novel approach to activity recognition in a smart home environment which combines sensor and video data through an ontological framework. The ontology describes the relationships and interactions between activities, the user, objects, sensors and video data.

  18. Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

    Science.gov (United States)

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

    Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. The structure of semantic person memory: evidence from semantic priming in person recognition.

    Science.gov (United States)

    Wiese, Holger

    2011-11-01

    This paper reviews research on the structure of semantic person memory as examined with semantic priming. In this experimental paradigm, a familiarity decision on a target face or written name is usually faster when it is preceded by a related as compared to an unrelated prime. This effect has been shown to be relatively short lived and susceptible to interfering items. Moreover, semantic priming can cross stimulus domains, such that a written name can prime a target face and vice versa. However, it remains controversial whether representations of people are stored in associative networks based on co-occurrence, or in more abstract semantic categories. In line with prominent cognitive models of face recognition, which explain semantic priming by shared semantic information between prime and target, recent research demonstrated that priming could be obtained from purely categorically related, non-associated prime/target pairs. Although strategic processes, such as expectancy and retrospective matching likely contribute, there is also evidence for a non-strategic contribution to priming, presumably related to spreading activation. Finally, a semantic priming effect has been demonstrated in the N400 event-related potential (ERP) component, which may reflect facilitated access to semantic information. It is concluded that categorical relatedness is one organizing principle of semantic person memory. ©2011 The British Psychological Society.

  20. A semantic web ontology for small molecules and their biological targets.

    Science.gov (United States)

    Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

    2010-05-24

    A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

  1. A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

    Science.gov (United States)

    Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

    2016-02-01

    Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. CelOWS: an ontology based framework for the provision of semantic web services related to biological models.

    Science.gov (United States)

    Matos, Ely Edison; Campos, Fernanda; Braga, Regina; Palazzi, Daniele

    2010-02-01

    The amount of information generated by biological research has lead to an intensive use of models. Mathematical and computational modeling needs accurate description to share, reuse and simulate models as formulated by original authors. In this paper, we introduce the Cell Component Ontology (CelO), expressed in OWL-DL. This ontology captures both the structure of a cell model and the properties of functional components. We use this ontology in a Web project (CelOWS) to describe, query and compose CellML models, using semantic web services. It aims to improve reuse and composition of existent components and allow semantic validation of new models.

  3. Novel Ontologies-based Optical Character Recognition-error Correction Cooperating with Graph Component Extraction

    Directory of Open Access Journals (Sweden)

    Sarunya Kanjanawattana

    2017-01-01

    Full Text Available literature. Extracting graph information clearly contributes to readers, who are interested in graph information interpretation, because we can obtain significant information presenting in the graph. A typical tool used to transform image-based characters to computer editable characters is optical character recognition (OCR. Unfortunately, OCR cannot guarantee perfect results, because it is sensitive to noise and input quality. This becomes a serious problem because misrecognition provides misunderstanding information to readers and causes misleading communication. In this study, we present a novel method for OCR-error correction based on bar graphs using semantics, such as ontologies and dependency parsing. Moreover, we used a graph component extraction proposed in our previous study to omit irrelevant parts from graph components. It was applied to clean and prepare input data for this OCR-error correction. The main objectives of this paper are to extract significant information from the graph using OCR and to correct OCR errors using semantics. As a result, our method provided remarkable performance with the highest accuracies and F-measures. Moreover, we examined that our input data contained less of noise because of an efficiency of our graph component extraction. Based on the evidence, we conclude that our solution to the OCR problem achieves the objectives.

  4. The MGED Ontology: a resource for semantics-based description of microarray experiments.

    Science.gov (United States)

    Whetzel, Patricia L; Parkinson, Helen; Causton, Helen C; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Game, Laurence; Heiskanen, Mervi; Morrison, Norman; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Taylor, Chris; White, Joseph; Stoeckert, Christian J

    2006-04-01

    The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). Stoeckrt@pcbi.upenn.edu Supplementary data are available at Bioinformatics online.

  5. Recognition during recall failure: Semantic feature matching as a mechanism for recognition of semantic cues when recall fails.

    Science.gov (United States)

    Cleary, Anne M; Ryals, Anthony J; Wagner, Samantha R

    2016-01-01

    Research suggests that a feature-matching process underlies cue familiarity-detection when cued recall with graphemic cues fails. When a test cue (e.g., potchbork) overlaps in graphemic features with multiple unrecalled studied items (e.g., patchwork, pitchfork, pocketbook, pullcork), higher cue familiarity ratings are given during recall failure of all of the targets than when the cue overlaps in graphemic features with only one studied target and that target fails to be recalled (e.g., patchwork). The present study used semantic feature production norms (McRae et al., Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005) to examine whether the same holds true when the cues are semantic in nature (e.g., jaguar is used to cue cheetah). Indeed, test cues (e.g., cedar) that overlapped in semantic features (e.g., a_tree, has_bark, etc.) with four unretrieved studied items (e.g., birch, oak, pine, willow) received higher cue familiarity ratings during recall failure than test cues that overlapped in semantic features with only two (also unretrieved) studied items (e.g., birch, oak), which in turn received higher familiarity ratings during recall failure than cues that did not overlap in semantic features with any studied items. These findings suggest that the feature-matching theory of recognition during recall failure can accommodate recognition of semantic cues during recall failure, providing a potential mechanism for conceptually-based forms of cue recognition during target retrieval failure. They also provide converging evidence for the existence of the semantic features envisaged in feature-based models of semantic knowledge representation and for those more concretely specified by the production norms of McRae et al. (Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005).

  6. KaBOB: ontology-based semantic integration of biomedical databases.

    Science.gov (United States)

    Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

    2015-04-23

    The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for

  7. Understanding semantic mapping evolution by observing changes in biomedical ontologies.

    Science.gov (United States)

    dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

    2014-02-01

    Knowledge Organization Systems (KOSs) are extensively used in the biomedical domain to support information sharing between software applications. KOSs are proposed covering different, but overlapping subjects, and mappings indicate the semantic relation between concepts from two KOSs. Over time, KOSs change as do the mappings between them. This can result from a new discovery or a revision of existing knowledge which includes corrections of concepts or mappings. Indeed, changes affecting KOS entities may force the underline mappings to be updated in order to ensure their reliability over time. To tackle this open research problem, we study how mappings are affected by KOS evolution. This article presents a detailed descriptive analysis of the impact that changes in KOS have on mappings. As a case study, we use the official mappings established between SNOMED CT and ICD-9-CM from 2009 to 2011. Results highlight factors according to which KOS changes in varying degrees influence the evolution of mappings. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. Handling Real-World Context Awareness, Uncertainty and Vagueness in Real-Time Human Activity Tracking and Recognition with a Fuzzy Ontology-Based Hybrid Method

    Science.gov (United States)

    Díaz-Rodríguez, Natalia; Cadahía, Olmo León; Cuéllar, Manuel Pegalajar; Lilius, Johan; Calvo-Flores, Miguel Delgado

    2014-01-01

    Human activity recognition is a key task in ambient intelligence applications to achieve proper ambient assisted living. There has been remarkable progress in this domain, but some challenges still remain to obtain robust methods. Our goal in this work is to provide a system that allows the modeling and recognition of a set of complex activities in real life scenarios involving interaction with the environment. The proposed framework is a hybrid model that comprises two main modules: a low level sub-activity recognizer, based on data-driven methods, and a high-level activity recognizer, implemented with a fuzzy ontology to include the semantic interpretation of actions performed by users. The fuzzy ontology is fed by the sub-activities recognized by the low level data-driven component and provides fuzzy ontological reasoning to recognize both the activities and their influence in the environment with semantics. An additional benefit of the approach is the ability to handle vagueness and uncertainty in the knowledge-based module, which substantially outperforms the treatment of incomplete and/or imprecise data with respect to classic crisp ontologies. We validate these advantages with the public CAD-120 dataset (Cornell Activity Dataset), achieving an accuracy of 90.1% and 91.07% for low-level and high-level activities, respectively. This entails an improvement over fully data-driven or ontology-based approaches. PMID:25268914

  9. Handling Real-World Context Awareness, Uncertainty and Vagueness in Real-Time Human Activity Tracking and Recognition with a Fuzzy Ontology-Based Hybrid Method

    Directory of Open Access Journals (Sweden)

    Natalia Díaz-Rodríguez

    2014-09-01

    Full Text Available Human activity recognition is a key task in ambient intelligence applications to achieve proper ambient assisted living. There has been remarkable progress in this domain, but some challenges still remain to obtain robust methods. Our goal in this work is to provide a system that allows the modeling and recognition of a set of complex activities in real life scenarios involving interaction with the environment. The proposed framework is a hybrid model that comprises two main modules: a low level sub-activity recognizer, based on data-driven methods, and a high-level activity recognizer, implemented with a fuzzy ontology to include the semantic interpretation of actions performed by users. The fuzzy ontology is fed by the sub-activities recognized by the low level data-driven component and provides fuzzy ontological reasoning to recognize both the activities and their influence in the environment with semantics. An additional benefit of the approach is the ability to handle vagueness and uncertainty in the knowledge-based module, which substantially outperforms the treatment of incomplete and/or imprecise data with respect to classic crisp ontologies. We validate these advantages with the public CAD-120 dataset (Cornell Activity Dataset, achieving an accuracy of 90.1% and 91.07% for low-level and high-level activities, respectively. This entails an improvement over fully data-driven or ontology-based approaches.

  10. Advancing data reuse in phyloinformatics using an ontology-driven Semantic Web approach.

    Science.gov (United States)

    Panahiazar, Maryam; Sheth, Amit P; Ranabahu, Ajith; Vos, Rutger A; Leebens-Mack, Jim

    2013-01-01

    Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena, including, for example, the importance of gene and genome duplications in the evolution of gene function, the role of adaptation as a driver of diversification, or the evolutionary consequences of biogeographic shifts. Phyloinformaticists are developing data standards, databases and communication protocols (e.g. Application Programming Interfaces, APIs) to extend the accessibility of gene trees, species trees, and the metadata necessary to interpret these trees, thus enabling researchers across the life sciences to reuse phylogenetic knowledge. Specifically, Semantic Web technologies are being developed to make phylogenetic knowledge interpretable by web agents, thereby enabling intelligently automated, high-throughput reuse of results generated by phylogenetic research. This manuscript describes an ontology-driven, semantic problem-solving environment for phylogenetic analyses and introduces artefacts that can promote phyloinformatic efforts to promote accessibility of trees and underlying metadata. PhylOnt is an extensible ontology with concepts describing tree types and tree building methodologies including estimation methods, models and programs. In addition we present the PhylAnt platform for annotating scientific articles and NeXML files with PhylOnt concepts. The novelty of this work is the annotation of NeXML files and phylogenetic related documents with PhylOnt Ontology. This approach advances data reuse in phyloinformatics.

  11. Improvements to the Ontology-based Metadata Portal for Unified Semantics (OlyMPUS)

    Science.gov (United States)

    Linsinbigler, M. A.; Gleason, J. L.; Huffer, E.

    2016-12-01

    The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support Earth Science data consumers and data providers, enabling the latter to register data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS complements the ODISEES' data discovery system with an intelligent tool to enable data producers to auto-generate semantically enhanced metadata and upload it to the metadata repository that drives ODISEES. Like ODISEES, the OlyMPUS metadata provisioning tool leverages robust semantics, a NoSQL database and query engine, an automated reasoning engine that performs first- and second-order deductive inferencing, and uses a controlled vocabulary to support data interoperability and automated analytics. The ODISEES data discovery portal leverages this metadata to provide a seamless data discovery and access experience for data consumers who are interested in comparing and contrasting the multiple Earth science data products available across NASA data centers. Olympus will support scientists' services and tools for performing complex analyses and identifying correlations and non-obvious relationships across all types of Earth System phenomena using the full spectrum of NASA Earth Science data available. By providing an intelligent discovery portal that supplies users - both human users and machines - with detailed information about data products, their contents and their structure, ODISEES will reduce the level of effort required to identify and prepare large volumes of data for analysis. This poster will explain how OlyMPUS leverages deductive reasoning and other technologies to create an integrated environment for generating and exploiting semantically rich metadata.

  12. Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines.

    Science.gov (United States)

    Kumar, Anand; Ciccarese, Paolo; Quaglini, Silvana; Stefanelli, Mario; Caffi, Ezio; Boiocchi, Lorenzo

    2003-01-01

    Medical knowledge in clinical practice guideline (GL) texts is the source of task-based computer-interpretable clinical guideline models (CIGMs). We have used Unified Medical Language System (UMLS) semantic types (STs) to understand the percentage of GL text which belongs to a particular ST. We also use UMLS semantic network together with the CIGM-specific ontology to derive a semantic meaning behind the GL text. In order to achieve this objective, we took nine GL texts from the National Guideline Clearinghouse (NGC) and marked up the text dealing with a particular ST. The STs we took into consideration were restricted taking into account the requirements of a task-based CIGM. We used DARPA Agent Markup Language and Ontology Inference Layer (DAML + OIL) to create the UMLS and CIGM specific semantic network. For the latter, as a bench test, we used the 1999 WHO-International Society of Hypertension Guidelines for the Management of Hypertension. We took into consideration the UMLS STs closest to the clinical tasks. The percentage of the GL text dealing with the ST "Health Care Activity" and subtypes "Laboratory Procedure", "Diagnostic Procedure" and "Therapeutic or Preventive Procedure" were measured. The parts of text belonging to other STs or comments were separated. A mapping of terms belonging to other STs was done to the STs under "HCA" for representation in DAML + OIL. As a result, we found that the three STs under "HCA" were the predominant STs present in the GL text. In cases where the terms of related STs existed, they were mapped into one of the three STs. The DAML + OIL representation was able to describe the hierarchy in task-based CIGMs. To conclude, we understood that the three STs could be used to represent the semantic network of the task-bases CIGMs. We identified some mapping operators which could be used for the mapping of other STs into these.

  13. Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Carlos R. Rangel

    2016-08-01

    Full Text Available In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease, and the main cells in each community. We analyze our approach in two cases: TGF-ß and the Alzheimer Disease.

  14. Lexical-Semantic Processing and Reading: Relations between Semantic Priming, Visual Word Recognition and Reading Comprehension

    Science.gov (United States)

    Nobre, Alexandre de Pontes; de Salles, Jerusa Fumagalli

    2016-01-01

    The aim of this study was to investigate relations between lexical-semantic processing and two components of reading: visual word recognition and reading comprehension. Sixty-eight children from private schools in Porto Alegre, Brazil, from 7 to 12 years, were evaluated. Reading was assessed with a word/nonword reading task and a reading…

  15. Cloud based automated framework for semantic rich ontology construction and similarity computation for E-health applications

    Directory of Open Access Journals (Sweden)

    T. MuthamilSelvan

    Full Text Available Ontology structure, a core of semantic web is an excellent tool for knowledge representation and semantic visualization. Moreover, knowledge reuse is made possible through similarity measure estimation between two ontologies, threshold estimation and use of simple if-then rules for checking relevancy and irrelevancy measures. Reduced semantic representations of the ontology provide reduced knowledge visualization which is critical especially for e-health data processing and analysis. This usually occurs due to the presence of implicit knowledge and polymorphic objects and can be made semantically rich through the construction by resolving this implicit knowledge occurring in the form of non-dominant words and conditional dependence actions. This paper presents the working of the automated framework for the construction of semantic rich ontology structures and store in the repository. This construction uses dyadic deontic logic based Graph Derivation Representation in order to construct semantically rich ontologies. Moreover, in order to retrieve a set of relevant documents in response to the cloud user document, the degree of similarity between two ontologies is estimated using the traditional cosine similarity measure and simple if-then rules are used to determine the number of relevant documents and obtain such document's metadata for further processing. These working modules will be extremely beneficial to the authenticated cloud users for document retrieval, information extraction and domain dictionary construction which are especially used for e-health applications. The proposed framework is implemented using diabetes dataset and the effectiveness of the experimental results is high when compared to other Graph Derivation Representation methods. The graphical results shown in the paper is an added visualization for viewing the performance of the proposed framework. Keywords: Ontology, Implicit knowledge, Conditional dependence, Graph

  16. Terminology representation guidelines for biomedical ontologies in the semantic web notations.

    Science.gov (United States)

    Tao, Cui; Pathak, Jyotishman; Solbrig, Harold R; Wei, Wei-Qi; Chute, Christopher G

    2013-02-01

    Terminologies and ontologies are increasingly prevalent in healthcare and biomedicine. However they suffer from inconsistent renderings, distribution formats, and syntax that make applications through common terminologies services challenging. To address the problem, one could posit a shared representation syntax, associated schema, and tags. We identified a set of commonly-used elements in biomedical ontologies and terminologies based on our experience with the Common Terminology Services 2 (CTS2) Specification as well as the Lexical Grid (LexGrid) project. We propose guidelines for precisely such a shared terminology model, and recommend tags assembled from SKOS, OWL, Dublin Core, RDF Schema, and DCMI meta-terms. We divide these guidelines into lexical information (e.g. synonyms, and definitions) and semantic information (e.g. hierarchies). The latter we distinguish for use by informal terminologies vs. formal ontologies. We then evaluate the guidelines with a spectrum of widely used terminologies and ontologies to examine how the lexical guidelines are implemented, and whether our proposed guidelines would enhance interoperability. Copyright © 2012 Elsevier Inc. All rights reserved.

  17. Desiderata for ontologies to be used in semantic annotation of biomedical documents.

    Science.gov (United States)

    Bada, Michael; Hunter, Lawrence

    2011-02-01

    A wealth of knowledge valuable to the translational research scientist is contained within the vast biomedical literature, but this knowledge is typically in the form of natural language. Sophisticated natural-language-processing systems are needed to translate text into unambiguous formal representations grounded in high-quality consensus ontologies, and these systems in turn rely on gold-standard corpora of annotated documents for training and testing. To this end, we are constructing the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-text biomedical journal articles that are being manually annotated with the entire sets of terms from select vocabularies, predominantly from the Open Biomedical Ontologies (OBO) library. Our efforts in building this corpus has illuminated infelicities of these ontologies with respect to the semantic annotation of biomedical documents, and we propose desiderata whose implementation could substantially improve their utility in this task; these include the integration of overlapping terms across OBOs, the resolution of OBO-specific ambiguities, the integration of the BFO with the OBOs and the use of mid-level ontologies, the inclusion of noncanonical instances, and the expansion of relations and realizable entities. Copyright © 2010 Elsevier Inc. All rights reserved.

  18. Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

    Science.gov (United States)

    Dos Reis, Julio Cesar; Dinh, Duy; Da Silveira, Marcos; Pruski, Cédric; Reynaud-Delaître, Chantal

    2015-03-01

    Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappings are highly demanded. The accuracy of such methods relies on the available description about the evolution of ontologies, especially regarding concepts involved in mappings. However, from one ontology version to another, a further understanding of ontology changes relevant for supporting mapping adaptation is typically lacking. This research work defines a set of change patterns at the level of concept attributes, and proposes original methods to automatically recognize instances of these patterns based on the similarity between attributes denoting the evolving concepts. This investigation evaluates the benefits of the proposed methods and the influence of the recognized change patterns to select the strategies for mapping adaptation. The summary of the findings is as follows: (1) the Precision (>60%) and Recall (>35%) achieved by comparing manually identified change patterns with the automatic ones; (2) a set of potential impact of recognized change patterns on the way mappings is adapted. We found that the detected correlations cover ∼66% of the mapping adaptation actions with a positive impact; and (3) the influence of the similarity coefficient calculated between concept attributes on the performance of the recognition algorithms. The experimental evaluations conducted with real life science ontologies showed the effectiveness of our approach to accurately characterize ontology evolution at the level of concept attributes. This investigation confirmed the relevance of the proposed change patterns to support decisions on mapping adaptation. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. A case-study of ontology-driven semantic mediation of flower-visiting data from heterogeneous data-stores in three South African natural history collections

    CSIR Research Space (South Africa)

    Coetzer, W

    2013-05-01

    Full Text Available -study of ontology-driven semantic mediation using records of flower-visiting insects from three natural history collections in South Africa. We establish a conceptual domain model for flower-visiting, expressed in an OWL ontology, and use it to semantically enrich...

  20. OlyMPUS - The Ontology-based Metadata Portal for Unified Semantics

    Science.gov (United States)

    Huffer, E.; Gleason, J. L.

    2015-12-01

    The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support data consumers and data providers, enabling the latter to register their data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS leverages the semantics and reasoning capabilities of ODISEES to provide data producers with a semi-automated interface for producing the semantically rich metadata needed to support ODISEES' data discovery and access services. It integrates the ODISEES metadata search system with multiple NASA data delivery tools to enable data consumers to create customized data sets for download to their computers, or for NASA Advanced Supercomputing (NAS) facility registered users, directly to NAS storage resources for access by applications running on NAS supercomputers. A core function of NASA's Earth Science Division is research and analysis that uses the full spectrum of data products available in NASA archives. Scientists need to perform complex analyses that identify correlations and non-obvious relationships across all types of Earth System phenomena. Comprehensive analytics are hindered, however, by the fact that many Earth science data products are disparate and hard to synthesize. Variations in how data are collected, processed, gridded, and stored, create challenges for data interoperability and synthesis, which are exacerbated by the sheer volume of available data. Robust, semantically rich metadata can support tools for data discovery and facilitate machine-to-machine transactions with services such as data subsetting, regridding, and reformatting. Such capabilities are critical to enabling the research activities integral to NASA's strategic plans. However, as metadata requirements increase and competing standards emerge

  1. Coupling ontology driven semantic representation with multilingual natural language generation for tuning international terminologies.

    Science.gov (United States)

    Rassinoux, Anne-Marie; Baud, Robert H; Rodrigues, Jean-Marie; Lovis, Christian; Geissbühler, Antoine

    2007-01-01

    The importance of clinical communication between providers, consumers and others, as well as the requisite for computer interoperability, strengthens the need for sharing common accepted terminologies. Under the directives of the World Health Organization (WHO), an approach is currently being conducted in Australia to adopt a standardized terminology for medical procedures that is intended to become an international reference. In order to achieve such a standard, a collaborative approach is adopted, in line with the successful experiment conducted for the development of the new French coding system CCAM. Different coding centres are involved in setting up a semantic representation of each term using a formal ontological structure expressed through a logic-based representation language. From this language-independent representation, multilingual natural language generation (NLG) is performed to produce noun phrases in various languages that are further compared for consistency with the original terms. Outcomes are presented for the assessment of the International Classification of Health Interventions (ICHI) and its translation into Portuguese. The initial results clearly emphasize the feasibility and cost-effectiveness of the proposed method for handling both a different classification and an additional language. NLG tools, based on ontology driven semantic representation, facilitate the discovery of ambiguous and inconsistent terms, and, as such, should be promoted for establishing coherent international terminologies.

  2. Supporting spatial data harmonization process with the use of ontologies and Semantic Web technologies

    Science.gov (United States)

    Strzelecki, M.; Iwaniak, A.; Łukowicz, J.; Kaczmarek, I.

    2013-10-01

    Nowadays, spatial information is not only used by professionals, but also by common citizens, who uses it for their daily activities. Open Data initiative states that data should be freely and unreservedly available for all users. It also applies to spatial data. As spatial data becomes widely available it is essential to publish it in form which guarantees the possibility of integrating it with other, heterogeneous data sources. Interoperability is the possibility to combine spatial data sets from different sources in a consistent way as well as providing access to it. Providing syntactic interoperability based on well-known data formats is relatively simple, unlike providing semantic interoperability, due to the multiple possible data interpretation. One of the issues connected with the problem of achieving interoperability is data harmonization. It is a process of providing access to spatial data in a representation that allows combining it with other harmonized data in a coherent way by using a common set of data product specification. Spatial data harmonization is performed by creating definition of reclassification and transformation rules (mapping schema) for source application schema. Creation of those rules is a very demanding task which requires wide domain knowledge and a detailed look into application schemas. The paper focuses on proposing methods for supporting data harmonization process, by automated or supervised creation of mapping schemas with the use of ontologies, ontology matching methods and Semantic Web technologies.

  3. Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

    Science.gov (United States)

    Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

    2015-05-01

    Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

  4. Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

    Science.gov (United States)

    Gómez A, Héctor F.; Martínez-Tomás, Rafael; Arias Tapia, Susana A.; Rincón Zamorano, Mariano

    2014-04-01

    Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

  5. Using XML technology for the ontology-based semantic integration of life science databases.

    Science.gov (United States)

    Philippi, Stephan; Köhler, Jacob

    2004-06-01

    Several hundred internet accessible life science databases with constantly growing contents and varying areas of specialization are publicly available via the internet. Database integration, consequently, is a fundamental prerequisite to be able to answer complex biological questions. Due to the presence of syntactic, schematic, and semantic heterogeneities, large scale database integration at present takes considerable efforts. As there is a growing apprehension of extensible markup language (XML) as a means for data exchange in the life sciences, this article focuses on the impact of XML technology on database integration in this area. In detail, a general architecture for ontology-driven data integration based on XML technology is introduced, which overcomes some of the traditional problems in this area. As a proof of concept, a prototypical implementation of this architecture based on a native XML database and an expert system shell is described for the realization of a real world integration scenario.

  6. An ontology-based semantic configuration approach to constructing Data as a Service for enterprises

    Science.gov (United States)

    Cai, Hongming; Xie, Cheng; Jiang, Lihong; Fang, Lu; Huang, Chenxi

    2016-03-01

    To align business strategies with IT systems, enterprises should rapidly implement new applications based on existing information with complex associations to adapt to the continually changing external business environment. Thus, Data as a Service (DaaS) has become an enabling technology for enterprise through information integration and the configuration of existing distributed enterprise systems and heterogonous data sources. However, business modelling, system configuration and model alignment face challenges at the design and execution stages. To provide a comprehensive solution to facilitate data-centric application design in a highly complex and large-scale situation, a configurable ontology-based service integrated platform (COSIP) is proposed to support business modelling, system configuration and execution management. First, a meta-resource model is constructed and used to describe and encapsulate information resources by way of multi-view business modelling. Then, based on ontologies, three semantic configuration patterns, namely composite resource configuration, business scene configuration and runtime environment configuration, are designed to systematically connect business goals with executable applications. Finally, a software architecture based on model-view-controller (MVC) is provided and used to assemble components for software implementation. The result of the case study demonstrates that the proposed approach provides a flexible method of implementing data-centric applications.

  7. The Open-Multinet Upper Ontology Towards the Semantic-based Management of Federated Infrastructures

    Directory of Open Access Journals (Sweden)

    Alexander Willner

    2015-12-01

    Full Text Available The Internet remains an unfinished work. There are several approaches to enhancing it that have been experimentally validated within federated testbed environments. To best gain scientific knowledge from these studies, reproducibility and automation are needed in all areas of the experiment life cycle. Within the GENI and FIRE context, several architectures and protocols have been developed for this purpose. However, a major open research issue remains, namely the description and discovery of the heterogeneous resources involved. To remedy this, we propose a semantic information model that can be used to allow declarative interoperability, build dependency graphs, validate requests, infer knowledge and conduct complex queries. The requirements for such an information model have been extracted from current international Future Internet research projects and the practicality of the model is being evaluated through initial implementations. The main outcome of this work is the definition of the Open-Multinet Upper Ontology and related sub-ontologies, which can be used to describe and manage federated infrastructures and their resources.

  8. Recognition rights, mental health consumers and reconstructive cultural semantics

    Directory of Open Access Journals (Sweden)

    Radden Jennifer H

    2012-01-01

    Full Text Available Abstract Introduction Those in mental health-related consumer movements have made clear their demands for humane treatment and basic civil rights, an end to stigma and discrimination, and a chance to participate in their own recovery. But theorizing about the politics of recognition, 'recognition rights' and epistemic justice, suggests that they also have a stake in the broad cultural meanings associated with conceptions of mental health and illness. Results First person accounts of psychiatric diagnosis and mental health care (shown here to represent 'counter stories' to the powerful 'master narrative' of biomedical psychiatry, offer indications about how experiences of mental disorder might be reframed and redefined as part of efforts to acknowledge and honor recognition rights and epistemic justice. However, the task of cultural semantics is one for the entire culture, not merely consumers. These new meanings must be negotiated. When they are not the result of negotiation, group-wrought definitions risk imposing a revision no less constraining than the mis-recognizing one it aims to replace. Contested realities make this a challenging task when it comes to cultural meanings about mental disorder. Examples from mental illness memoirs about two contested realities related to psychosis are examined here: the meaninglessness of symptoms, and the role of insight into illness. They show the magnitude of the challenge involved - for consumers, practitioners, and the general public - in the reconstruction of these new meanings and realities. Conclusion To honor recognition rights and epistemic justice acknowledgement must be made of the heterogeneity of the effects of, and of responses to, psychiatric diagnosis and care, and the extent of the challenge of the reconstructive cultural semantics involved.

  9. Desain Sistem Semantic Data Warehouse dengan Metode Ontology dan Rule Based untuk Mengolah Data Akademik Universitas XYZ di Bali

    Directory of Open Access Journals (Sweden)

    Made Pradnyana Ambara

    2016-06-01

    Full Text Available Data warehouse pada umumnya yang sering dikenal data warehouse tradisional mempunyai beberapa kelemahan yang mengakibatkan kualitas data yang dihasilkan tidak spesifik dan efektif. Sistem semantic data warehouse merupakan solusi untuk menangani permasalahan pada data warehouse tradisional dengan kelebihan antara lain: manajeman kualitas data yang spesifik dengan format data seragam untuk mendukung laporan OLAP yang baik, dan performance pencarian informasi yang lebih efektif dengan kata kunci bahasa alami. Pemodelan sistem semantic data warehouse menggunakan metode ontology menghasilkan model resource description framework schema (RDFS logic yang akan ditransformasikan menjadi snowflake schema. Laporan akademik yang dibutuhkan dihasilkan melalui metode nine step Kimball dan pencarian semantic menggunakan metode rule based. Pengujian dilakukan menggunakan dua metode uji yaitu pengujian dengan black box testing dan angket kuesioner cheklist. Dari hasil penelitian ini dapat disimpulkan bahwa sistem semantic data warehouse dapat membantu proses pengolahan data akademik yang menghasilkan laporan yang berkualitas untuk mendukung proses pengambilan keputusan.

  10. Semantic Ambiguity Effects in L2 Word Recognition.

    Science.gov (United States)

    Ishida, Tomomi

    2018-06-01

    The present study examined the ambiguity effects in second language (L2) word recognition. Previous studies on first language (L1) lexical processing have observed that ambiguous words are recognized faster and more accurately than unambiguous words on lexical decision tasks. In this research, L1 and L2 speakers of English were asked whether a letter string on a computer screen was an English word or not. An ambiguity advantage was found for both groups and greater ambiguity effects were found for the non-native speaker group when compared to the native speaker group. The findings imply that the larger ambiguity advantage for L2 processing is due to their slower response time in producing adequate feedback activation from the semantic level to the orthographic level.

  11. Semantic Web Services with Web Ontology Language (OWL-S) - Specification of Agent-Services for DARPA Agent Markup Language (DAML)

    Science.gov (United States)

    2006-08-01

    Sycara, and T. Nishimura, "Towards a Semantic Web Ecommerce ," in Proceedings of 6th Conference on Business Information Systems (BIS2003), Colorado...the ontology used is the fictitious ontology http://fly.com/Onto. The advantage of using concepts from Web-addressable ontologies, rather than XML...the advantage of the OWL-S approach compared with other approaches, namely BPEL4WS and WS-CDL, is that OWL-S allows the flexibility to change the

  12. A Concept Lattice for Semantic Integration of Geo-Ontologies Based on Weight of Inclusion Degree Importance and Information Entropy

    Directory of Open Access Journals (Sweden)

    Jia Xiao

    2016-11-01

    Full Text Available Constructing a merged concept lattice with formal concept analysis (FCA is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies.

  13. Using semantic analysis to improve speech recognition performance

    OpenAIRE

    Erdoğan, Hakan; Erdogan, Hakan; Sarıkaya, Ruhi; Sarikaya, Ruhi; Chen, Stanley F.; Gao, Yuqing; Picheny, Michael

    2005-01-01

    Although syntactic structure has been used in recent work in language modeling, there has not been much effort in using semantic analysis for language models. In this study, we propose three new language modeling techniques that use semantic analysis for spoken dialog systems. We call these methods concept sequence modeling, two-level semantic-lexical modeling, and joint semantic-lexical modeling. These models combine lexical information with varying amounts of semantic information, using ann...

  14. Word recognition in Alzheimer's disease: Effects of semantic degeneration.

    Science.gov (United States)

    Cuetos, Fernando; Arce, Noemí; Martínez, Carmen; Ellis, Andrew W

    2017-03-01

    Impairments of word recognition in Alzheimer's disease (AD) have been less widely investigated than impairments affecting word retrieval and production. In particular, we know little about what makes individual words easier or harder for patients with AD to recognize. We used a lexical selection task in which participants were shown sets of four items, each set consisting of one word and three non-words. The task was simply to point to the word on each trial. Forty patients with mild-to-moderate AD were significantly impaired on this task relative to matched controls who made very few errors. The number of patients with AD able to recognize each word correctly was predicted by the frequency, age of acquisition, and imageability of the words, but not by their length or number of orthographic neighbours. Patient Mini-Mental State Examination and phonological fluency scores also predicted the number of words recognized. We propose that progressive degradation of central semantic representations in AD differentially affects the ability to recognize low-imageability, low-frequency, late-acquired words, with the same factors affecting word recognition as affecting word retrieval. © 2015 The British Psychological Society.

  15. LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

    Science.gov (United States)

    Katić, Darko; Julliard, Chantal; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie; Jannin, Pierre; Gibaud, Bernard

    2015-09-01

    The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial. However, most existing systems do not represent knowledge in a reusable way, hindering also reuse of data. Our purpose is therefore to make our computational models of medical knowledge sharable, extensible and interoperational with established knowledge representations in the form of the LapOntoSPM ontology. To show its usefulness, we apply it to situation interpretation, i.e., the recognition of surgical phases based on surgical activities. Considering best practices in ontology engineering and building on our ontology for laparoscopy, we formalized the workflow of laparoscopic adrenalectomies, cholecystectomies and pancreatic resections in the framework of OntoSPM, a new standard for surgical process models. Furthermore, we provide a rule-based situation interpretation algorithm based on SQWRL to recognize surgical phases using the ontology. The system was evaluated on ground-truth data from 19 manually annotated surgeries. The aim was to show that the phase recognition capabilities are equal to a specialized solution. The recognition rates of the new system were equal to the specialized one. However, the time needed to interpret a situation rose from 0.5 to 1.8 s on average which is still viable for practical application. We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data

  16. Effects of Semantic Context and Fundamental Frequency Contours on Mandarin Speech Recognition by Second Language Learners.

    Science.gov (United States)

    Zhang, Linjun; Li, Yu; Wu, Han; Li, Xin; Shu, Hua; Zhang, Yang; Li, Ping

    2016-01-01

    Speech recognition by second language (L2) learners in optimal and suboptimal conditions has been examined extensively with English as the target language in most previous studies. This study extended existing experimental protocols (Wang et al., 2013) to investigate Mandarin speech recognition by Japanese learners of Mandarin at two different levels (elementary vs. intermediate) of proficiency. The overall results showed that in addition to L2 proficiency, semantic context, F0 contours, and listening condition all affected the recognition performance on the Mandarin sentences. However, the effects of semantic context and F0 contours on L2 speech recognition diverged to some extent. Specifically, there was significant modulation effect of listening condition on semantic context, indicating that L2 learners made use of semantic context less efficiently in the interfering background than in quiet. In contrast, no significant modulation effect of listening condition on F0 contours was found. Furthermore, there was significant interaction between semantic context and F0 contours, indicating that semantic context becomes more important for L2 speech recognition when F0 information is degraded. None of these effects were found to be modulated by L2 proficiency. The discrepancy in the effects of semantic context and F0 contours on L2 speech recognition in the interfering background might be related to differences in processing capacities required by the two types of information in adverse listening conditions.

  17. An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

    Science.gov (United States)

    Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

    2008-10-01

    This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

  18. Ontology Design Patterns: Bridging the Gap Between Local Semantic Use Cases and Large-Scale, Long-Term Data Integration

    Science.gov (United States)

    Shepherd, Adam; Arko, Robert; Krisnadhi, Adila; Hitzler, Pascal; Janowicz, Krzysztof; Chandler, Cyndy; Narock, Tom; Cheatham, Michelle; Schildhauer, Mark; Jones, Matt; Raymond, Lisa; Mickle, Audrey; Finin, Tim; Fils, Doug; Carbotte, Suzanne; Lehnert, Kerstin

    2015-04-01

    Integrating datasets for new use cases is one of the common drivers for adopting semantic web technologies. Even though linked data principles enables this type of activity over time, the task of reconciling new ontological commitments for newer use cases can be daunting. This situation was faced by the Biological and Chemical Oceanography Data Management Office (BCO-DMO) as it sought to integrate its existing linked data with other data repositories to address newer scientific use cases as a partner in the GeoLink Project. To achieve a successful integration with other GeoLink partners, BCO-DMO's metadata would need to be described using the new ontologies developed by the GeoLink partners - a situation that could impact semantic inferencing, pre-existing software and external users of BCO-DMO's linked data. This presentation describes the process of how GeoLink is bridging the gap between local, pre-existing ontologies to achieve scientific metadata integration for all its partners through the use of ontology design patterns. GeoLink, an NSF EarthCube Building Block, brings together experts from the geosciences, computer science, and library science in an effort to improve discovery and reuse of data and knowledge. Its participating repositories include content from field expeditions, laboratory analyses, journal publications, conference presentations, theses/reports, and funding awards that span scientific studies from marine geology to marine ecology and biogeochemistry to paleoclimatology. GeoLink's outcomes include a set of reusable ontology design patterns (ODPs) that describe core geoscience concepts, a network of Linked Data published by participating repositories using those ODPs, and tools to facilitate discovery of related content in multiple repositories.

  19. Semantic metrics

    OpenAIRE

    Hu, Bo; Kalfoglou, Yannis; Dupplaw, David; Alani, Harith; Lewis, Paul; Shadbolt, Nigel

    2006-01-01

    In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a...

  20. The Influence of Semantic Constraints on Bilingual Word Recognition during Sentence Reading

    Science.gov (United States)

    Van Assche, Eva; Drieghe, Denis; Duyck, Wouter; Welvaert, Marijke; Hartsuiker, Robert J.

    2011-01-01

    The present study investigates how semantic constraint of a sentence context modulates language-non-selective activation in bilingual visual word recognition. We recorded Dutch-English bilinguals' eye movements while they read cognates and controls in low and high semantically constraining sentences in their second language. Early and late…

  1. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology.

    Science.gov (United States)

    Caniza, Horacio; Romero, Alfonso E; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-08-01

    We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve the accuracy of similarity measures. GOssTo is very fast, easy to use, and it allows the calculation of similarities on a genomic scale in a few minutes on a regular desktop machine. alberto@cs.rhul.ac.uk GOssTo is available both as a stand-alone application running on GNU/Linux, Windows and MacOS from www.paccanarolab.org/gossto and as a web application from www.paccanarolab.org/gosstoweb. The stand-alone application features a simple and concise command line interface for easy integration into high-throughput data processing pipelines. © The Author 2014. Published by Oxford University Press.

  2. Brain mechanisms of successful recognition through retrieval of semantic context.

    Science.gov (United States)

    Flegal, Kristin E; Marín-Gutiérrez, Alejandro; Ragland, J Daniel; Ranganath, Charan

    2014-08-01

    Episodic memory is associated with the encoding and retrieval of context information and with a subjective sense of reexperiencing past events. The neural correlates of episodic retrieval have been extensively studied using fMRI, leading to the identification of a "general recollection network" including medial temporal, parietal, and prefrontal regions. However, in these studies, it is difficult to disentangle the effects of context retrieval from recollection. In this study, we used fMRI to determine the extent to which the recruitment of regions in the recollection network is contingent on context reinstatement. Participants were scanned during a cued recognition test for target words from encoded sentences. Studied target words were preceded by either a cue word studied in the same sentence (thus congruent with encoding context) or a cue word studied in a different sentence (thus incongruent with encoding context). Converging fMRI results from independently defined ROIs and whole-brain analysis showed regional specificity in the recollection network. Activity in hippocampus and parahippocampal cortex was specifically increased during successful retrieval following congruent context cues, whereas parietal and prefrontal components of the general recollection network were associated with confident retrieval irrespective of contextual congruency. Our findings implicate medial temporal regions in the retrieval of semantic context, contributing to, but dissociable from, recollective experience.

  3. The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

    Science.gov (United States)

    Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; Vasilevsky, Nicole; Baynam, Gareth; Zemojtel, Tomasz; Schriml, Lynn Marie; Kibbe, Warren Alden; Schofield, Paul N.; Beck, Tim; Vasant, Drashtti; Brookes, Anthony J.; Zankl, Andreas; Washington, Nicole L.; Mungall, Christopher J.; Lewis, Suzanna E.; Haendel, Melissa A.; Parkinson, Helen; Robinson, Peter N.

    2015-01-01

    The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available. PMID:26119816

  4. Speaker information affects false recognition of unstudied lexical-semantic associates.

    Science.gov (United States)

    Luthra, Sahil; Fox, Neal P; Blumstein, Sheila E

    2018-05-01

    Recognition of and memory for a spoken word can be facilitated by a prior presentation of that word spoken by the same talker. However, it is less clear whether this speaker congruency advantage generalizes to facilitate recognition of unheard related words. The present investigation employed a false memory paradigm to examine whether information about a speaker's identity in items heard by listeners could influence the recognition of novel items (critical intruders) phonologically or semantically related to the studied items. In Experiment 1, false recognition of semantically associated critical intruders was sensitive to speaker information, though only when subjects attended to talker identity during encoding. Results from Experiment 2 also provide some evidence that talker information affects the false recognition of critical intruders. Taken together, the present findings indicate that indexical information is able to contact the lexical-semantic network to affect the processing of unheard words.

  5. Combining Semantic and Acoustic Features for Valence and Arousal Recognition in Speech

    DEFF Research Database (Denmark)

    Karadogan, Seliz; Larsen, Jan

    2012-01-01

    The recognition of affect in speech has attracted a lot of interest recently; especially in the area of cognitive and computer sciences. Most of the previous studies focused on the recognition of basic emotions (such as happiness, sadness and anger) using categorical approach. Recently, the focus...... has been shifting towards dimensional affect recognition based on the idea that emotional states are not independent from one another but related in a systematic manner. In this paper, we design a continuous dimensional speech affect recognition model that combines acoustic and semantic features. We...... show that combining semantic and acoustic information for dimensional speech recognition improves the results. Moreover, we show that valence is better estimated using semantic features while arousal is better estimated using acoustic features....

  6. [Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

    Science.gov (United States)

    Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

    2012-07-01

    In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

  7. Semantic similarity between old and new items produces false alarms in recognition memory.

    Science.gov (United States)

    Montefinese, Maria; Zannino, Gian Daniele; Ambrosini, Ettore

    2015-09-01

    In everyday life, human beings can report memories of past events that did not occur or that occurred differently from the way they remember them because memory is an imperfect process of reconstruction and is prone to distortion and errors. In this recognition study using word stimuli, we investigated whether a specific operationalization of semantic similarity among concepts can modulate false memories while controlling for the possible effect of associative strength and word co-occurrence in an old-new recognition task. The semantic similarity value of each new concept was calculated as the mean cosine similarity between pairs of vectors representing that new concept and each old concept belonging to the same semantic category. Results showed that, compared with (new) low-similarity concepts, (new) high-similarity concepts had significantly higher probability of being falsely recognized as old, even after partialling out the effect of confounding variables, including associative relatedness and lexical co-occurrence. This finding supports the feature-based view of semantic memory, suggesting that meaning overlap and sharing of semantic features (which are greater when more similar semantic concepts are being processed) have an influence on recognition performance, resulting in more false alarms for new high-similarity concepts. We propose that the associative strength and word co-occurrence among concepts are not sufficient to explain illusory memories but is important to take into account also the effects of feature-based semantic relations, and, in particular, the semantic similarity among concepts.

  8. Semantic knowledge for histopathological image analysis: from ontologies to processing portals and deep learning

    Science.gov (United States)

    Kergosien, Yannick L.; Racoceanu, Daniel

    2017-11-01

    This article presents our vision about the next generation of challenges in computational/digital pathology. The key role of the domain ontology, developed in a sustainable manner (i.e. using reference checklists and protocols, as the living semantic repositories), opens the way to effective/sustainable traceability and relevance feedback concerning the use of existing machine learning algorithms, proven to be very performant in the latest digital pathology challenges (i.e. convolutional neural networks). Being able to work in an accessible web-service environment, with strictly controlled issues regarding intellectual property (image and data processing/analysis algorithms) and medical data/image confidentiality is essential for the future. Among the web-services involved in the proposed approach, the living yellow pages in the area of computational pathology seems to be very important in order to reach an operational awareness, validation, and feasibility. This represents a very promising way to go to the next generation of tools, able to bring more guidance to the computer scientists and confidence to the pathologists, towards an effective/efficient daily use. Besides, a consistent feedback and insights will be more likely to emerge in the near future - from these sophisticated machine learning tools - back to the pathologists-, strengthening, therefore, the interaction between the different actors of a sustainable biomedical ecosystem (patients, clinicians, biologists, engineers, scientists etc.). Beside going digital/computational - with virtual slide technology demanding new workflows-, Pathology must prepare for another coming revolution: semantic web technologies now enable the knowledge of experts to be stored in databases, shared through the Internet, and accessible by machines. Traceability, disambiguation of reports, quality monitoring, interoperability between health centers are some of the associated benefits that pathologists were seeking. However

  9. Reviewing the design of DAML+OIL : An ontology language for the Semantic Web

    NARCIS (Netherlands)

    Horrocks, Ian; Patel-Schneider, Peter F.; Van Harmelen, Frank

    2002-01-01

    In the current "Syntactic Web", uninterpreted syntactic constructs are given meaning only by private off-line agreements that are inaccessible to computers. In the Semantic Web vision, this is replaced by a web where both data and its semantic definition are accessible and manipulable by computer

  10. Effects of perceptual similarity but not semantic association on false recognition in aging

    Directory of Open Access Journals (Sweden)

    Kayleigh Burnside

    2017-12-01

    Full Text Available This study investigated semantic and perceptual influences on false recognition in older and young adults in a variant on the Deese-Roediger-McDermott paradigm. In two experiments, participants encoded intermixed sets of semantically associated words, and sets of unrelated words. Each set was presented in a shared distinctive font. Older adults were no more likely to falsely recognize semantically associated lure words compared to unrelated lures also presented in studied fonts. However, they showed an increase in false recognition of lures which were related to studied items only by a shared font. This increased false recognition was associated with recollective experience. The data show that older adults do not always rely more on prior knowledge in episodic memory tasks. They converge with other findings suggesting that older adults may also be more prone to perceptually-driven errors.

  11. Ontology for Semantic Data Integration in the Domain of IT Benchmarking.

    Science.gov (United States)

    Pfaff, Matthias; Neubig, Stefan; Krcmar, Helmut

    2018-01-01

    A domain-specific ontology for IT benchmarking has been developed to bridge the gap between a systematic characterization of IT services and their data-based valuation. Since information is generally collected during a benchmark exercise using questionnaires on a broad range of topics, such as employee costs, software licensing costs, and quantities of hardware, it is commonly stored as natural language text; thus, this information is stored in an intrinsically unstructured form. Although these data form the basis for identifying potentials for IT cost reductions, neither a uniform description of any measured parameters nor the relationship between such parameters exists. Hence, this work proposes an ontology for the domain of IT benchmarking, available at https://w3id.org/bmontology. The design of this ontology is based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years. The development of the ontology and its main concepts is described in detail (i.e., the conceptualization of benchmarking events, questionnaires, IT services, indicators and their values) together with its alignment with the DOLCE-UltraLite foundational ontology.

  12. Scientific Reproducibility in Biomedical Research: Provenance Metadata Ontology for Semantic Annotation of Study Description.

    Science.gov (United States)

    Sahoo, Satya S; Valdez, Joshua; Rueschman, Michael

    2016-01-01

    Scientific reproducibility is key to scientific progress as it allows the research community to build on validated results, protect patients from potentially harmful trial drugs derived from incorrect results, and reduce wastage of valuable resources. The National Institutes of Health (NIH) recently published a systematic guideline titled "Rigor and Reproducibility " for supporting reproducible research studies, which has also been accepted by several scientific journals. These journals will require published articles to conform to these new guidelines. Provenance metadata describes the history or origin of data and it has been long used in computer science to capture metadata information for ensuring data quality and supporting scientific reproducibility. In this paper, we describe the development of Provenance for Clinical and healthcare Research (ProvCaRe) framework together with a provenance ontology to support scientific reproducibility by formally modeling a core set of data elements representing details of research study. We extend the PROV Ontology (PROV-O), which has been recommended as the provenance representation model by World Wide Web Consortium (W3C), to represent both: (a) data provenance, and (b) process provenance. We use 124 study variables from 6 clinical research studies from the National Sleep Research Resource (NSRR) to evaluate the coverage of the provenance ontology. NSRR is the largest repository of NIH-funded sleep datasets with 50,000 studies from 36,000 participants. The provenance ontology reuses ontology concepts from existing biomedical ontologies, for example the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), to model the provenance information of research studies. The ProvCaRe framework is being developed as part of the Big Data to Knowledge (BD2K) data provenance project.

  13. A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

    OpenAIRE

    Okoye, Kingsley; Tawil, Abdel-Rahman; Naeem, Usman; Lamine, Elyes

    2015-01-01

    Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respo...

  14. OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

    Science.gov (United States)

    Huang, Jingshan; Gutierrez, Fernando; Strachan, Harrison J; Dou, Dejing; Huang, Weili; Smith, Barry; Blake, Judith A; Eilbeck, Karen; Natale, Darren A; Lin, Yu; Wu, Bin; Silva, Nisansa de; Wang, Xiaowei; Liu, Zixing; Borchert, Glen M; Tan, Ming; Ruttenberg, Alan

    2016-01-01

    As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software.

  15. Semantic and visual determinants of face recognition in a prosopagnosic patient.

    Science.gov (United States)

    Dixon, M J; Bub, D N; Arguin, M

    1998-05-01

    Prosopagnosia is the neuropathological inability to recognize familiar people by their faces. It can occur in isolation or can coincide with recognition deficits for other nonface objects. Often, patients whose prosopagnosia is accompanied by object recognition difficulties have more trouble identifying certain categories of objects relative to others. In previous research, we demonstrated that objects that shared multiple visual features and were semantically close posed severe recognition difficulties for a patient with temporal lobe damage. We now demonstrate that this patient's face recognition is constrained by these same parameters. The prosopagnosic patient ELM had difficulties pairing faces to names when the faces shared visual features and the names were semantically related (e.g., Tonya Harding, Nancy Kerrigan, and Josee Chouinard -three ice skaters). He made tenfold fewer errors when the exact same faces were associated with semantically unrelated people (e.g., singer Celine Dion, actress Betty Grable, and First Lady Hillary Clinton). We conclude that prosopagnosia and co-occurring category-specific recognition problems both stem from difficulties disambiguating the stored representations of objects that share multiple visual features and refer to semantically close identities or concepts.

  16. Semantic Network Adaptation Based on QoS Pattern Recognition for Multimedia Streams

    Science.gov (United States)

    Exposito, Ernesto; Gineste, Mathieu; Lamolle, Myriam; Gomez, Jorge

    This article proposes an ontology based pattern recognition methodology to compute and represent common QoS properties of the Application Data Units (ADU) of multimedia streams. The use of this ontology by mechanisms located at different layers of the communication architecture will allow implementing fine per-packet self-optimization of communication services regarding the actual application requirements. A case study showing how this methodology is used by error control mechanisms in the context of wireless networks is presented in order to demonstrate the feasibility and advantages of this approach.

  17. The Effects of Semantic Transparency and Base Frequency on the Recognition of English Complex Words

    Science.gov (United States)

    Xu, Joe; Taft, Marcus

    2015-01-01

    A visual lexical decision task was used to examine the interaction between base frequency (i.e., the cumulative frequencies of morphologically related forms) and semantic transparency for a list of derived words. Linear mixed effects models revealed that high base frequency facilitates the recognition of the complex word (i.e., a "base…

  18. A Patient with Difficulty of Object Recognition: Semantic Amnesia for Manipulable Objects

    Directory of Open Access Journals (Sweden)

    A. Yamadori

    1992-01-01

    Full Text Available We studied a patient who had recognition difficulty for manipulable objects. MRI showed a lesion in the left occipito-parietotemporal area. Differential diagnosis of agnosia, aphasia and apraxia is discussed. We believe this “object meaning amnesia” constitutes a distinct subtype of semantic amnesia.

  19. Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

    Science.gov (United States)

    Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

    2014-07-21

    Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

  20. Enacting the Semantic Web: Ontological Orderings, Negotiated Standards, and Human-Machine Translations

    Science.gov (United States)

    McCarthy, Matthew T.

    2017-01-01

    Artificial intelligence (AI) that is based upon semantic search has become one of the dominant means for accessing information in recent years. This is particularly the case in mobile contexts, as search-based AI are embedded in each of the major mobile operating systems. The implications are such that information is becoming less a matter of…

  1. Reasoning and Ontologies for Personalized E-Learning in the Semantic Web

    Science.gov (United States)

    Henze, Nicola; Dolog, Peter; Nejdl, Wolfgang

    2004-01-01

    The challenge of the semantic web is the provision of distributed information with well-defined meaning, understandable for different parties. Particularly, applications should be able to provide individually optimized access to information by taking the individual needs and requirements of the users into account. In this paper we propose a…

  2. ONTOLOGIES REPRESENTATION AND MANAGEMENT, AS A SEMANTIC TOOL FOR ORGANIZATIONAL MEMORY CONSOLIDATION

    Directory of Open Access Journals (Sweden)

    Mangiuc Dragos Marian

    2009-05-01

    Full Text Available The present paper is a component of an exploratory research project focused on discovering new ways to build, organize and consolidate organizational memory for an economic entity by means of the new a€śSemantic Weba€ť technologies and also encloses some

  3. What does it all mean? Capturing Semantics of Surgical Data and Algorithms with Ontologies

    OpenAIRE

    Katić, Darko; Maleshkova, Maria; Engelhardt, Sandy; Wolf, Ivo; März, Keno; Maier-Hein, Lena; Nolden, Marco; Wagner, Martin; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

    2017-01-01

    Every year approximately 234 million major surgeries are performed, leading to plentiful, highly diverse data. This is accompanied by a matching number of novel algorithms for the surgical domain. To garner all benefits of surgical data science it is necessary to have an unambiguous, shared understanding of algorithms and data. This includes inputs and outputs of algorithms and thus their function, but also the semantic content, i.e. meaning of data such as patient parameters. We therefore pr...

  4. Stimulus-independent semantic bias misdirects word recognition in older adults.

    Science.gov (United States)

    Rogers, Chad S; Wingfield, Arthur

    2015-07-01

    Older adults' normally adaptive use of semantic context to aid in word recognition can have a negative consequence of causing misrecognitions, especially when the word actually spoken sounds similar to a word that more closely fits the context. Word-pairs were presented to young and older adults, with the second word of the pair masked by multi-talker babble varying in signal-to-noise ratio. Results confirmed older adults' greater tendency to misidentify words based on their semantic context compared to the young adults, and to do so with a higher level of confidence. This age difference was unaffected by differences in the relative level of acoustic masking.

  5. No one way ticket from orthography to semantics in recognition memory: N400 and P200 effects of associations.

    Science.gov (United States)

    Stuellein, Nicole; Radach, Ralph R; Jacobs, Arthur M; Hofmann, Markus J

    2016-05-15

    Computational models of word recognition already successfully used associative spreading from orthographic to semantic levels to account for false memories. But can they also account for semantic effects on event-related potentials in a recognition memory task? To address this question, target words in the present study had either many or few semantic associates in the stimulus set. We found larger P200 amplitudes and smaller N400 amplitudes for old words in comparison to new words. Words with many semantic associates led to larger P200 amplitudes and a smaller N400 in comparison to words with a smaller number of semantic associations. We also obtained inverted response time and accuracy effects for old and new words: faster response times and fewer errors were found for old words that had many semantic associates, whereas new words with a large number of semantic associates produced slower response times and more errors. Both behavioral and electrophysiological results indicate that semantic associations between words can facilitate top-down driven lexical access and semantic integration in recognition memory. Our results support neurophysiologically plausible predictions of the Associative Read-Out Model, which suggests top-down connections from semantic to orthographic layers. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Mandarin-Speaking Children’s Speech Recognition: Developmental Changes in the Influences of Semantic Context and F0 Contours

    Directory of Open Access Journals (Sweden)

    Hong Zhou

    2017-06-01

    Full Text Available The goal of this developmental speech perception study was to assess whether and how age group modulated the influences of high-level semantic context and low-level fundamental frequency (F0 contours on the recognition of Mandarin speech by elementary and middle-school-aged children in quiet and interference backgrounds. The results revealed different patterns for semantic and F0 information. One the one hand, age group modulated significantly the use of F0 contours, indicating that elementary school children relied more on natural F0 contours than middle school children during Mandarin speech recognition. On the other hand, there was no significant modulation effect of age group on semantic context, indicating that children of both age groups used semantic context to assist speech recognition to a similar extent. Furthermore, the significant modulation effect of age group on the interaction between F0 contours and semantic context revealed that younger children could not make better use of semantic context in recognizing speech with flat F0 contours compared with natural F0 contours, while older children could benefit from semantic context even when natural F0 contours were altered, thus confirming the important role of F0 contours in Mandarin speech recognition by elementary school children. The developmental changes in the effects of high-level semantic and low-level F0 information on speech recognition might reflect the differences in auditory and cognitive resources associated with processing of the two types of information in speech perception.

  7. Age-Related Differences in Face Recognition: Neural Correlates of Repetition and Semantic Priming in Young and Older Adults

    Science.gov (United States)

    Wiese, Holger; Komes, Jessica; Tüttenberg, Simone; Leidinger, Jana; Schweinberger, Stefan R.

    2017-01-01

    Difficulties in person recognition are among the common complaints associated with cognitive ageing. The present series of experiments therefore investigated face and person recognition in young and older adults. The authors examined how within-domain and cross-domain repetition as well as semantic priming affect familiar face recognition and…

  8. Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms.

    Science.gov (United States)

    Falda, Marco; Toppo, Stefano; Pescarolo, Alessandro; Lavezzo, Enrico; Di Camillo, Barbara; Facchinetti, Andrea; Cilia, Elisa; Velasco, Riccardo; Fontana, Paolo

    2012-03-28

    Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario, the Gene Ontology has provided the means to standardize the annotation classification with a structured vocabulary which can be easily exploited by computational methods. Argot2 is a web-based function prediction tool able to annotate nucleic or protein sequences from small datasets up to entire genomes. It accepts as input a list of sequences in FASTA format, which are processed using BLAST and HMMER searches vs UniProKB and Pfam databases respectively; these sequences are then annotated with GO terms retrieved from the UniProtKB-GOA database and the terms are weighted using the e-values from BLAST and HMMER. The weighted GO terms are processed according to both their semantic similarity relations described by the Gene Ontology and their associated score. The algorithm is based on the original idea developed in a previous tool called Argot. The entire engine has been completely rewritten to improve both accuracy and computational efficiency, thus allowing for the annotation of complete genomes. The revised algorithm has been already employed and successfully tested during in-house genome projects of grape and apple, and has proven to have a high precision and recall in all our benchmark conditions. It has also been successfully compared with Blast2GO, one of the methods most commonly employed for sequence annotation. The server is freely accessible at http://www.medcomp.medicina.unipd.it/Argot2.

  9. Semantic Ambiguity: Do Multiple Meanings Inhibit or Facilitate Word Recognition?

    Science.gov (United States)

    Haro, Juan; Ferré, Pilar

    2018-06-01

    It is not clear whether multiple unrelated meanings inhibit or facilitate word recognition. Some studies have found a disadvantage for words having multiple meanings with respect to unambiguous words in lexical decision tasks (LDT), whereas several others have shown a facilitation for such words. In the present study, we argue that these inconsistent findings may be due to the approach employed to select ambiguous words across studies. To address this issue, we conducted three LDT experiments in which we varied the measure used to classify ambiguous and unambiguous words. The results suggest that multiple unrelated meanings facilitate word recognition. In addition, we observed that the approach employed to select ambiguous words may affect the pattern of experimental results. This evidence has relevant implications for theoretical accounts of ambiguous words processing and representation.

  10. Constructive Ontology Engineering

    Science.gov (United States)

    Sousan, William L.

    2010-01-01

    The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…

  11. An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

    Science.gov (United States)

    Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

    2008-01-01

    Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

  12. The Onset and Time Course of Semantic Priming during Rapid Recognition of Visual Words

    Science.gov (United States)

    Hoedemaker, Renske S.; Gordon, Peter C.

    2016-01-01

    In two experiments, we assessed the effects of response latency and task-induced goals on the onset and time course of semantic priming during rapid processing of visual words as revealed by ocular response tasks. In Experiment 1 (Ocular Lexical Decision Task), participants performed a lexical decision task using eye-movement responses on a sequence of four words. In Experiment 2, the same words were encoded for an episodic recognition memory task that did not require a meta-linguistic judgment. For both tasks, survival analyses showed that the earliest-observable effect (Divergence Point or DP) of semantic priming on target-word reading times occurred at approximately 260 ms, and ex-Gaussian distribution fits revealed that the magnitude of the priming effect increased as a function of response time. Together, these distributional effects of semantic priming suggest that the influence of the prime increases when target processing is more effortful. This effect does not require that the task include a metalinguistic judgment; manipulation of the task goals across experiments affected the overall response speed but not the location of the DP or the overall distributional pattern of the priming effect. These results are more readily explained as the result of a retrospective rather than a prospective priming mechanism and are consistent with compound-cue models of semantic priming. PMID:28230394

  13. The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines

    Directory of Open Access Journals (Sweden)

    Gaston K Mazandu

    2014-08-01

    Full Text Available With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations from different pipelines using semantic similarity measures. We used this approach to identify inconsistencies and similarities in functional annotations between orthologs of human and Drosophila melanogaster, to assess the quality of GO annotations derived from InterPro2GO mappings compared to manually annotated GO annotations for the Drosophila melanogaster proteome from a FlyBase dataset and human, and to filter GO annotation data for these proteomes. Results obtained indicate that an efficient integration of GO annotations eliminates redundancy up to 27.08 and 22.32% in the Drosophila melanogaster and human GO annotation datasets, respectively. Furthermore, we identified lack of and missing annotations for some orthologs, and annotation mismatches between InterPro2GO and manual pipelines in these two proteomes, thus requiring further curation. This simplifies and facilitates tasks of curators in assessing protein annotations, reduces redundancy and eliminates inconsistencies in large annotation datasets for ease of comparative functional genomics.

  14. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  15. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  16. Practical ontologies for information professionals

    CERN Document Server

    AUTHOR|(CDS)2071712

    2016-01-01

    Practical Ontologies for Information Professionals provides an introduction to ontologies and their development, an essential tool for fighting back against information overload. The development of robust and widely used ontologies is an increasingly important tool in the fight against information overload. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and identify new knowledge. This new book provides an accessible introduction to the following: * What is an ontology? Defining the concept and why it is increasingly important to the information professional * Ontologies and the semantic web * Existing ontologies, such as SKOS, OWL, FOAF, schema.org, and the DBpedia Ontology * Adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology with Protege * Interrogating semantic web ontologies * The future of ontologies and the role of the ...

  17. Meaningful Memory in Acute Anorexia Nervosa Patients-Comparing Recall, Learning, and Recognition of Semantically Related and Semantically Unrelated Word Stimuli.

    Science.gov (United States)

    Terhoeven, Valentin; Kallen, Ursula; Ingenerf, Katrin; Aschenbrenner, Steffen; Weisbrod, Matthias; Herzog, Wolfgang; Brockmeyer, Timo; Friederich, Hans-Christoph; Nikendei, Christoph

    2017-03-01

    It is unclear whether observed memory impairment in anorexia nervosa (AN) depends on the semantic structure (categorized words) of material to be encoded. We aimed to investigate the processing of semantically related information in AN. Memory performance was assessed in a recall, learning, and recognition test in 27 adult women with AN (19 restricting, 8 binge-eating/purging subtype; average disease duration: 9.32 years) and 30 healthy controls using an extended version of the Rey Auditory Verbal Learning Test, applying semantically related and unrelated word stimuli. Short-term memory (immediate recall, learning), regardless of semantics of the words, was significantly worse in AN patients, whereas long-term memory (delayed recall, recognition) did not differ between AN patients and controls. Semantics of stimuli do not have a better effect on memory recall in AN compared to CO. Impaired short-term versus long-term memory is discussed in relation to dysfunctional working memory in AN. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

  18. Feature activation during word recognition: action, visual, and associative-semantic priming effects

    Directory of Open Access Journals (Sweden)

    Kevin J.Y. Lam

    2015-05-01

    Full Text Available Embodied theories of language postulate that language meaning is stored in modality-specific brain areas generally involved in perception and action in the real world. However, the temporal dynamics of the interaction between modality-specific information and lexical-semantic processing remain unclear. We investigated the relative timing at which two types of modality-specific information (action-based and visual-form information contribute to lexical-semantic comprehension. To this end, we applied a behavioral priming paradigm in which prime and target words were related with respect to (1 action features, (2 visual features, or (3 semantically associative information. Using a Go/No-Go lexical decision task, priming effects were measured across four different inter-stimulus intervals (ISI = 100 ms, 250 ms, 400 ms, and 1,000 ms to determine the relative time course of the different features . Notably, action priming effects were found in ISIs of 100 ms, 250 ms, and 1,000 ms whereas a visual priming effect was seen only in the ISI of 1,000 ms. Importantly, our data suggest that features follow different time courses of activation during word recognition. In this regard, feature activation is dynamic, measurable in specific time windows but not in others. Thus the current study (1 demonstrates how multiple ISIs can be used within an experiment to help chart the time course of feature activation and (2 provides new evidence for embodied theories of language.

  19. Get rich quick: the signal to respond procedure reveals the time course of semantic richness effects during visual word recognition.

    Science.gov (United States)

    Hargreaves, Ian S; Pexman, Penny M

    2014-05-01

    According to several current frameworks, semantic processing involves an early influence of language-based information followed by later influences of object-based information (e.g., situated simulations; Santos, Chaigneau, Simmons, & Barsalou, 2011). In the present study we examined whether these predictions extend to the influence of semantic variables in visual word recognition. We investigated the time course of semantic richness effects in visual word recognition using a signal-to-respond (STR) paradigm fitted to a lexical decision (LDT) and a semantic categorization (SCT) task. We used linear mixed effects to examine the relative contributions of language-based (number of senses, ARC) and object-based (imageability, number of features, body-object interaction ratings) descriptions of semantic richness at four STR durations (75, 100, 200, and 400ms). Results showed an early influence of number of senses and ARC in the SCT. In both LDT and SCT, object-based effects were the last to influence participants' decision latencies. We interpret our results within a framework in which semantic processes are available to influence word recognition as a function of their availability over time, and of their relevance to task-specific demands. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. The Evidence-base for Using Ontologies and Semantic Integration Methodologies to Support Integrated Chronic Disease Management in Primary and Ambulatory Care: Realist Review. Contribution of the IMIA Primary Health Care Informatics WG.

    Science.gov (United States)

    Liyanage, H; Liaw, S-T; Kuziemsky, C; Terry, A L; Jones, S; Soler, J K; de Lusignan, S

    2013-01-01

    Most chronic diseases are managed in primary and ambulatory care. The chronic care model (CCM) suggests a wide range of community, technological, team and patient factors contribute to effective chronic disease management. Ontologies have the capability to enable formalised linkage of heterogeneous data sources as might be found across the elements of the CCM. To describe the evidence base for using ontologies and other semantic integration methods to support chronic disease management. We reviewed the evidence-base for the use of ontologies and other semantic integration methods within and across the elements of the CCM. We report them using a realist review describing the context in which the mechanism was applied, and any outcome measures. Most evidence was descriptive with an almost complete absence of empirical research and important gaps in the evidence-base. We found some use of ontologies and semantic integration methods for community support of the medical home and for care in the community. Ubiquitous information technology (IT) and other IT tools were deployed to support self-management support, use of shared registries, health behavioural models and knowledge discovery tools to improve delivery system design. Data quality issues restricted the use of clinical data; however there was an increased use of interoperable data and health system integration. Ontologies and semantic integration methods are emergent with limited evidence-base for their implementation. However, they have the potential to integrate the disparate community wide data sources to provide the information necessary for effective chronic disease management.

  1. Integration of low level and ontology derived features for automatic weapon recognition and identification

    Science.gov (United States)

    Sirakov, Nikolay M.; Suh, Sang; Attardo, Salvatore

    2011-06-01

    This paper presents a further step of a research toward the development of a quick and accurate weapons identification methodology and system. A basic stage of this methodology is the automatic acquisition and updating of weapons ontology as a source of deriving high level weapons information. The present paper outlines the main ideas used to approach the goal. In the next stage, a clustering approach is suggested on the base of hierarchy of concepts. An inherent slot of every node of the proposed ontology is a low level features vector (LLFV), which facilitates the search through the ontology. Part of the LLFV is the information about the object's parts. To partition an object a new approach is presented capable of defining the objects concavities used to mark the end points of weapon parts, considered as convexities. Further an existing matching approach is optimized to determine whether an ontological object matches the objects from an input image. Objects from derived ontological clusters will be considered for the matching process. Image resizing is studied and applied to decrease the runtime of the matching approach and investigate its rotational and scaling invariance. Set of experiments are preformed to validate the theoretical concepts.

  2. Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System

    Science.gov (United States)

    Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.

    2008-12-01

    The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so

  3. An Agent-mediated Ontology-based Approach for Composite Activity Recognition in Smart Homes

    OpenAIRE

    Okeyo, George; Chen, Liming; Wang, H.

    2013-01-01

    Activity recognition enables ambient assisted living applications to provide activity-aware services to users in smart homes. Despite significant progress being made in activity recognition research, the focus has been on simple activity recognition leaving composite activity recognition an open problem. For instance, knowledge-driven activity recognition has recently attracted increasing attention but mainly focused on simple activities. This paper extends previous work by introducing a know...

  4. OpenTox predictive toxicology framework: toxicological ontology and semantic media wiki-based OpenToxipedia.

    Science.gov (United States)

    Tcheremenskaia, Olga; Benigni, Romualdo; Nikolova, Ivelina; Jeliazkova, Nina; Escher, Sylvia E; Batke, Monika; Baier, Thomas; Poroikov, Vladimir; Lagunin, Alexey; Rautenberg, Micha; Hardy, Barry

    2012-04-24

    The OpenTox Framework, developed by the partners in the OpenTox project (http://www.opentox.org), aims at providing a unified access to toxicity data, predictive models and validation procedures. Interoperability of resources is achieved using a common information model, based on the OpenTox ontologies, describing predictive algorithms, models and toxicity data. As toxicological data may come from different, heterogeneous sources, a deployed ontology, unifying the terminology and the resources, is critical for the rational and reliable organization of the data, and its automatic processing. The following related ontologies have been developed for OpenTox: a) Toxicological ontology - listing the toxicological endpoints; b) Organs system and Effects ontology - addressing organs, targets/examinations and effects observed in in vivo studies; c) ToxML ontology - representing semi-automatic conversion of the ToxML schema; d) OpenTox ontology- representation of OpenTox framework components: chemical compounds, datasets, types of algorithms, models and validation web services; e) ToxLink-ToxCast assays ontology and f) OpenToxipedia community knowledge resource on toxicology terminology.OpenTox components are made available through standardized REST web services, where every compound, data set, and predictive method has a unique resolvable address (URI), used to retrieve its Resource Description Framework (RDF) representation, or to initiate the associated calculations and generate new RDF-based resources.The services support the integration of toxicity and chemical data from various sources, the generation and validation of computer models for toxic effects, seamless integration of new algorithms and scientifically sound validation routines and provide a flexible framework, which allows building arbitrary number of applications, tailored to solving different problems by end users (e.g. toxicologists). The OpenTox toxicological ontology projects may be accessed via the Open

  5. Foundations of semantic web technologies

    CERN Document Server

    Hitzler, Pascal; Rudolph, Sebastian

    2009-01-01

    The Quest for Semantics Building Models Calculating with Knowledge Exchanging Information Semanic Web Technologies RESOURCE DESCRIPTION LANGUAGE (RDF)Simple Ontologies in RDF and RDF SchemaIntroduction to RDF Syntax for RDF Advanced Features Simple Ontologies in RDF Schema Encoding of Special Data Structures An ExampleRDF Formal Semantics Why Semantics? Model-Theoretic Semantics for RDF(S) Syntactic Reasoning with Deduction Rules The Semantic Limits of RDF(S)WEB ONTOLOGY LANGUAGE (OWL) Ontologies in OWL OWL Syntax and Intuitive Semantics OWL Species The Forthcoming OWL 2 StandardOWL Formal Sem

  6. Geospatial semantic web

    CERN Document Server

    Zhang, Chuanrong; Li, Weidong

    2015-01-01

    This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

  7. Survey on Ontology Mapping

    Science.gov (United States)

    Zhu, Junwu

    To create a sharable semantic space in which the terms from different domain ontology or knowledge system, Ontology mapping become a hot research point in Semantic Web Community. In this paper, motivated factors of ontology mapping research are given firstly, and then 5 dominating theories and methods, such as information accessing technology, machine learning, linguistics, structure graph and similarity, are illustrated according their technology class. Before we analyses the new requirements and takes a long view, the contributions of these theories and methods are summarized in details. At last, this paper suggest to design a group of semantic connector with the ability of migration learning for OWL-2 extended with constrains and the ontology mapping theory of axiom, so as to provide a new methodology for ontology mapping.

  8. The effects of presentation methods and semantic information on multi-ethnicity face recognition

    Directory of Open Access Journals (Sweden)

    Kaarel Rundu

    2012-01-01

    Full Text Available Studies have shown that own-race faces are more accurately recognised than other-race faces. The present study examined the effects of own- and other-race face recognition when different ethnicity targets are presented to the participants together. Also the effect of semantic information on the recognition of different race faces was examined. The participants (N = 234 were presented with photos of own-race and other-race faces. For some participants the faces were presented with stereotypical names and for some not. As hypothesized, own-race faces were better recognised in target-present lineup and more correctly rejected in target-absent lineup than other-race faces. Concerning presentation method, both own-race and other-race faces were more correctly identified in target-present simultaneous than in target-present sequential lineups. No effects of stereotypical names on face recognition were found. The findings suggest that identifying multi-ethnicity perpetrators is a problematic and difficult task.

  9. Semantic Memory Recognition Is Supported by Intrinsic Recollection-Like Processes: "The Butcher on the Bus" Revisited

    Science.gov (United States)

    Waidergoren, Shani; Segalowicz, Judith; Gilboa, Asaf

    2012-01-01

    Dual-process models suggest that recognition memory is independently supported by recollection and familiarity. Current theories attribute recollection solely to hippocampally mediated episodic memory (EM), and familiarity to both episodic and semantic memory (SM) supported by medial temporal lobe cortex (MTLC) and prefrontal cortex. We tested…

  10. Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

    Science.gov (United States)

    Urbain, Jay

    2015-12-01

    We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Universal Dimensions of Meaning Derived from Semantic Relations among Words and Senses: Mereological Completeness vs. Ontological Generality

    Directory of Open Access Journals (Sweden)

    Alexei V. Samsonovich

    2014-07-01

    Full Text Available A key to semantic analysis is a precise and practically useful definition of meaning that is general for all domains of knowledge. We previously introduced the notion of weak semantic map: a metric space allocating concepts along their most general (universal semantic characteristics while at the same time ignoring other, domain-specific aspects of their meanings. Here we address questions of the number, quality, and mutual independence of the weak semantic dimensions. Specifically, we employ semantic relationships not previously used for weak semantic mapping, such as holonymy/meronymy (“is-part/member-of”, and we compare maps constructed from word senses to those constructed from words. We show that the “completeness” dimension derived from the holonym/meronym relation is independent of, and practically orthogonal to, the “abstractness” dimension derived from the hypernym-hyponym (“is-a” relation, while both dimensions are orthogonal to the maps derived from synonymy and antonymy. Interestingly, the choice of using relations among words vs. senses implies a non-trivial trade-off between rich and unambiguous information due to homonymy and polysemy. The practical utility of the new and prior dimensions is illustrated by the automated evaluation of different kinds of documents. Residual analysis of available linguistic resources, such as WordNet, suggests that the number of universal semantic dimensions representable in natural language may be finite. Their complete characterization, as well as the extension of results to non-linguistic materials, remains an open challenge.

  12. Linguistic Context Versus Semantic Competition in Word Recognition by Younger and Older Adults With Cochlear Implants.

    Science.gov (United States)

    Amichetti, Nicole M; Atagi, Eriko; Kong, Ying-Yee; Wingfield, Arthur

    greater degree of interference from other words that might also be activated by the context, with negative effects on ease of word recognition. These results are consistent with an age-related inhibition deficit extending to the domain of semantic constraints on word recognition.

  13. Marine Planning and Service Platform: specific ontology based semantic search engine serving data management and sustainable development

    Science.gov (United States)

    Manzella, Giuseppe M. R.; Bartolini, Andrea; Bustaffa, Franco; D'Angelo, Paolo; De Mattei, Maurizio; Frontini, Francesca; Maltese, Maurizio; Medone, Daniele; Monachini, Monica; Novellino, Antonio; Spada, Andrea

    2016-04-01

    : the whole document gets parsed to extract the words which are more meaningful for the main argument of the document, and applies the extraction in the form of N-grams (mono-grams, bi-grams, tri-grams). • MAPS database - This module is a simple database which contains all the N-grams used by MAPS (physical parameters from SeaDataNet vocabularies) to define our marine "ontology". • Relation identifier - This module performs the most important task of identifying relationships between the N-gram extracted from the text by the parser and the provided oceanographic terminology. It checks N-grams supplied by the Syntactic parser and then matches them with the terms stored in the MAPS database. Found matches are returned back to the parser with flexed form appearing in the source text. • A "relaxed" extractor - This option can be activated when the search engine is launched. It was introduced to give the user a chance to create new N-grams combining existing mono-grams and bi-grams in the database with rich-words found within the source text. The innovation of a semantic engine lies in the fact that the process is not just about the retrieval of already known documents by means of a simple term query but rather the retrieval of a population of documents whose existence was unknown. The system answers by showing a screenshot of results ordered according to the following criteria: • Relevance - of the document with respect to the concept that is searched • Date - of publication of the paper • Source - data provider as defined in the SeaDataNet Common Data Index • Matrix - environmental matrices as defined in the oceanographic field • Geographic area - area specified in the text • Clustering - the process of organizing objects into groups whose members are similar The clustering returns as the output the related documents. For each document the MAPS visualization provides: • Title, author, source/provider of data, web address • Tagging of key terms or

  14. Relative Weighting of Semantic and Syntactic Cues in Native and Non-Native Listeners' Recognition of English Sentences.

    Science.gov (United States)

    Shi, Lu-Feng; Koenig, Laura L

    2016-01-01

    Non-native listeners do not recognize English sentences as effectively as native listeners, especially in noise. It is not entirely clear to what extent such group differences arise from differences in relative weight of semantic versus syntactic cues. This study quantified the use and weighting of these contextual cues via Boothroyd and Nittrouer's j and k factors. The j represents the probability of recognizing sentences with or without context, whereas the k represents the degree to which context improves recognition performance. Four groups of 13 normal-hearing young adult listeners participated. One group consisted of native English monolingual (EMN) listeners, whereas the other three consisted of non-native listeners contrasting in their language dominance and first language: English-dominant Russian-English, Russian-dominant Russian-English, and Spanish-dominant Spanish-English bilinguals. All listeners were presented three sets of four-word sentences: high-predictability sentences included both semantic and syntactic cues, low-predictability sentences included syntactic cues only, and zero-predictability sentences included neither semantic nor syntactic cues. Sentences were presented at 65 dB SPL binaurally in the presence of speech-spectrum noise at +3 dB SNR. Listeners orally repeated each sentence and recognition was calculated for individual words as well as the sentence as a whole. Comparable j values across groups for high-predictability, low-predictability, and zero-predictability sentences suggested that all listeners, native and non-native, utilized contextual cues to recognize English sentences. Analysis of the k factor indicated that non-native listeners took advantage of syntax as effectively as EMN listeners. However, only English-dominant bilinguals utilized semantics to the same extent as EMN listeners; semantics did not provide a significant benefit for the two non-English-dominant groups. When combined, semantics and syntax benefitted EMN

  15. A semantics of love: Brief notes on desire and recognition in Georges Bataille

    Directory of Open Access Journals (Sweden)

    Herivelto Pereira de Souza

    2013-06-01

    , transgressive experiences points to a disruptive effect over the features of subjective arrangement, intersubjectively formed. That is why excitement and fear, pleasure and anguish intertwine in eroticism, and desire becomes the name of a fascinating and frightening ontological excess. It is this very paradoxical character that is decisive for Bataille, for if norms need their transgression in order to exert a subjective inscription, one should not take the passage from desire to recognition as just a progressive process towards a determined form of sociality. Bataille associates a certain Durkheimian heritage with a philosophy of life to account for a libidinal economy of recognition in which desire lies at its very core. This paper proposes a reflection on what is at stake in this conceptual operation, and on the significance of the peculiar enjoyment of norms to a rethinking of the particular aspirations of recognition in love relationships.

  16. Supporting Better Treatments for Meeting Health Consumers' Needs: Extracting Semantics in Social Data for Representing a Consumer Health Ontology

    Science.gov (United States)

    Choi, Yunseon

    2016-01-01

    Introduction: The purpose of this paper is to provide a framework for building a consumer health ontology using social tags. This would assist health users when they are accessing health information and increase the number of documents relevant to their needs. Methods: In order to extract concepts from social tags, this study conducted an…

  17. Realist Ontology and Natural Processes: A Semantic Tool to Analyze the Presentation of the Osmosis Concept in Science Texts

    Science.gov (United States)

    Spinelli Barria, Michele; Morales, Cecilia; Merino, Cristian; Quiroz, Waldo

    2016-01-01

    In this work, we developed an ontological tool, based on the scientific realism of Mario Bunge, for the analysis of the presentation of natural processes in science textbooks. This tool was applied to analyze the presentation of the concept of osmosis in 16 chemistry and biology books at different educational levels. The results showed that more…

  18. The role of semantic and phonological factors in word recognition: an ERP cross-modal priming study of derivational morphology.

    Science.gov (United States)

    Kielar, Aneta; Joanisse, Marc F

    2011-01-01

    Theories of morphological processing differ on the issue of how lexical and grammatical information are stored and accessed. A key point of contention is whether complex forms are decomposed during recognition (e.g., establish+ment), compared to forms that cannot be analyzed into constituent morphemes (e.g., apartment). In the present study, we examined these issues with respect to English derivational morphology by measuring ERP responses during a cross-modal priming lexical decision task. ERP priming effects for semantically and phonologically transparent derived words (government-govern) were compared to those of semantically opaque derived words (apartment-apart) as well as "quasi-regular" items that represent intermediate cases of morphological transparency (dresser-dress). Additional conditions independently manipulated semantic and phonological relatedness in non-derived words (semantics: couch-sofa; phonology: panel-pan). The degree of N400 ERP priming to morphological forms varied depending on the amount of semantic and phonological overlap between word types, rather than respecting a bivariate distinction between derived and opaque forms. Moreover, these effects could not be accounted for by semantic or phonological relatedness alone. The findings support the theory that morphological relatedness is graded rather than absolute, and depend on the joint contribution of form and meaning overlap. Copyright © 2010 Elsevier Ltd. All rights reserved.

  19. Semantic Radicals Contribute More Than Phonetic Radicals to the Recognition of Chinese Phonograms: Behavioral and ERP Evidence in a Factorial Study

    Directory of Open Access Journals (Sweden)

    Xieshun Wang

    2017-12-01

    Full Text Available The Chinese phonograms consist of a semantic radical and a phonetic radical. The two types of radicals have different functional contributions to their host phonogram. The semantic radical typically signifies the meaning of the phonogram, while the phonetic radical usually contains a phonological clue to the phonogram’s pronunciation. However, it is still unclear how they interplay with each other when we attempt to recognize a phonogram because previous studies rarely manipulated the functionality of the two types of radicals in a single design. Using a full factorial design, the present study aimed to probe this issue by directly manipulating the functional validity of the two types of radicals in a lexical decision task with both behavioral and event-related potential (ERP measurements. The results showed that recognition of phonograms which were related to their semantic radicals in meaning took a shorter reaction time, showed a lower error rate, and elicited a smaller P200 and a larger N400 than did recognition of those which had no semantic relation with their semantic radicals. However, the validity of phonetic radicals did not show any main effect or interaction with that of semantic radicals on either behavioral or ERP measurements. These results indicated that semantic radicals played a dominant role in the recognition of phonograms. Transparent semantic radicals, which provide valid semantic cues to phonograms, can facilitate the recognition of phonograms.

  20. Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

    Science.gov (United States)

    Malhotra, Ashutosh; Gündel, Michaela; Rajput, Abdul Mateen; Mevissen, Heinz-Theodor; Saiz, Albert; Pastor, Xavier; Lozano-Rubi, Raimundo; Martinez-Lapiscina, Elena H; Martinez-Lapsicina, Elena H; Zubizarreta, Irati; Mueller, Bernd; Kotelnikova, Ekaterina; Toldo, Luca; Hofmann-Apitius, Martin; Villoslada, Pablo

    2015-01-01

    In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.

  1. Ontology-based approaches for cross-enterprise collaboration: a literature review on semantic business process management

    Science.gov (United States)

    Hoang, Hanh H.; Jung, Jason J.; Tran, Chi P.

    2014-11-01

    Based on an in-depth analysis of the existing approaches in applying semantic technologies to business process management (BPM) research in the perspective of cross-enterprise collaboration or so-called business-to-business integration, we analyse, discuss and compare methodologies, applications and best practices of the surveyed approaches with the proposed criteria. This article identifies various relevant research directions in semantic BPM (SBPM). Founded on the result of our investigation, we summarise the state of art of SBPM. We also address areas and directions for further research activities.

  2. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel; Hoehndorf, Robert

    2018-01-01

    ' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies

  3. Addressing issues in foundational ontology mediation

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available An approach in achieving semantic interoperability among heterogeneous systems is to offer infrastructure to assist with linking and integration using a foundational ontology. Due to the creation of multiple foundational ontologies, this also means...

  4. Lack of semantic priming effects in famous person recognition in Mild Cognitive Impairment.

    Science.gov (United States)

    Brambati, Simona M; Peters, Frédéric; Belleville, Sylvie; Joubert, Sven

    2012-04-01

    Growing evidence indicates that individuals with Mild Cognitive Impairment (MCI) manifest semantic deficits that are often more severe for items that are characterized by a unique semantic and lexical association, such as famous people and famous buildings, than common concepts, such as objects. However, it is still controversial whether the semantic deficits observed in MCI are determined by a degradation of semantic information or by a deficit in intentional access to semantic knowledge. Here we used a semantic priming task in order to assess the integrity of the semantic system without requiring explicit access to this system. This paradigm may provide new insights in clarifying the nature of the semantic deficits in MCI. We assessed the semantic and repetition priming effect in 13 individuals with MCI and 13 age-matched controls who engaged in a familiarity judgment task of famous names. In the semantic priming condition, the prime was the name of a member of the same occupation category as the target (Tom Cruise-Brad Pitt), while in the repetition priming condition the prime was the same name as the target (Charlie Chaplin-Charlie Chaplin). The results showed a defective priming effect in MCI in the semantic but not in the repetition priming condition. Specifically, when compared to controls, MCI patients did not show a facilitation effect in responding to the same occupation prime-target pairs, but they showed an equivalent facilitation effect when the target was the same name as the prime. The present results provide support to the hypothesis that the semantic impairments observed in MCI cannot be uniquely ascribed to a deficit in intentional access to semantic information. Instead, these findings point to the semantic nature of these deficits and, in particular, to a degraded representation of semantic information concerning famous people. Copyright © 2011 Elsevier Srl. All rights reserved.

  5. An Ontology of Quality Initiatives and a Model for Decentralized, Collaborative Quality Management on the (Semantic) World Wide Web

    Science.gov (United States)

    2001-01-01

    This editorial provides a model of how quality initiatives concerned with health information on the World Wide Web may in the future interact with each other. This vision fits into the evolving "Semantic Web" architecture - ie, the prospective that the World Wide Web may evolve from a mess of unstructured, human-readable information sources into a global knowledge base with an additional layer providing richer and more meaningful relationships between resources. One first prerequisite for forming such a "Semantic Web" or "web of trust" among the players active in quality management of health information is that these initiatives make statements about themselves and about each other in a machine-processable language. I present a concrete model on how this collaboration could look, and provide some recommendations on what the role of the World Health Organization (WHO) and other policy makers in this framework could be. PMID:11772549

  6. Toxicology ontology perspectives.

    Science.gov (United States)

    Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

    2012-01-01

    The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

  7. Didactical Ontologies

    Directory of Open Access Journals (Sweden)

    Steffen Mencke, Reiner Dumke

    2008-03-01

    Full Text Available Ontologies are a fundamental concept of theSemantic Web envisioned by Tim Berners-Lee [1]. Togetherwith explicit representation of the semantics of data formachine-accessibility such domain theories are the basis forintelligent next generation applications for the web andother areas of interest [2]. Their application for specialaspects within the domain of e-learning is often proposed tosupport the increasing complexity ([3], [4], [5], [6]. So theycan provide a better support for course generation orlearning scenario description [7]. By the modeling ofdidactics-related expertise and their provision for thecreators of courses many improvements like reuse, rapiddevelopment and of course increased learning performancebecome possible due to the separation from other aspects ofe-learning platforms as already proposed in [8].

  8. Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

    Science.gov (United States)

    Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

    2016-01-01

    Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method

  9. ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.

    Science.gov (United States)

    Malhotra, Ashutosh; Younesi, Erfan; Gündel, Michaela; Müller, Bernd; Heneka, Michael T; Hofmann-Apitius, Martin

    2014-03-01

    Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain. Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios. Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  10. The facilitation effect of associative and semantic relatedness in word recognition

    Directory of Open Access Journals (Sweden)

    Jakić Milena

    2011-01-01

    Full Text Available In this study we addressed three issues concerning semantic and associative relatedness between two words and how they prime each other. The first issue is whether there is a priming effect of semantic relatedness over and above the effect of associative relatedness. The second issue is how difference in semantic overlap between two words affects priming. In order to specify the semantic overlap we introduce five relation types that differ in number of common semantic components. Three relation types (synonyms, antonyms and hyponyms represent semantic relatedness while two relation types represent associative relatedness, with negligible or no semantic relatedness. Finally, the third issue addressed in this study is whether there is a symmetric priming effect if we swap the position of prime and target, i.e. whether the direction of relatedness between two words affects priming. In two lexical decision experiments we presented five types of word pairs. In both experiments we obtained stronger facilitation for pairs that were both semantically and associatively related. Closer inspection showed that larger semantic overlap between words is paralleled by greater facilitation effect. The effects did not change when prime and target swap their position, indicating that the observed facilitation effects are symmetrical. This outcome complies with predictions of distributed models of memory.

  11. Towards an Integrated Visualization Of Semantically Enriched 3D City Models: An Ontology of 3D Visualization Techniques

    OpenAIRE

    Métral, Claudine; Ghoula, Nizar; Falquet, Gilles

    2012-01-01

    3D city models - which represent in 3 dimensions the geometric elements of a city - are increasingly used for an intended wide range of applications. Such uses are made possible by using semantically enriched 3D city models and by presenting such enriched 3D city models in a way that allows decision-making processes to be carried out from the best choices among sets of objectives, and across issues and scales. In order to help in such a decision-making process we have defined a framework to f...

  12. Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

    Science.gov (United States)

    Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

    The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain ontologies can be used to define a common vocabulary for sharing and reuse of knowledge about some domain. Foundational ontologies can be used for evaluating and re-designing domain ontologies, giving to these real-world semantics. This paper presents an evaluating of a Software Enterprise Ontology that was reengineered using the Unified Foundation Ontology (UFO) as basis.

  13. The Electronic Notebook Ontology

    OpenAIRE

    Chalk, Stuart

    2016-01-01

    Science is rapidly being brought into the electronic realm and electronic laboratory notebooks (ELN) are a big part of this activity. The representation of the scientific process in the context of an ELN is an important component to making the data recorded in ELNs semantically integrated. This presentation will outline initial developments of an Electronic Notebook Ontology (ENO) that will help tie together the ExptML ontology, HCLS Community Profile data descriptions, and the VIVO-ISF ontol...

  14. Learning expressive ontologies

    CERN Document Server

    Völker, J

    2009-01-01

    This publication advances the state-of-the-art in ontology learning by presenting a set of novel approaches to the semi-automatic acquisition, refinement and evaluation of logically complex axiomatizations. It has been motivated by the fact that the realization of the semantic web envisioned by Tim Berners-Lee is still hampered by the lack of ontological resources, while at the same time more and more applications of semantic technologies emerge from fast-growing areas such as e-business or life sciences. Such knowledge-intensive applications, requiring large scale reasoning over complex domai

  15. Perspectives on ontology learning

    CERN Document Server

    Lehmann, J

    2014-01-01

    Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c

  16. Towards Agile Ontology Maintenance

    Science.gov (United States)

    Luczak-Rösch, Markus

    Ontologies are an appropriate means to represent knowledge on the Web. Research on ontology engineering reached practices for an integrative lifecycle support. However, a broader success of ontologies in Web-based information systems remains unreached while the more lightweight semantic approaches are rather successful. We assume, paired with the emerging trend of services and microservices on the Web, new dynamic scenarios gain momentum in which a shared knowledge base is made available to several dynamically changing services with disparate requirements. Our work envisions a step towards such a dynamic scenario in which an ontology adapts to the requirements of the accessing services and applications as well as the user's needs in an agile way and reduces the experts' involvement in ontology maintenance processes.

  17. The interaction of lexical semantics and cohort competition in spoken word recognition: an fMRI study.

    Science.gov (United States)

    Zhuang, Jie; Randall, Billi; Stamatakis, Emmanuel A; Marslen-Wilson, William D; Tyler, Lorraine K

    2011-12-01

    Spoken word recognition involves the activation of multiple word candidates on the basis of the initial speech input--the "cohort"--and selection among these competitors. Selection may be driven primarily by bottom-up acoustic-phonetic inputs or it may be modulated by other aspects of lexical representation, such as a word's meaning [Marslen-Wilson, W. D. Functional parallelism in spoken word-recognition. Cognition, 25, 71-102, 1987]. We examined these potential interactions in an fMRI study by presenting participants with words and pseudowords for lexical decision. In a factorial design, we manipulated (a) cohort competition (high/low competitive cohorts which vary the number of competing word candidates) and (b) the word's semantic properties (high/low imageability). A previous behavioral study [Tyler, L. K., Voice, J. K., & Moss, H. E. The interaction of meaning and sound in spoken word recognition. Psychonomic Bulletin & Review, 7, 320-326, 2000] showed that imageability facilitated word recognition but only for words in high competition cohorts. Here we found greater activity in the left inferior frontal gyrus (BA 45, 47) and the right inferior frontal gyrus (BA 47) with increased cohort competition, an imageability effect in the left posterior middle temporal gyrus/angular gyrus (BA 39), and a significant interaction between imageability and cohort competition in the left posterior superior temporal gyrus/middle temporal gyrus (BA 21, 22). In words with high competition cohorts, high imageability words generated stronger activity than low imageability words, indicating a facilitatory role of imageability in a highly competitive cohort context. For words in low competition cohorts, there was no effect of imageability. These results support the behavioral data in showing that selection processes do not rely solely on bottom-up acoustic-phonetic cues but rather that the semantic properties of candidate words facilitate discrimination between competitors.

  18. SELECTION OF ONTOLOGY FOR WEB SERVICE DESCRIPTION LANGUAGE TO ONTOLOGY WEB LANGUAGE CONVERSION

    OpenAIRE

    J. Mannar Mannan; M. Sundarambal; S. Raghul

    2014-01-01

    Semantic web is to extend the current human readable web to encoding some of the semantic of resources in a machine processing form. As a Semantic web component, Semantic Web Services (SWS) uses a mark-up that makes the data into detailed and sophisticated machine readable way. One such language is Ontology Web Language (OWL). Existing conventional web service annotation can be changed to semantic web service by mapping Web Service Description Language (WSDL) with the semantic annotation of O...

  19. Ontological Surprises

    DEFF Research Database (Denmark)

    Leahu, Lucian

    2016-01-01

    a hybrid approach where machine learning algorithms are used to identify objects as well as connections between them; finally, it argues for remaining open to ontological surprises in machine learning as they may enable the crafting of different relations with and through technologies.......This paper investigates how we might rethink design as the technological crafting of human-machine relations in the context of a machine learning technique called neural networks. It analyzes Google’s Inceptionism project, which uses neural networks for image recognition. The surprising output...

  20. Ontology for cell-based geographic information

    Science.gov (United States)

    Zheng, Bin; Huang, Lina; Lu, Xinhai

    2009-10-01

    Inter-operability is a key notion in geographic information science (GIS) for the sharing of geographic information (GI). That requires a seamless translation among different information sources. Ontology is enrolled in GI discovery to settle the semantic conflicts for its natural language appearance and logical hierarchy structure, which are considered to be able to provide better context for both human understanding and machine cognition in describing the location and relationships in the geographic world. However, for the current, most studies on field ontology are deduced from philosophical theme and not applicable for the raster expression in GIS-which is a kind of field-like phenomenon but does not physically coincide to the general concept of philosophical field (mostly comes from the physics concepts). That's why we specifically discuss the cell-based GI ontology in this paper. The discussion starts at the investigation of the physical characteristics of cell-based raster GI. Then, a unified cell-based GI ontology framework for the recognition of the raster objects is introduced, from which a conceptual interface for the connection of the human epistemology and the computer world so called "endurant-occurrant window" is developed for the better raster GI discovery and sharing.

  1. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  2. Inferring ontology graph structures using OWL reasoning.

    Science.gov (United States)

    Rodríguez-García, Miguel Ángel; Hoehndorf, Robert

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  3. Semantic Web Services with Web Ontology Language (OWL-S) - Specification of Agent-Services for DARPA Agent Markup Language (DAML)

    National Research Council Canada - National Science Library

    Sycara, Katia P

    2006-01-01

    CMU did research and development on semantic web services using OWL-S, the semantic web service language under the Defense Advanced Research Projects Agency- DARPA Agent Markup Language (DARPA-DAML) program...

  4. Gated Word Recognition by Postlingually Deafened Adults with Cochlear Implants: Influence of Semantic Context

    Science.gov (United States)

    Patro, Chhayakanta; Mendel, Lisa Lucks

    2018-01-01

    Purpose: The main goal of this study was to investigate the minimum amount of sensory information required to recognize spoken words (isolation points [IPs]) in listeners with cochlear implants (CIs) and investigate facilitative effects of semantic contexts on the IPs. Method: Listeners with CIs as well as those with normal hearing (NH)…

  5. Stereotype Priming in Face Recognition: Interactions between Semantic and Visual Information in Face Encoding

    Science.gov (United States)

    Hills, Peter J.; Lewis, Michael B.; Honey, R. C.

    2008-01-01

    The accuracy with which previously unfamiliar faces are recognised is increased by the presentation of a stereotype-congruent occupation label [Klatzky, R. L., Martin, G. L., & Kane, R. A. (1982a). "Semantic interpretation effects on memory for faces." "Memory & Cognition," 10, 195-206; Klatzky, R. L., Martin, G. L., & Kane, R. A. (1982b).…

  6. Two obvious intuitions : Ontology-mapping needs background knowledge and approximation

    NARCIS (Netherlands)

    Van Harmelen, Frank

    2007-01-01

    Ontology mapping (or: ontology alignment, or integration) is one of the most active areas the Semantic Web area. An increasing amount of ontologies are becoming available in recent years, and if the Semantic Web is to be taken seriously, the problem of ontology mapping must be solved. Numerous

  7. Ontology based decision system for breast cancer diagnosis

    Science.gov (United States)

    Trabelsi Ben Ameur, Soumaya; Cloppet, Florence; Wendling, Laurent; Sellami, Dorra

    2018-04-01

    In this paper, we focus on analysis and diagnosis of breast masses inspired by expert concepts and rules. Accordingly, a Bag of Words is built based on the ontology of breast cancer diagnosis, accurately described in the Breast Imaging Reporting and Data System. To fill the gap between low level knowledge and expert concepts, a semantic annotation is developed using a machine learning tool. Then, breast masses are classified into benign or malignant according to expert rules implicitly modeled with a set of classifiers (KNN, ANN, SVM and Decision Tree). This semantic context of analysis offers a frame where we can include external factors and other meta-knowledge such as patient risk factors as well as exploiting more than one modality. Based on MRI and DECEDM modalities, our developed system leads a recognition rate of 99.7% with Decision Tree where an improvement of 24.7 % is obtained owing to semantic analysis.

  8. Rapid interactions between lexical semantic and word form analysis during word recognition in context: evidence from ERPs.

    Science.gov (United States)

    Kim, Albert; Lai, Vicky

    2012-05-01

    We used ERPs to investigate the time course of interactions between lexical semantic and sublexical visual word form processing during word recognition. Participants read sentence-embedded pseudowords that orthographically resembled a contextually supported real word (e.g., "She measured the flour so she could bake a ceke…") or did not (e.g., "She measured the flour so she could bake a tont…") along with nonword consonant strings (e.g., "She measured the flour so she could bake a srdt…"). Pseudowords that resembled a contextually supported real word ("ceke") elicited an enhanced positivity at 130 msec (P130), relative to real words (e.g., "She measured the flour so she could bake a cake…"). Pseudowords that did not resemble a plausible real word ("tont") enhanced the N170 component, as did nonword consonant strings ("srdt"). The effect pattern shows that the visual word recognition system is, perhaps, counterintuitively, more rapidly sensitive to minor than to flagrant deviations from contextually predicted inputs. The findings are consistent with rapid interactions between lexical and sublexical representations during word recognition, in which rapid lexical access of a contextually supported word (CAKE) provides top-down excitation of form features ("cake"), highlighting the anomaly of an unexpected word "ceke."

  9. Semantic heterogeneity: comparing new semantic web approaches with those of digital libraries

    OpenAIRE

    Krause, Jürgen

    2008-01-01

    To demonstrate that newer developments in the semantic web community, particularly those based on ontologies (simple knowledge organization system and others) mitigate common arguments from the digital library (DL) community against participation in the Semantic web. The approach is a semantic web discussion focusing on the weak structure of the Web and the lack of consideration given to the semantic content during indexing. The points criticised by the semantic web and ontology approaches ar...

  10. Surreptitious, Evolving and Participative Ontology Development: An End-User Oriented Ontology Development Methodology

    Science.gov (United States)

    Bachore, Zelalem

    2012-01-01

    Ontology not only is considered to be the backbone of the semantic web but also plays a significant role in distributed and heterogeneous information systems. However, ontology still faces limited application and adoption to date. One of the major problems is that prevailing engineering-oriented methodologies for building ontologies do not…

  11. Ontology-aided Data Fusion (Invited)

    Science.gov (United States)

    Raskin, R.

    2009-12-01

    An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

  12. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....

  13. Semantic Segmentation of Real-time Sensor Data Stream for Complex Activity Recognition

    OpenAIRE

    Triboan, Darpan; Chen, Liming; Chen, Feng; Wang, Zumin

    2016-01-01

    Department of Information Engineering, Dalian University, China The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Data segmentation plays a critical role in performing human activity recognition (HAR) in the ambient assistant living (AAL) systems. It is particularly important for complex activity recognition when the events occur in short bursts with attributes of multiple sub-tasks. Althou...

  14. Alignment of the UMLS semantic network with BioTop: methodology and assessment.

    Science.gov (United States)

    Schulz, Stefan; Beisswanger, Elena; van den Hoek, László; Bodenreider, Olivier; van Mulligen, Erik M

    2009-06-15

    For many years, the Unified Medical Language System (UMLS) semantic network (SN) has been used as an upper-level semantic framework for the categorization of terms from terminological resources in biomedicine. BioTop has recently been developed as an upper-level ontology for the biomedical domain. In contrast to the SN, it is founded upon strict ontological principles, using OWL DL as a formal representation language, which has become standard in the semantic Web. In order to make logic-based reasoning available for the resources annotated or categorized with the SN, a mapping ontology was developed aligning the SN with BioTop. The theoretical foundations and the practical realization of the alignment are being described, with a focus on the design decisions taken, the problems encountered and the adaptations of BioTop that became necessary. For evaluation purposes, UMLS concept pairs obtained from MEDLINE abstracts by a named entity recognition system were tested for possible semantic relationships. Furthermore, all semantic-type combinations that occur in the UMLS Metathesaurus were checked for satisfiability. The effort-intensive alignment process required major design changes and enhancements of BioTop and brought up several design errors that could be fixed. A comparison between a human curator and the ontology yielded only a low agreement. Ontology reasoning was also used to successfully identify 133 inconsistent semantic-type combinations. BioTop, the OWL DL representation of the UMLS SN, and the mapping ontology are available at http://www.purl.org/biotop/.

  15. An ontological case base engineering methodology for diabetes management.

    Science.gov (United States)

    El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

    2014-08-01

    Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

  16. Toward the Use of an Upper Ontology for U.S. Government and U.S. Military Domains: An Evaluation

    National Research Council Canada - National Science Library

    Semy, Salim K; Pulvermacher, Mary K; Obrst, Leo J

    2004-01-01

    ...) of data and ultimately of applications. Key to the vision of a Semantic Web is the ability to capture data and application semantics in ontologies and map these ontologies together via related concepts...

  17. Semantic and phonetic enhancements for speech-in-noise recognition by native and non-native listeners.

    Science.gov (United States)

    Bradlow, Ann R; Alexander, Jennifer A

    2007-04-01

    Previous research has shown that speech recognition differences between native and proficient non-native listeners emerge under suboptimal conditions. Current evidence has suggested that the key deficit that underlies this disproportionate effect of unfavorable listening conditions for non-native listeners is their less effective use of compensatory information at higher levels of processing to recover from information loss at the phoneme identification level. The present study investigated whether this non-native disadvantage could be overcome if enhancements at various levels of processing were presented in combination. Native and non-native listeners were presented with English sentences in which the final word varied in predictability and which were produced in either plain or clear speech. Results showed that, relative to the low-predictability-plain-speech baseline condition, non-native listener final word recognition improved only when both semantic and acoustic enhancements were available (high-predictability-clear-speech). In contrast, the native listeners benefited from each source of enhancement separately and in combination. These results suggests that native and non-native listeners apply similar strategies for speech-in-noise perception: The crucial difference is in the signal clarity required for contextual information to be effective, rather than in an inability of non-native listeners to take advantage of this contextual information per se.

  18. A Formal Theory for Modular ERDF Ontologies

    Science.gov (United States)

    Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas

    The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

  19. Ontology modeling for generation of clinical pathways

    Directory of Open Access Journals (Sweden)

    Jasmine Tehrani

    2012-12-01

    Full Text Available Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the

  20. Interspecific semantic alarm call recognition in the solitary Sahamalaza sportive lemur, Lepilemur sahamalazensis.

    Directory of Open Access Journals (Sweden)

    Melanie Seiler

    Full Text Available As alarm calls indicate the presence of predators, the correct interpretation of alarm calls, including those of other species, is essential for predator avoidance. Conversely, communication calls of other species might indicate the perceived absence of a predator and hence allow a reduction in vigilance. This "eavesdropping" was demonstrated in birds and mammals, including lemur species. Interspecific communication between taxonomic groups has so far been reported in some reptiles and mammals, including three primate species. So far, neither semantic nor interspecific communication has been tested in a solitary and nocturnal lemur species. The aim of this study was to investigate if the nocturnal and solitary Sahamalaza sportive lemur, Lepilemur sahamalazensis, is able to access semantic information of sympatric species. During the day, this species faces the risk of falling prey to aerial and terrestrial predators and therefore shows high levels of vigilance. We presented alarm calls of the crested coua, the Madagascar magpie-robin and aerial, terrestrial and agitation alarm calls of the blue-eyed black lemur to 19 individual Sahamalaza sportive lemurs resting in tree holes. Songs of both bird species' and contact calls of the blue-eyed black lemur were used as a control. After alarm calls of crested coua, Madagascar magpie-robin and aerial alarm of the blue-eyed black lemur, the lemurs scanned up and their vigilance increased significantly. After presentation of terrestrial alarm and agitation calls of the blue-eyed black lemur, the animals did not show significant changes in scanning direction or in the duration of vigilance. Sportive lemur vigilance decreased after playbacks of songs of the bird species and contact calls of blue-eyed black lemurs. Our results indicate that the Sahamalaza sportive lemur is capable of using information on predator presence as well as predator type of different sympatric species, using their referential

  1. Application of the Financial Industry Business Ontology (FIBO) for development of a financial organization ontology

    Science.gov (United States)

    Petrova, G. G.; Tuzovsky, A. F.; Aksenova, N. V.

    2017-01-01

    The article considers an approach to a formalized description and meaning harmonization for financial terms and means of semantic modeling. Ontologies for the semantic models are described with the help of special languages developed for the Semantic Web. Results of FIBO application to solution of different tasks in the Russian financial sector are given.

  2. Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

    Science.gov (United States)

    Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

    2010-01-01

    Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

  3. Syntactic and semantic errors in radiology reports associated with speech recognition software.

    Science.gov (United States)

    Ringler, Michael D; Goss, Brian C; Bartholmai, Brian J

    2017-03-01

    Speech recognition software can increase the frequency of errors in radiology reports, which may affect patient care. We retrieved 213,977 speech recognition software-generated reports from 147 different radiologists and proofread them for errors. Errors were classified as "material" if they were believed to alter interpretation of the report. "Immaterial" errors were subclassified as intrusion/omission or spelling errors. The proportion of errors and error type were compared among individual radiologists, imaging subspecialty, and time periods. In all, 20,759 reports (9.7%) contained errors, of which 3992 (1.9%) were material errors. Among immaterial errors, spelling errors were more common than intrusion/omission errors ( p reports, reports reinterpreting results of outside examinations, and procedural studies (all p < .001). Error rate decreased over time ( p < .001), which suggests that a quality control program with regular feedback may reduce errors.

  4. A Bayesian Network Approach to Ontology Mapping

    National Research Council Canada - National Science Library

    Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun

    2005-01-01

    This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web...

  5. Multimedia ontology representation and applications

    CERN Document Server

    Chaudhury, Santanu; Ghosh, Hiranmay

    2015-01-01

    The result of more than 15 years of collective research, Multimedia Ontology: Representation and Applications provides a theoretical foundation for understanding the nature of media data and the principles involved in its interpretation. The book presents a unified approach to recent advances in multimedia and explains how a multimedia ontology can fill the semantic gap between concepts and the media world. It relays real-life examples of implementations in different domains to illustrate how this gap can be filled.The book contains information that helps with building semantic, content-based

  6. Ontology: ambiguity and accuracy

    Directory of Open Access Journals (Sweden)

    Marcelo Schiessl

    2012-08-01

    Full Text Available Ambiguity is a major obstacle to information retrieval. It is source of several researches in Information Science. Ontologies have been studied in order to solve problems related to ambiguities. Paradoxically, “ontology” term is also ambiguous and it is understood according to the use by the community. Philosophy and Computer Science seems to have the most accentuated difference related to the term sense. The former holds undisputed tradition and authority. The latter, in despite of being quite recent, holds an informal sense, but pragmatic. Information Science acts ranging from philosophical to computational approaches so as to get organized collections based on balance between users’ necessities and available information. The semantic web requires informational cycle automation and demands studies related to ontologies. Consequently, revisiting relevant approaches for the study of ontologies plays a relevant role as a way to provide useful ideas to researchers maintaining philosophical rigor, and convenience provided by computers.

  7. Ontological engineering versus metaphysics

    Science.gov (United States)

    Tataj, Emanuel; Tomanek, Roman; Mulawka, Jan

    2011-10-01

    It has been recognized that ontologies are a semantic version of world wide web and can be found in knowledge-based systems. A recent time survey of this field also suggest that practical artificial intelligence systems may be motivated by this research. Especially strong artificial intelligence as well as concept of homo computer can also benefit from their use. The main objective of this contribution is to present and review already created ontologies and identify the main advantages which derive such approach for knowledge management systems. We would like to present what ontological engineering borrows from metaphysics and what a feedback it can provide to natural language processing, simulations and modelling. The potential topics of further development from philosophical point of view is also underlined.

  8. Semantically Interoperable XML Data.

    Science.gov (United States)

    Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

    2013-09-01

    XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups.

  9. Semantically Interoperable XML Data

    Science.gov (United States)

    Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

    2013-01-01

    XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

  10. The ontology-based answers (OBA) service: a connector for embedded usage of ontologies in applications.

    Science.gov (United States)

    Dönitz, Jürgen; Wingender, Edgar

    2012-01-01

    The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and "partOf" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba.

  11. Opening the Semantic Space in the Service of Collective Intelligence - DOI: 10.3395/reciis.v1i1.43en

    Directory of Open Access Journals (Sweden)

    Pierre Lévy

    2007-06-01

    Full Text Available As the human recorded memory is progressively digitized and posted on line, the need for a common semantic coordinate system independant from natural languages and ontologies is growing. A future universal semantic addressing system, able to index all digital documents, should meet three basic requirements. First, each distinct concept should have a unique address. Second, the semantic coordinate system should be open to any concept and relations between concepts (ontologies, whatever the cultural environments where these concepts are created and transformed, without neither privileges nor exclusions. Third, it should support a group of mathematically defined (automatable operations on semantic addresses, namely : rotations, symmetries and translations in the « semantic space » ; semantic compression and decompression ; set-theory operations like union, intersection and symmetric differences ; ranking on semantic criteria ; semantic pattern recognition ; semantic distances measurement ; logical inferences, etc. Developped by an international research network led by the Canada Research Chair in Collective Intelligence at the University of Ottawa, the Information Economy MetaLanguage (IEML, allows the construction of a semantic coordinate system meeting these three constraints. Website, including the IEML dictionary, since may 2006 : www.ieml.org. In Brasil, BIREME (www.bireme.br is member of the IEML initiative.

  12. An ontology roadmap for crowdsourcing innovation intermediaries

    OpenAIRE

    Silva, Cândida; Ramos, Isabel

    2014-01-01

    Ontologies have proliferated in the last years, essentially justified by the need of achieving a consensus in the multiple representations of reality inside computers, and therefore the accomplishment of interoperability between machines and systems. Ontologies provide an explicit conceptualization that describes the semantics of the data. Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solv...

  13. Quantum ontologies

    International Nuclear Information System (INIS)

    Stapp, H.P.

    1988-12-01

    Quantum ontologies are conceptions of the constitution of the universe that are compatible with quantum theory. The ontological orientation is contrasted to the pragmatic orientation of science, and reasons are given for considering quantum ontologies both within science, and in broader contexts. The principal quantum ontologies are described and evaluated. Invited paper at conference: Bell's Theorem, Quantum Theory, and Conceptions of the Universe, George Mason University, October 20-21, 1988. 16 refs

  14. Versioning System for Distributed Ontology Development

    Science.gov (United States)

    2016-03-15

    Framework for Grid Computing and Semantic Web Services,” Trust Management, Springer Berlin Heidelberg (2004), pp. 16−26. [TIME] W3C, “Time Ontology in...Distributed Ontology Development S.K. Damodaran 15 March 2016 This material is based on work supported by the Assistant Secretary of Defense for...Distributed Ontology Development S.K. Damodaran Formerly Group 59 15 March 2016 Massachusetts Institute of Technology Lincoln Laboratory

  15. Web ontology and semantics for governance of scientific research and technological development in inputs for public health - DOI: 10.3395/reciis.v1i2.89en

    Directory of Open Access Journals (Sweden)

    Laura Cristina Simões Viana

    2007-12-01

    Full Text Available The increasing adoption of information and communication technology (ICT in public administration has changed the way governments make the purchases of products and service procurement, activities that are essential for the rendering of services in quantities and quality appropriate to meet the needs of the population. The present project suggests the use of a type of ICT aiming at good governance of scientific research and technological development in inputs for health at the Fundação Oswaldo Cruz: Web semantics and ontologies. From a theoretical point of view, this project is in tune with one of the emerging approaches for the understanding and outlining of current policies for research and technological development in health - an innovation systems approach. Despite the economic advantages of the adoption of electronic methods in governmental purchasing policy, it is necessary to keep in mind that it is a long term change process, since many administrative stages are being transferred to the electronic environment, requiring a new work flow design, as well as integration of electronic purchasing and management and administration systems such as, for instance, orders, purchase orders, logistics, finance and accounting. We propose the sharing of ontologies so as to allow interoperability between systems used in the purchasing process as well as in other key institutional management and administration systems.

  16. Semantically Enhanced Recommender Systems

    Science.gov (United States)

    Ruiz-Montiel, Manuela; Aldana-Montes, José F.

    Recommender Systems have become a significant area in the context of web personalization, given the large amount of available data. Ontologies can be widely taken advantage of in recommender systems, since they provide a means of classifying and discovering of new information about the items to recommend, about user profiles and even about their context. We have developed a semantically enhanced recommender system based on this kind of ontologies. In this paper we present a description of the proposed system.

  17. Towards semantic software engineering enviroments

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Natali, A.; Bertollo, G.; Ruy, F.; Mian, P.; Tortora, G.; Chang, S.K.

    2002-01-01

    Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based

  18. a framework for semantic driven electronic examination system

    African Journals Online (AJOL)

    HOD

    The framework is implemented using Java programming language ... Ontolog have been suggested as a cornerstone to solve ... is the background of study and problem statement, ... requires concept of ontology or semantic knowledge.

  19. Querying archetype-based EHRs by search ontology-based XPath engineering.

    Science.gov (United States)

    Kropf, Stefan; Uciteli, Alexandr; Schierle, Katrin; Krücken, Peter; Denecke, Kerstin; Herre, Heinrich

    2018-05-11

    Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that lead to false positive results, the precision can be increased by constraining the search to certain parts of documents. A search ontology-based specification of queries on XML documents defines search concepts and relates them to parts in the XML document structure. Such query specification method is practically introduced and evaluated by applying concrete research questions formulated in natural language on a data collection for information retrieval purposes. The search is performed by search ontology-based XPath engineering that reuses ontologies and XML-related W3C standards. The key result is that the specification of research questions can be supported by the usage of search ontology-based XPath engineering. A deeper recognition of entities and a semantic understanding of the content is necessary for a further improvement of precision and recall. Key limitation is that the application of the introduced process requires skills in ontology and software development. In future, the time consuming ontology development could be overcome by implementing a new clinical role: the clinical ontologist. The introduced Search Ontology XML extension connects Search Terms to certain parts in XML documents and enables an ontology-based definition of queries. Search ontology-based XPath engineering can support research question answering by the specification of complex XPath expressions without deep syntax knowledge about XPaths.

  20. The Ontology for Biomedical Investigations.

    Science.gov (United States)

    Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

    2016-01-01

    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

  1. A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

    Directory of Open Access Journals (Sweden)

    Chao Wang

    2017-12-01

    Full Text Available Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

  2. The processing of semantic relatedness in the brain: Evidence from associative and categorical false recognition effects following transcranial direct current stimulation of the left anterior temporal lobe.

    Science.gov (United States)

    Díez, Emiliano; Gómez-Ariza, Carlos J; Díez-Álamo, Antonio M; Alonso, María A; Fernandez, Angel

    2017-08-01

    A dominant view of the role of the anterior temporal lobe (ATL) in semantic memory is that it serves as an integration hub, specialized in the processing of semantic relatedness by way of mechanisms that bind together information from different brain areas to form coherent amodal representations of concepts. Two recent experiments, using brain stimulation techniques along with the Deese-Roediger-McDermott (DRM) paradigm, have found a consistent false memory reduction effect following stimulation of the ATL, pointing to the importance of the ATL in semantic/conceptual processing. To more precisely identify the specific process being involved, we conducted a DRM experiment in which transcranial direct current stimulation (anode/cathode/sham) was applied over the participants' left ATL during the study of lists of words that were associatively related to their non-presented critical words (e.g., rotten, worm, red, tree, liqueur, unripe, cake, food, eden, peel, for the critical item apple) or categorically related (e.g., pear, banana, peach, orange, cantaloupe, watermelon, strawberry, cherry, kiwi, plum, for the same critical item apple). The results showed that correct recognition was not affected by stimulation. However, an interaction between stimulation condition and type of relation for false memories was found, explained by a significant false recognition reduction effect in the anodal condition for associative lists that was not observed for categorical lists. Results are congruent with previous findings and, more importantly, they help to clarify the nature and locus of false memory reduction effects, suggesting a differential role of the left ATL, and providing critical evidence for understanding the creation of semantic relatedness-based memory illusions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Model Driven Engineering with Ontology Technologies

    Science.gov (United States)

    Staab, Steffen; Walter, Tobias; Gröner, Gerd; Parreiras, Fernando Silva

    Ontologies constitute formal models of some aspect of the world that may be used for drawing interesting logical conclusions even for large models. Software models capture relevant characteristics of a software artifact to be developed, yet, most often these software models have limited formal semantics, or the underlying (often graphical) software language varies from case to case in a way that makes it hard if not impossible to fix its semantics. In this contribution, we survey the use of ontology technologies for software modeling in order to carry over advantages from ontology technologies to the software modeling domain. It will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers.

  4. A collaborative recommendation framework for ontology evaluation and reuse

    OpenAIRE

    Cantador, Iván; Fernández Sánchez, Miriam; Castells, Pablo

    2006-01-01

    This is an electronic version of the paper presented at the International Workshop on Recommender Systems, held in Riva del Garda on 2006 Ontology evaluation can be defined as assessing the quality and the adequacy of an ontology for being used in a spe-cific context, for a specific goal. Although ontology reuse is being extensively addressed by the Semantic Web community, the lack of appropriate support tools and automatic techniques for the evaluation of certain ontology features are oft...

  5. Ontology and medical diagnosis.

    Science.gov (United States)

    Bertaud-Gounot, Valérie; Duvauferrier, Régis; Burgun, Anita

    2012-03-01

    Ontology and associated generic tools are appropriate for knowledge modeling and reasoning, but most of the time, disease definitions in existing description logic (DL) ontology are not sufficient to classify patient's characteristics under a particular disease because they do not formalize operational definitions of diseases (association of signs and symptoms=diagnostic criteria). The main objective of this study is to propose an ontological representation which takes into account the diagnostic criteria on which specific patient conditions may be classified under a specific disease. This method needs as a prerequisite a clear list of necessary and sufficient diagnostic criteria as defined for lots of diseases by learned societies. It does not include probability/uncertainty which Web Ontology Language (OWL 2.0) cannot handle. We illustrate it with spondyloarthritis (SpA). Ontology has been designed in Protégé 4.1 OWL-DL2.0. Several kinds of criteria were formalized: (1) mandatory criteria, (2) picking two criteria among several diagnostic criteria, (3) numeric criteria. Thirty real patient cases were successfully classified with the reasoner. This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases. Representing diagnostic criteria as descriptive knowledge (instead of rules in Semantic Web Rule Language or Prolog) allows us to take advantage of tools already available for OWL. While we focused on Assessment of SpondyloArthritis international Society SpA criteria, we believe that many of the representation issues addressed here are relevant to using OWL-DL for operational definition of other diseases in ontology.

  6. Semantic Web Technologies for the Adaptive Web

    DEFF Research Database (Denmark)

    Dolog, Peter; Nejdl, Wolfgang

    2007-01-01

    Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web...... provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional...... means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components...

  7. Leave-two-out stability of ontology learning algorithm

    International Nuclear Information System (INIS)

    Wu, Jianzhang; Yu, Xiao; Zhu, Linli; Gao, Wei

    2016-01-01

    Ontology is a semantic analysis and calculation model, which has been applied to many subjects. Ontology similarity calculation and ontology mapping are employed as machine learning approaches. The purpose of this paper is to study the leave-two-out stability of ontology learning algorithm. Several leave-two-out stabilities are defined in ontology learning setting and the relationship among these stabilities are presented. Furthermore, the results manifested reveal that leave-two-out stability is a sufficient and necessary condition for ontology learning algorithm.

  8. Semantic web for integrated network analysis in biomedicine.

    Science.gov (United States)

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  9. ER2OWL: Generating OWL Ontology from ER Diagram

    Science.gov (United States)

    Fahad, Muhammad

    Ontology is the fundamental part of Semantic Web. The goal of W3C is to bring the web into (its full potential) a semantic web with reusing previous systems and artifacts. Most legacy systems have been documented in structural analysis and structured design (SASD), especially in simple or Extended ER Diagram (ERD). Such systems need up-gradation to become the part of semantic web. In this paper, we present ERD to OWL-DL ontology transformation rules at concrete level. These rules facilitate an easy and understandable transformation from ERD to OWL. The set of rules for transformation is tested on a structured analysis and design example. The framework provides OWL ontology for semantic web fundamental. This framework helps software engineers in upgrading the structured analysis and design artifact ERD, to components of semantic web. Moreover our transformation tool, ER2OWL, reduces the cost and time for building OWL ontologies with the reuse of existing entity relationship models.

  10. Semantic Observation Integration

    Directory of Open Access Journals (Sweden)

    Werner Kuhn

    2012-09-01

    Full Text Available Although the integration of sensor-based information into analysis and decision making has been a research topic for many years, semantic interoperability has not yet been reached. The advent of user-generated content for the geospatial domain, Volunteered Geographic Information (VGI, makes it even more difficult to establish semantic integration. This paper proposes a novel approach to integrating conventional sensor information and VGI, which is exploited in the context of detecting forest fires. In contrast to common logic-based semantic descriptions, we present a formal system using algebraic specifications to unambiguously describe the processing steps from natural phenomena to value-added information. A generic ontology of observations is extended and profiled for forest fire detection in order to illustrate how the sensing process, and transformations between heterogeneous sensing systems, can be represented as mathematical functions and grouped into abstract data types. We discuss the required ontological commitments and a possible generalization.

  11. Semi-automated ontology generation and evolution

    Science.gov (United States)

    Stirtzinger, Anthony P.; Anken, Craig S.

    2009-05-01

    Extending the notion of data models or object models, ontology can provide rich semantic definition not only to the meta-data but also to the instance data of domain knowledge, making these semantic definitions available in machine readable form. However, the generation of an effective ontology is a difficult task involving considerable labor and skill. This paper discusses an Ontology Generation and Evolution Processor (OGEP) aimed at automating this process, only requesting user input when un-resolvable ambiguous situations occur. OGEP directly attacks the main barrier which prevents automated (or self learning) ontology generation: the ability to understand the meaning of artifacts and the relationships the artifacts have to the domain space. OGEP leverages existing lexical to ontological mappings in the form of WordNet, and Suggested Upper Merged Ontology (SUMO) integrated with a semantic pattern-based structure referred to as the Semantic Grounding Mechanism (SGM) and implemented as a Corpus Reasoner. The OGEP processing is initiated by a Corpus Parser performing a lexical analysis of the corpus, reading in a document (or corpus) and preparing it for processing by annotating words and phrases. After the Corpus Parser is done, the Corpus Reasoner uses the parts of speech output to determine the semantic meaning of a word or phrase. The Corpus Reasoner is the crux of the OGEP system, analyzing, extrapolating, and evolving data from free text into cohesive semantic relationships. The Semantic Grounding Mechanism provides a basis for identifying and mapping semantic relationships. By blending together the WordNet lexicon and SUMO ontological layout, the SGM is given breadth and depth in its ability to extrapolate semantic relationships between domain entities. The combination of all these components results in an innovative approach to user assisted semantic-based ontology generation. This paper will describe the OGEP technology in the context of the architectural

  12. The MMI Device Ontology: Enabling Sensor Integration

    Science.gov (United States)

    Rueda, C.; Galbraith, N.; Morris, R. A.; Bermudez, L. E.; Graybeal, J.; Arko, R. A.; Mmi Device Ontology Working Group

    2010-12-01

    The Marine Metadata Interoperability (MMI) project has developed an ontology for devices to describe sensors and sensor networks. This ontology is implemented in the W3C Web Ontology Language (OWL) and provides an extensible conceptual model and controlled vocabularies for describing heterogeneous instrument types, with different data characteristics, and their attributes. It can help users populate metadata records for sensors; associate devices with their platforms, deployments, measurement capabilities and restrictions; aid in discovery of sensor data, both historic and real-time; and improve the interoperability of observational oceanographic data sets. We developed the MMI Device Ontology following a community-based approach. By building on and integrating other models and ontologies from related disciplines, we sought to facilitate semantic interoperability while avoiding duplication. Key concepts and insights from various communities, including the Open Geospatial Consortium (eg., SensorML and Observations and Measurements specifications), Semantic Web for Earth and Environmental Terminology (SWEET), and W3C Semantic Sensor Network Incubator Group, have significantly enriched the development of the ontology. Individuals ranging from instrument designers, science data producers and consumers to ontology specialists and other technologists contributed to the work. Applications of the MMI Device Ontology are underway for several community use cases. These include vessel-mounted multibeam mapping sonars for the Rolling Deck to Repository (R2R) program and description of diverse instruments on deepwater Ocean Reference Stations for the OceanSITES program. These trials involve creation of records completely describing instruments, either by individual instances or by manufacturer and model. Individual terms in the MMI Device Ontology can be referenced with their corresponding Uniform Resource Identifiers (URIs) in sensor-related metadata specifications (e

  13. The Role of Semantics in Translation Recognition: Effects of Number of Translations, Dominance of Translations and Semantic Relatedness of Multiple Translations

    Science.gov (United States)

    Laxen, Jannika; Lavaur, Jean-Marc

    2010-01-01

    This study aims to examine the influence of multiple translations of a word on bilingual processing in three translation recognition experiments during which French-English bilinguals had to decide whether two words were translations of each other or not. In the first experiment, words with only one translation were recognized as translations…

  14. Anatomy Ontology Matching Using Markov Logic Networks

    Directory of Open Access Journals (Sweden)

    Chunhua Li

    2016-01-01

    Full Text Available The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

  15. Semantic relation vs. surprise: the differential effects of related and unrelated co-verbal gestures on neural encoding and subsequent recognition.

    Science.gov (United States)

    Straube, Benjamin; Meyer, Lea; Green, Antonia; Kircher, Tilo

    2014-06-03

    Speech-associated gesturing leads to memory advantages for spoken sentences. However, unexpected or surprising events are also likely to be remembered. With this study we test the hypothesis that different neural mechanisms (semantic elaboration and surprise) lead to memory advantages for iconic and unrelated gestures. During fMRI-data acquisition participants were presented with video clips of an actor verbalising concrete sentences accompanied by iconic gestures (IG; e.g., circular gesture; sentence: "The man is sitting at the round table"), unrelated free gestures (FG; e.g., unrelated up down movements; same sentence) and no gestures (NG; same sentence). After scanning, recognition performance for the three conditions was tested. Videos were evaluated regarding semantic relation and surprise by a different group of participants. The semantic relationship between speech and gesture was rated higher for IG (IG>FG), whereas surprise was rated higher for FG (FG>IG). Activation of the hippocampus correlated with subsequent memory performance of both gesture conditions (IG+FG>NG). For the IG condition we found activation in the left temporal pole and middle cingulate cortex (MCC; IG>FG). In contrast, for the FG condition posterior thalamic structures (FG>IG) as well as anterior and posterior cingulate cortices were activated (FG>NG). Our behavioral and fMRI-data suggest different mechanisms for processing related and unrelated co-verbal gestures, both of them leading to enhanced memory performance. Whereas activation in MCC and left temporal pole for iconic co-verbal gestures may reflect semantic memory processes, memory enhancement for unrelated gestures relies on the surprise response, mediated by anterior/posterior cingulate cortex and thalamico-hippocampal structures. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Use artificial neural network to align biological ontologies.

    Science.gov (United States)

    Huang, Jingshan; Dang, Jiangbo; Huhns, Michael N; Zheng, W Jim

    2008-09-16

    Being formal, declarative knowledge representation models, ontologies help to address the problem of imprecise terminologies in biological and biomedical research. However, ontologies constructed under the auspices of the Open Biomedical Ontologies (OBO) group have exhibited a great deal of variety, because different parties can design ontologies according to their own conceptual views of the world. It is therefore becoming critical to align ontologies from different parties. During automated/semi-automated alignment across biological ontologies, different semantic aspects, i.e., concept name, concept properties, and concept relationships, contribute in different degrees to alignment results. Therefore, a vector of weights must be assigned to these semantic aspects. It is not trivial to determine what those weights should be, and current methodologies depend a lot on human heuristics. In this paper, we take an artificial neural network approach to learn and adjust these weights, and thereby support a new ontology alignment algorithm, customized for biological ontologies, with the purpose of avoiding some disadvantages in both rule-based and learning-based aligning algorithms. This approach has been evaluated by aligning two real-world biological ontologies, whose features include huge file size, very few instances, concept names in numerical strings, and others. The promising experiment results verify our proposed hypothesis, i.e., three weights for semantic aspects learned from a subset of concepts are representative of all concepts in the same ontology. Therefore, our method represents a large leap forward towards automating biological ontology alignment.

  17. Selective verbal recognition memory impairments are associated with atrophy of the language network in non-semantic variants of primary progressive aphasia.

    Science.gov (United States)

    Nilakantan, Aneesha S; Voss, Joel L; Weintraub, Sandra; Mesulam, M-Marsel; Rogalski, Emily J

    2017-06-01

    Primary progressive aphasia (PPA) is clinically defined by an initial loss of language function and preservation of other cognitive abilities, including episodic memory. While PPA primarily affects the left-lateralized perisylvian language network, some clinical neuropsychological tests suggest concurrent initial memory loss. The goal of this study was to test recognition memory of objects and words in the visual and auditory modality to separate language-processing impairments from retentive memory in PPA. Individuals with non-semantic PPA had longer reaction times and higher false alarms for auditory word stimuli compared to visual object stimuli. Moreover, false alarms for auditory word recognition memory were related to cortical thickness within the left inferior frontal gyrus and left temporal pole, while false alarms for visual object recognition memory was related to cortical thickness within the right-temporal pole. This pattern of results suggests that specific vulnerability in processing verbal stimuli can hinder episodic memory in PPA, and provides evidence for differential contributions of the left and right temporal poles in word and object recognition memory. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Ontological Planning

    Directory of Open Access Journals (Sweden)

    Ahmet Alkan

    2017-12-01

    • Is it possible to redefine ontology within the hierarchical structure of planning? We are going to seek answers to some of these questions within the limited scope of this paper and we are going to offer the rest for discussion by just asking them. In light of these assessments, drawing attention, based on ontological knowledge relying on the wholeness of universe, to the question, on macro level planning, of whether or not the ontological realities of man, energy and movements of thinking can provide macro data for planning on a universal level as important factors affecting mankind will be one of the limited objectives of the paper.

  19. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects.

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A; Noy, Natalya F

    2013-05-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product . In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.

  20. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A.; Noy, Natalya F.

    2013-01-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches. PMID:24311994

  1. Where to Publish and Find Ontologies? A Survey of Ontology Libraries

    Science.gov (United States)

    d'Aquin, Mathieu; Noy, Natalya F.

    2011-01-01

    One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to “talk” to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing—and surprisingly diverse—landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries a ects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address. PMID:22408576

  2. Towards IoT platforms’ integration : Semantic Translations between W3C SSN and ETSI SAREF

    NARCIS (Netherlands)

    Moreira, João Luiz; Daniele, L.M.; Ferreira Pires, Luis; van Sinderen, Marten J.; Wasielewska, Katarzyna; Szmeja, Pawel; Pawlowski, Wieslaw; Ganzha, Maria; Paprzycki, Marcin

    2017-01-01

    Several IoT ontologies have been developed lately to improve the semantic interoperability of IoT solutions. The most popular of these ontologies, the W3C Semantic Sensor Network (SSN), is considered an ontological foundation for diverse IoT initiatives, particularly OpenIoT. With characteristics

  3. Evaluating the effect of annotation size on measures of semantic similarity

    KAUST Repository

    Kulmanov, Maxat

    2017-02-13

    Background: Ontologies are widely used as metadata in biological and biomedical datasets. Measures of semantic similarity utilize ontologies to determine how similar two entities annotated with classes from ontologies are, and semantic similarity is increasingly applied in applications ranging from diagnosis of disease to investigation in gene networks and functions of gene products.

  4. Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

    KAUST Repository

    Alghamdi, Sarah M.

    2018-01-01

    To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

  5. Ontology-based multi-agent systems

    Energy Technology Data Exchange (ETDEWEB)

    Hadzic, Maja; Wongthongtham, Pornpit; Dillon, Tharam; Chang, Elizabeth [Digital Ecosystems and Business Intelligence Institute, Perth, WA (Australia)

    2009-07-01

    The Semantic web has given a great deal of impetus to the development of ontologies and multi-agent systems. Several books have appeared which discuss the development of ontologies or of multi-agent systems separately on their own. The growing interaction between agents and ontologies has highlighted the need for integrated development of these. This book is unique in being the first to provide an integrated treatment of the modeling, design and implementation of such combined ontology/multi-agent systems. It provides clear exposition of this integrated modeling and design methodology. It further illustrates this with two detailed case studies in (a) the biomedical area and (b) the software engineering area. The book is, therefore, of interest to researchers, graduate students and practitioners in the semantic web and web science area. (orig.)

  6. Interoperability between phenotype and anatomy ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

    2010-12-15

    Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

  7. Semantic technologies in a decision support system

    Science.gov (United States)

    Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

    2015-10-01

    The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

  8. Automatic Tamil lyric generation based on ontological interpretation ...

    Indian Academy of Sciences (India)

    In this work, we use an ontology to determine the semantic information from ... Hence, to study the context-based lyric generation process, we referred to ...... Mann C W and Moore A J 1981 Computer Generation of Multiparagraph English text.

  9. An Extensible, Ontology-based, Distributed Information System Architecture

    National Research Council Canada - National Science Library

    Chao, Alan I; Krikeles, Basil C; Lusignan, Angela E; Starczewski, Edward

    2003-01-01

    ...), which facilitates the construction of scalable, flexible distributed systems. XDA is based on a simple ontology mechanism that enables the definition and maintenance of high-level object models to capture the shared semantics necessary for interoperability...

  10. Constructing a Geology Ontology Using a Relational Database

    Science.gov (United States)

    Hou, W.; Yang, L.; Yin, S.; Ye, J.; Clarke, K.

    2013-12-01

    In geology community, the creation of a common geology ontology has become a useful means to solve problems of data integration, knowledge transformation and the interoperation of multi-source, heterogeneous and multiple scale geological data. Currently, human-computer interaction methods and relational database-based methods are the primary ontology construction methods. Some human-computer interaction methods such as the Geo-rule based method, the ontology life cycle method and the module design method have been proposed for applied geological ontologies. Essentially, the relational database-based method is a reverse engineering of abstracted semantic information from an existing database. The key is to construct rules for the transformation of database entities into the ontology. Relative to the human-computer interaction method, relational database-based methods can use existing resources and the stated semantic relationships among geological entities. However, two problems challenge the development and application. One is the transformation of multiple inheritances and nested relationships and their representation in an ontology. The other is that most of these methods do not measure the semantic retention of the transformation process. In this study, we focused on constructing a rule set to convert the semantics in a geological database into a geological ontology. According to the relational schema of a geological database, a conversion approach is presented to convert a geological spatial database to an OWL-based geological ontology, which is based on identifying semantics such as entities, relationships, inheritance relationships, nested relationships and cluster relationships. The semantic integrity of the transformation was verified using an inverse mapping process. In a geological ontology, an inheritance and union operations between superclass and subclass were used to present the nested relationship in a geochronology and the multiple inheritances

  11. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  12. OMOGENIA: A Semantically Driven Collaborative Environment

    Science.gov (United States)

    Liapis, Aggelos

    Ontology creation can be thought of as a social procedure. Indeed the concepts involved in general need to be elicited from communities of domain experts and end-users by teams of knowledge engineers. Many problems in ontology creation appear to resemble certain problems in software design, particularly with respect to the setup of collaborative systems. For instance, the resolution of conceptual conflicts between formalized ontologies is a major engineering problem as ontologies move into widespread use on the semantic web. Such conflict resolution often requires human collaboration and cannot be achieved by automated methods with the exception of simple cases. In this chapter we discuss research in the field of computer-supported cooperative work (CSCW) that focuses on classification and which throws light on ontology building. Furthermore, we present a semantically driven collaborative environment called OMOGENIA as a natural way to display and examine the structure of an evolving ontology in a collaborative setting.

  13. The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability.

    Science.gov (United States)

    He, Yongqun; Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; Overton, James A; Ong, Edison

    2018-01-12

    Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an "eXtensible Ontology Development" (XOD) strategy and its associated four principles. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).

  14. SUGOI: automated ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2015-04-01

    Full Text Available A foundational ontology can solve interoperability issues among the domain ontologies aligned to it. However, several foundational ontologies have been developed, hence such interoperability issues exist among domain ontologies. The novel SUGOI tool...

  15. Ontology modeling in physical asset integrity management

    CERN Document Server

    Yacout, Soumaya

    2015-01-01

    This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles. This book also: Introduces practicing engineers, research scientists, and graduate students to ontology engineering as a modeling techniqu...

  16. Cross document ontology based information for multimedia retrieval

    NARCIS (Netherlands)

    Reidsma, Dennis; Kuper, Jan; Declerck, T.; Saggion, H.; Cunningham, H.; Ganter, B.; de Moor, A.

    2003-01-01

    This paper describes the MUMIS project, which applies ontology based Information Extraction to improve the results of Information Retrieval in multimedia archives. It makes use of a domain specific ontology, multilingual lexicons and reasoning algorithms to automatically create a semantic annotation

  17. Interpreting XML documents via an RDF schema ontology

    NARCIS (Netherlands)

    Klein, Michel

    2002-01-01

    Many business documents are represented in XML. However XML only describes the structure of data, not its meaning. The meaning of data is required for advanced automated processing, as is envisaged in the "Semantic Web". Ontologies are often used to describe the meaning of data items. Many ontology

  18. Ontology Extraction Tools: An Empirical Study with Educators

    Science.gov (United States)

    Hatala, M.; Gasevic, D.; Siadaty, M.; Jovanovic, J.; Torniai, C.

    2012-01-01

    Recent research in Technology-Enhanced Learning (TEL) demonstrated several important benefits that semantic technologies can bring to the TEL domain. An underlying assumption for most of these research efforts is the existence of a domain ontology. The second unspoken assumption follows that educators will build domain ontologies for their…

  19. An ontology design pattern for surface water features

    Science.gov (United States)

    Sinha, Gaurav; Mark, David; Kolas, Dave; Varanka, Dalia; Romero, Boleslo E.; Feng, Chen-Chieh; Usery, E. Lynn; Liebermann, Joshua; Sorokine, Alexandre

    2014-01-01

    Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities exist due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology for other more context-dependent ontologies. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex or specialized surface water ontologies. A fundamental distinction is made in this ontology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is implemented in OWL, but Description Logic axioms and a detailed explanation is provided in this paper. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. Also provided is a discussion of why there is a need to complement the pattern with other ontologies, especially the previously developed Surface Network pattern. Finally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through an annotated geospatial dataset and sample queries using the classes of the Surface Water pattern.

  20. A Knowledge Base for Automatic Feature Recognition from Point Clouds in an Urban Scene

    Directory of Open Access Journals (Sweden)

    Xu-Feng Xing

    2018-01-01

    Full Text Available LiDAR technology can provide very detailed and highly accurate geospatial information on an urban scene for the creation of Virtual Geographic Environments (VGEs for different applications. However, automatic 3D modeling and feature recognition from LiDAR point clouds are very complex tasks. This becomes even more complex when the data is incomplete (occlusion problem or uncertain. In this paper, we propose to build a knowledge base comprising of ontology and semantic rules aiming at automatic feature recognition from point clouds in support of 3D modeling. First, several modules for ontology are defined from different perspectives to describe an urban scene. For instance, the spatial relations module allows the formalized representation of possible topological relations extracted from point clouds. Then, a knowledge base is proposed that contains different concepts, their properties and their relations, together with constraints and semantic rules. Then, instances and their specific relations form an urban scene and are added to the knowledge base as facts. Based on the knowledge and semantic rules, a reasoning process is carried out to extract semantic features of the objects and their components in the urban scene. Finally, several experiments are presented to show the validity of our approach to recognize different semantic features of buildings from LiDAR point clouds.

  1. Uncertainty modeling process for semantic technology

    Directory of Open Access Journals (Sweden)

    Rommel N. Carvalho

    2016-08-01

    Full Text Available The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST, a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

  2. An approach to development of ontological knowledge base in the field of scientific and research activity in Russia

    Science.gov (United States)

    Murtazina, M. Sh; Avdeenko, T. V.

    2018-05-01

    The state of art and the progress in application of semantic technologies in the field of scientific and research activity have been analyzed. Even elementary empirical comparison has shown that the semantic search engines are superior in all respects to conventional search technologies. However, semantic information technologies are insufficiently used in the field of scientific and research activity in Russia. In present paper an approach to construction of ontological model of knowledge base is proposed. The ontological model is based on the upper-level ontology and the RDF mechanism for linking several domain ontologies. The ontological model is implemented in the Protégé environment.

  3. Application of Ontologies for Big Earth Data

    Science.gov (United States)

    Huang, T.; Chang, G.; Armstrong, E. M.; Boening, C.

    2014-12-01

    Connected data is smarter data! Earth Science research infrastructure must do more than just being able to support temporal, geospatial discovery of satellite data. As the Earth Science data archives continue to expand across NASA data centers, the research communities are demanding smarter data services. A successful research infrastructure must be able to present researchers the complete picture, that is, datasets with linked citations, related interdisciplinary data, imageries, current events, social media discussions, and scientific data tools that are relevant to the particular dataset. The popular Semantic Web for Earth and Environmental Terminology (SWEET) ontologies is a collection of ontologies and concepts designed to improve discovery and application of Earth Science data. The SWEET ontologies collection was initially developed to capture the relationships between keywords in the NASA Global Change Master Directory (GCMD). Over the years this popular ontologies collection has expanded to cover over 200 ontologies and 6000 concepts to enable scalable classification of Earth system science concepts and Space science. This presentation discusses the semantic web technologies as the enabling technology for data-intensive science. We will discuss the application of the SWEET ontologies as a critical component in knowledge-driven research infrastructure for some of the recent projects, which include the DARPA Ontological System for Context Artifact and Resources (OSCAR), 2013 NASA ACCESS Virtual Quality Screening Service (VQSS), and the 2013 NASA Sea Level Change Portal (SLCP) projects. The presentation will also discuss the benefits in using semantic web technologies in developing research infrastructure for Big Earth Science Data in an attempt to "accommodate all domains and provide the necessary glue for information to be cross-linked, correlated, and discovered in a semantically rich manner." [1] [1] Savas Parastatidis: A platform for all that we know

  4. Aber-OWL: a framework for ontology-based data access in biology

    KAUST Repository

    Hoehndorf, Robert

    2015-01-28

    Background: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning. Results: We have developed the Aber-OWL infrastructure that provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL is freely available at http://aber-owl.net. Conclusions: Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.

  5. Pedagogically-Driven Ontology Network for Conceptualizing the e-Learning Assessment Domain

    Science.gov (United States)

    Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura

    2015-01-01

    The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…

  6. An Approach to Folksonomy-Based Ontology Maintenance for Learning Environments

    Science.gov (United States)

    Gasevic, D.; Zouaq, Amal; Torniai, Carlo; Jovanovic, J.; Hatala, Marek

    2011-01-01

    Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning…

  7. Ontology-Based Retrieval of Spatially Related Objects for Location Based Services

    Science.gov (United States)

    Haav, Hele-Mai; Kaljuvee, Aivi; Luts, Martin; Vajakas, Toivo

    Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.

  8. A New role of ontologies and advanced scientific visualization in big data analytics

    OpenAIRE

    Chuprina, Svetlana

    2016-01-01

    Accessing and contextual semantic searching structured, semi-structured and unstructured information resources and their ontology based analysis in a uniform way across text-free Big Data query implementation is a main feature of approach under discussion. To increase the semantic power of query results’ analysis the ontology based implementation of multiplatform adaptive tools of scientific visualization are demonstrated. The ontologies are used not for integration of heterogeneous resources...

  9. Discovery and Selection of Semantic Web Services

    CERN Document Server

    Wang, Xia

    2013-01-01

    For advanced web search engines to be able not only to search for semantically related information dispersed over different web pages, but also for semantic services providing certain functionalities, discovering semantic services is the key issue. Addressing four problems of current solution, this book presents the following contributions. A novel service model independent of semantic service description models is proposed, which clearly defines all elements necessary for service discovery and selection. It takes service selection as its gist and improves efficiency. Corresponding selection algorithms and their implementation as components of the extended Semantically Enabled Service-oriented Architecture in the Web Service Modeling Environment are detailed. Many applications of semantic web services, e.g. discovery, composition and mediation, can benefit from a general approach for building application ontologies. With application ontologies thus built, services are discovered in the same way as with single...

  10. DMTO: a realistic ontology for standard diabetes mellitus treatment.

    Science.gov (United States)

    El-Sappagh, Shaker; Kwak, Daehan; Ali, Farman; Kwak, Kyung-Sup

    2018-02-06

    Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accuracy. The most important component of any CDSS is its knowledge base. This knowledge base can be formulated using ontologies. The formal description logic of ontology supports the inference of hidden knowledge. Building a complete, coherent, consistent, interoperable, and sharable ontology is a challenge. This paper introduces the first version of the newly constructed Diabetes Mellitus Treatment Ontology (DMTO) as a basis for shared-semantics, domain-specific, standard, machine-readable, and interoperable knowledge relevant to T2DM treatment. It is a comprehensive ontology and provides the highest coverage and the most complete picture of coded knowledge about T2DM patients' current conditions, previous profiles, and T2DM-related aspects, including complications, symptoms, lab tests, interactions, treatment plan (TP) frameworks, and glucose-related diseases and medications. It adheres to the design principles recommended by the Open Biomedical Ontologies Foundry and is based on ontological realism that follows the principles of the Basic Formal Ontology and the Ontology for General Medical Science. DMTO is implemented under Protégé 5.0 in Web Ontology Language (OWL) 2 format and is publicly available through the National Center for Biomedical Ontology's BioPortal at http://bioportal.bioontology.org/ontologies/DMTO . The current version of DMTO includes more than 10,700 classes, 277 relations, 39,425 annotations, 214 semantic rules, and 62,974 axioms. We provide proof of concept for this approach to modeling TPs. The ontology is able to collect and analyze most features of T2DM as well as customize chronic TPs with the most appropriate drugs, foods, and physical exercises. DMTO is ready to be used as a knowledge base for

  11. Mapping between the OBO and OWL ontology languages.

    Science.gov (United States)

    Tirmizi, Syed Hamid; Aitken, Stuart; Moreira, Dilvan A; Mungall, Chris; Sequeda, Juan; Shah, Nigam H; Miranker, Daniel P

    2011-03-07

    Ontologies are commonly used in biomedicine to organize concepts to describe domains such as anatomies, environments, experiment, taxonomies etc. NCBO BioPortal currently hosts about 180 different biomedical ontologies. These ontologies have been mainly expressed in either the Open Biomedical Ontology (OBO) format or the Web Ontology Language (OWL). OBO emerged from the Gene Ontology, and supports most of the biomedical ontology content. In comparison, OWL is a Semantic Web language, and is supported by the World Wide Web consortium together with integral query languages, rule languages and distributed infrastructure for information interchange. These features are highly desirable for the OBO content as well. A convenient method for leveraging these features for OBO ontologies is by transforming OBO ontologies to OWL. We have developed a methodology for translating OBO ontologies to OWL using the organization of the Semantic Web itself to guide the work. The approach reveals that the constructs of OBO can be grouped together to form a similar layer cake. Thus we were able to decompose the problem into two parts. Most OBO constructs have easy and obvious equivalence to a construct in OWL. A small subset of OBO constructs requires deeper consideration. We have defined transformations for all constructs in an effort to foster a standard common mapping between OBO and OWL. Our mapping produces OWL-DL, a Description Logics based subset of OWL with desirable computational properties for efficiency and correctness. Our Java implementation of the mapping is part of the official Gene Ontology project source. Our transformation system provides a lossless roundtrip mapping for OBO ontologies, i.e. an OBO ontology may be translated to OWL and back without loss of knowledge. In addition, it provides a roadmap for bridging the gap between the two ontology languages in order to enable the use of ontology content in a language independent manner.

  12. Semantic Memory in the Clinical Progression of Alzheimer Disease.

    Science.gov (United States)

    Tchakoute, Christophe T; Sainani, Kristin L; Henderson, Victor W

    2017-09-01

    Semantic memory measures may be useful in tracking and predicting progression of Alzheimer disease. We investigated relationships among semantic memory tasks and their 1-year predictive value in women with Alzheimer disease. We conducted secondary analyses of a randomized clinical trial of raloxifene in 42 women with late-onset mild-to-moderate Alzheimer disease. We assessed semantic memory with tests of oral confrontation naming, category fluency, semantic recognition and semantic naming, and semantic density in written narrative discourse. We measured global cognition (Alzheimer Disease Assessment Scale, cognitive subscale), dementia severity (Clinical Dementia Rating sum of boxes), and daily function (Activities of Daily Living Inventory) at baseline and 1 year. At baseline and 1 year, most semantic memory scores correlated highly or moderately with each other and with global cognition, dementia severity, and daily function. Semantic memory task performance at 1 year had worsened one-third to one-half standard deviation. Factor analysis of baseline test scores distinguished processes in semantic and lexical retrieval (semantic recognition, semantic naming, confrontation naming) from processes in lexical search (semantic density, category fluency). The semantic-lexical retrieval factor predicted global cognition at 1 year. Considered separately, baseline confrontation naming and category fluency predicted dementia severity, while semantic recognition and a composite of semantic recognition and semantic naming predicted global cognition. No individual semantic memory test predicted daily function. Semantic-lexical retrieval and lexical search may represent distinct aspects of semantic memory. Semantic memory processes are sensitive to cognitive decline and dementia severity in Alzheimer disease.

  13. Automatic Tamil lyric generation based on ontological interpretation ...

    Indian Academy of Sciences (India)

    This system proposes an -gram based approach to automatic Tamil lyric generation, by the ontological semantic interpretation of the input scene. The approach is based on identifying the semantics conveyed in the scenario, thereby making the system understand the situation and generate lyrics accordingly. The heart of ...

  14. Semantic memory in object use.

    Science.gov (United States)

    Silveri, Maria Caterina; Ciccarelli, Nicoletta

    2009-10-01

    We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.

  15. Contributions to a Conceptual Ontology for Wittgenstein

    DEFF Research Database (Denmark)

    Addis, Mark; Brock, Steen; Pichler, Alois

    2015-01-01

    A conceptual ontology was used to semantically enrich the Wittgenstein Archives at the University of Bergen’s taxonomy for Wittgenstein Source to facilitate improved searching in the areas of the philosophies of mathematics and psychology. The classes and sub-classes of the multilingual taxonomy...

  16. Recognition

    DEFF Research Database (Denmark)

    Gimmler, Antje

    2017-01-01

    In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory mus...

  17. Mediation, Alignment, and Information Services for Semantic interoperability (MAISSI): A Trade Study

    National Research Council Canada - National Science Library

    Barlos, Fotis; Hunter, Dan; Krikeles, Basil; McDonough, James

    2007-01-01

    .... Semantic Interoperability (SI) encompasses a broad range of technologies such as data mediation and schema matching, ontology alignment, and context representation that attempt to enable systems to understand each others semantics...

  18. Nuclear Nonproliferation Ontology Assessment Team Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Strasburg, Jana D.; Hohimer, Ryan E.

    2012-01-01

    Final Report for the NA22 Simulations, Algorithm and Modeling (SAM) Ontology Assessment Team's efforts from FY09-FY11. The Ontology Assessment Team began in May 2009 and concluded in September 2011. During this two-year time frame, the Ontology Assessment team had two objectives: (1) Assessing the utility of knowledge representation and semantic technologies for addressing nuclear nonproliferation challenges; and (2) Developing ontological support tools that would provide a framework for integrating across the Simulation, Algorithm and Modeling (SAM) program. The SAM Program was going through a large assessment and strategic planning effort during this time and as a result, the relative importance of these two objectives changed, altering the focus of the Ontology Assessment Team. In the end, the team conducted an assessment of the state of art, created an annotated bibliography, and developed a series of ontological support tools, demonstrations and presentations. A total of more than 35 individuals from 12 different research institutions participated in the Ontology Assessment Team. These included subject matter experts in several nuclear nonproliferation-related domains as well as experts in semantic technologies. Despite the diverse backgrounds and perspectives, the Ontology Assessment team functioned very well together and aspects could serve as a model for future inter-laboratory collaborations and working groups. While the team encountered several challenges and learned many lessons along the way, the Ontology Assessment effort was ultimately a success that led to several multi-lab research projects and opened up a new area of scientific exploration within the Office of Nuclear Nonproliferation and Verification.

  19. BiOSS: A system for biomedical ontology selection.

    Science.gov (United States)

    Martínez-Romero, Marcos; Vázquez-Naya, José M; Pereira, Javier; Pazos, Alejandro

    2014-04-01

    In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Semantic Learning Service Personalized

    Directory of Open Access Journals (Sweden)

    Yibo Chen

    2012-02-01

    Full Text Available To provide users with more suitable and personalized service, personalization is widely used in various fields. Current e-Learning systems search for learning resources using information search technology, based on the keywords that selected or inputted by the user. Due to lack of semantic analysis for keywords and exploring the user contexts, the system cannot provide a good learning experiment. In this paper, we defined the concept and characteristic of the personalized learning service, and proposed a semantic learning service personalized framework. Moreover, we made full use of semantic technology, using ontologies to represent the learning contents and user profile, mining and utilizing the friendship and membership of the social relationship to construct the user social relationship profile, and improved the collaboration filtering algorithm to recommend personalized learning resources for users. The results of the empirical evaluation show that the approach is effectiveness in augmenting recommendation.

  1. A Cognitive Support Framework for Ontology Mapping

    Science.gov (United States)

    Falconer, Sean M.; Storey, Margaret-Anne

    Ontology mapping is the key to data interoperability in the semantic web. This problem has received a lot of research attention, however, the research emphasis has been mostly devoted to automating the mapping process, even though the creation of mappings often involve the user. As industry interest in semantic web technologies grows and the number of widely adopted semantic web applications increases, we must begin to support the user. In this paper, we combine data gathered from background literature, theories of cognitive support and decision making, and an observational case study to propose a theoretical framework for cognitive support in ontology mapping tools. We also describe a tool called CogZ that is based on this framework.

  2. From Patient Discharge Summaries to an Ontology for Psychiatry.

    Science.gov (United States)

    Richard, Marion; Aimé, Xavier; Jaulent, Marie-Christine; Krebs, Marie-Odile; Charlet, Jean

    2017-01-01

    Psychiatry aims at detecting symptoms, providing diagnoses and treating mental disorders. We developed ONTOPSYCHIA, an ontology for psychiatry in three modules: social and environmental factors of mental disorders, mental disorders, and treatments. The use of ONTOPSYCHIA, associated with dedicated tools, will facilitate semantic research in Patient Discharge Summaries (PDS). To develop the first module of the ontology we propose a PDS text analysis in order to explicit psychiatry concepts. We decided to set aside classifications during the construction of the modu le, to focus only on the information contained in PDS (bottom-up approach) and to return to domain classifications solely for the enrichment phase (top-down approach). Then, we focused our work on the development of the LOVMI methodology (Les Ontologies Validées par Méthode Interactive - Ontologies Validated by Interactive Method), which aims to provide a methodological framework to validate the structure and the semantic of an ontology.

  3. Building ontologies with basic formal ontology

    CERN Document Server

    Arp, Robert; Spear, Andrew D.

    2015-01-01

    In the era of "big data," science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now u...

  4. Markov Chain Ontology Analysis (MCOA).

    Science.gov (United States)

    Frost, H Robert; McCray, Alexa T

    2012-02-03

    Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.

  5. Metadata and Ontologies in Learning Resources Design

    Science.gov (United States)

    Vidal C., Christian; Segura Navarrete, Alejandra; Menéndez D., Víctor; Zapata Gonzalez, Alfredo; Prieto M., Manuel

    Resource design and development requires knowledge about educational goals, instructional context and information about learner's characteristics among other. An important information source about this knowledge are metadata. However, metadata by themselves do not foresee all necessary information related to resource design. Here we argue the need to use different data and knowledge models to improve understanding the complex processes related to e-learning resources and their management. This paper presents the use of semantic web technologies, as ontologies, supporting the search and selection of resources used in design. Classification is done, based on instructional criteria derived from a knowledge acquisition process, using information provided by IEEE-LOM metadata standard. The knowledge obtained is represented in an ontology using OWL and SWRL. In this work we give evidence of the implementation of a Learning Object Classifier based on ontology. We demonstrate that the use of ontologies can support the design activities in e-learning.

  6. Semantic Advertising

    OpenAIRE

    Zamanzadeh, Ben; Ashish, Naveen; Ramakrishnan, Cartic; Zimmerman, John

    2013-01-01

    We present the concept of Semantic Advertising which we see as the future of online advertising. Semantic Advertising is online advertising powered by semantic technology which essentially enables us to represent and reason with concepts and the meaning of things. This paper aims to 1) Define semantic advertising, 2) Place it in the context of broader and more widely used concepts such as the Semantic Web and Semantic Search, 3) Provide a survey of work in related areas such as context matchi...

  7. Ontology authoring with Forza

    CSIR Research Space (South Africa)

    Keet, CM

    2014-11-01

    Full Text Available Generic, reusable ontology elements, such as a foundational ontology's categories and part-whole relations, are essential for good and interoperable knowledge representation. Ontology developers, which include domain experts and novices, face...

  8. SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

    Science.gov (United States)

    Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.

    2004-01-01

    SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.

  9. Semantic Context Reasoning Using Ontology Based Models

    NARCIS (Netherlands)

    Mantovaneli Pessoa, Rodrigo; Calvi, Camilo Zardo; Pereira Filho, J.G.; Pereira Filho, José Gonçalves; Guareis de farias, Cléver; Neisse, R.; Pras, A.; Pras, Aiko; van Sinderen, M.J.; van Sinderen, Marten J.

    New mobile computing technologies and the increasing use of portable devices have pushed the development of the so-called context-aware applications. This new class of applications aims at improving human-computer interactions by supporting dynamic adaptations according to context changes. This

  10. Citation and Recognition of contributions using Semantic Provenance Knowledge Captured in the OPeNDAP Software Framework

    Science.gov (United States)

    West, P.; Michaelis, J.; Lebot, T.; McGuinness, D. L.; Fox, P. A.

    2014-12-01

    Providing proper citation and attribution for published data, derived data products, and the software tools used to generate them, has always been an important aspect of scientific research. However, It is often the case that this type of detailed citation and attribution is lacking. This is in part because it often requires manual markup since dynamic generation of this type of provenance information is not typically done by the tools used to access, manipulate, transform, and visualize data. In addition, the tools themselves lack the information needed to be properly cited themselves. The OPeNDAP Hyrax Software Framework is a tool that provides access to and the ability to constrain, manipulate, and transform, different types of data from different data formats, into a common format, the DAP (Data Access Protocol), in order to derive new data products. A user, or another software client, specifies an HTTP URL in order to access a particular piece of data, and appropriately transform it to suit a specific purpose of use. The resulting data products, however, do not contain any information about what data was used to create it, or the software process used to generate it, let alone information that would allow the proper citing and attribution to down stream researchers and tool developers. We will present our approach to provenance capture in Hyrax including a mechanism that can be used to report back to the hosting site any derived products, such as publications and reports, using the W3C PROV recommendation pingback service. We will demonstrate our utilization of Semantic Web and Web standards, the development of an information model that extends the PROV model for provenance capture, and the development of the pingback service. We will present our findings, as well as our practices for providing provenance information, visualization of the provenance information, and the development of pingback services, to better enable scientists and tool developers to be

  11. Geo-Ontologies Are Scale Dependent

    Science.gov (United States)

    Frank, A. U.

    2009-04-01

    Philosophers aim at a single ontology that describes "how the world is"; for information systems we aim only at ontologies that describe a conceptualization of reality (Guarino 1995; Gruber 2005). A conceptualization of the world implies a spatial and temporal scale: what are the phenomena, the objects and the speed of their change? Few articles (Reitsma et al. 2003) seem to address that an ontology is scale specific (but many articles indicate that ontologies are scale-free in another sense namely that they are scale free in the link densities between concepts). The scale in the conceptualization can be linked to the observation process. The extent of the support of the physical observation instrument and the sampling theorem indicate what level of detail we find in a dataset. These rules apply for remote sensing or sensor networks alike. An ontology of observations must include scale or level of detail, and concepts derived from observations should carry this relation forward. A simple example: in high resolution remote sensing image agricultural plots and roads between them are shown, at lower resolution, only the plots and not the roads are visible. This gives two ontologies, one with plots and roads, the other with plots only. Note that a neighborhood relation in the two different ontologies also yield different results. References Gruber, T. (2005). "TagOntology - a way to agree on the semantics of tagging data." Retrieved October 29, 2005., from http://tomgruber.org/writing/tagontology-tagcapm-talk.pdf. Guarino, N. (1995). "Formal Ontology, Conceptual Analysis and Knowledge Representation." International Journal of Human and Computer Studies. Special Issue on Formal Ontology, Conceptual Analysis and Knowledge Representation, edited by N. Guarino and R. Poli 43(5/6). Reitsma, F. and T. Bittner (2003). Process, Hierarchy, and Scale. Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information ScienceInternational Conference

  12. A Proposition Of Knowledge Management Methodology For The Purpose Of Reasoning With The Use Of An Upper-Ontology

    Directory of Open Access Journals (Sweden)

    Kamil Szymański

    2007-01-01

    Full Text Available This article describes a proposition of knowledge organization for the purpose of reasoningusing an upper-ontology. It presents a model of integrated ontologies architecture whichconsists of a domain ontologies layer with instances, a shared upper-ontology layer withadditional rules and a layer of ontologies mapping concrete domain ontologies with the upperontology.Thanks to the upper-ontology, new facts were concluded from domain ontologiesduring the reasoning process. A practical realization proposition is given as well. It is basedon some popular SemanticWeb technologies and tools, such as OWL, SWRL, nRQL, Prot´eg´eand Racer.

  13. Gene Ontology

    Directory of Open Access Journals (Sweden)

    Gaston K. Mazandu

    2012-01-01

    Full Text Available The wide coverage and biological relevance of the Gene Ontology (GO, confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.

  14. Validating EHR clinical models using ontology patterns.

    Science.gov (United States)

    Martínez-Costa, Catalina; Schulz, Stefan

    2017-12-01

    Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. ERP profiles for face and word recognition are based on their status in semantic memory not their stimulus category.

    Science.gov (United States)

    Nie, Aiqing; Griffin, Michael; Keinath, Alexander; Walsh, Matthew; Dittmann, Andrea; Reder, Lynne

    2014-04-04

    Previous research has suggested that faces and words are processed and remembered differently as reflected by different ERP patterns for the two types of stimuli. Specifically, face stimuli produced greater late positive deflections for old items in anterior compared to posterior regions, while word stimuli produced greater late positive deflections in posterior compared to anterior regions. Given that words have existing representations in subjects׳ long-term memories (LTM) and that face stimuli used in prior experiments were of unknown individuals, we conducted an ERP study that crossed face and letter stimuli with the presence or absence of a prior (stable or existing) memory representation. During encoding, subjects judged whether stimuli were known (famous face or real word) or not known (unknown person or pseudo-word). A surprise recognition memory test required subjects to distinguish between stimuli that appeared during the encoding phase and stimuli that did not. ERP results were consistent with previous research when comparing unknown faces and words; however, the late ERP pattern for famous faces was more similar to that for words than for unknown faces. This suggests that the critical ERP difference is mediated by whether there is a prior representation in LTM, and not whether the stimulus involves letters or faces. Published by Elsevier B.V.

  16. Semantic models for adaptive interactive systems

    CERN Document Server

    Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

    2013-01-01

    Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

  17. Ontology Design of Influential People Identification Using Centrality

    Science.gov (United States)

    Maulana Awangga, Rolly; Yusril, Muhammad; Setyawan, Helmi

    2018-04-01

    Identifying influential people as a node in a graph theory commonly calculated by social network analysis. The social network data has the user as node and edge as relation forming a friend relation graph. This research is conducting different meaning of every nodes relation in the social network. Ontology was perfect match science to describe the social network data as conceptual and domain. Ontology gives essential relationship in a social network more than a current graph. Ontology proposed as a standard for knowledge representation for the semantic web by World Wide Web Consortium. The formal data representation use Resource Description Framework (RDF) and Web Ontology Language (OWL) which is strategic for Open Knowledge-Based website data. Ontology used in the semantic description for a relationship in the social network, it is open to developing semantic based relationship ontology by adding and modifying various and different relationship to have influential people as a conclusion. This research proposes a model using OWL and RDF for influential people identification in the social network. The study use degree centrality, between ness centrality, and closeness centrality measurement for data validation. As a conclusion, influential people identification in Facebook can use proposed Ontology model in the Group, Photos, Photo Tag, Friends, Events and Works data.

  18. NanoParticle Ontology for Cancer Nanotechnology Research

    Science.gov (United States)

    Thomas, Dennis G.; Pappu, Rohit V.; Baker, Nathan A.

    2010-01-01

    Data generated from cancer nanotechnology research are so diverse and large in volume that it is difficult to share and efficiently use them without informatics tools. In particular, ontologies that provide a unifying knowledge framework for annotating the data are required to facilitate the semantic integration, knowledge-based searching, unambiguous interpretation, mining and inferencing of the data using informatics methods. In this paper, we discuss the design and development of NanoParticle Ontology (NPO), which is developed within the framework of the Basic Formal Ontology (BFO), and implemented in the Ontology Web Language (OWL) using well-defined ontology design principles. The NPO was developed to represent knowledge underlying the preparation, chemical composition, and characterization of nanomaterials involved in cancer research. Public releases of the NPO are available through BioPortal website, maintained by the National Center for Biomedical Ontology. Mechanisms for editorial and governance processes are being developed for the maintenance, review, and growth of the NPO. PMID:20211274

  19. Using AberOWL for fast and scalable reasoning over BioPortal ontologies

    KAUST Repository

    Slater, Luke

    2016-08-08

    Background: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. Methods: We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. Results and conclusions: We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times.

  20. Semantic reasoning with XML-based biomedical information models.

    Science.gov (United States)

    O'Connor, Martin J; Das, Amar

    2010-01-01

    The Extensible Markup Language (XML) is increasingly being used for biomedical data exchange. The parallel growth in the use of ontologies in biomedicine presents opportunities for combining the two technologies to leverage the semantic reasoning services provided by ontology-based tools. There are currently no standardized approaches for taking XML-encoded biomedical information models and representing and reasoning with them using ontologies. To address this shortcoming, we have developed a workflow and a suite of tools for transforming XML-based information models into domain ontologies encoded using OWL. In this study, we applied semantics reasoning methods to these ontologies to automatically generate domain-level inferences. We successfully used these methods to develop semantic reasoning methods for information models in the HIV and radiological image domains.

  1. Developing an Ontology for Ocean Biogeochemistry Data

    Science.gov (United States)

    Chandler, C. L.; Allison, M. D.; Groman, R. C.; West, P.; Zednik, S.; Maffei, A. R.

    2010-12-01

    Semantic Web technologies offer great promise for enabling new and better scientific research. However, significant challenges must be met before the promise of the Semantic Web can be realized for a discipline as diverse as oceanography. Evolving expectations for open access to research data combined with the complexity of global ecosystem science research themes present a significant challenge, and one that is best met through an informatics approach. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is funded by the National Science Foundation Division of Ocean Sciences to work with ocean biogeochemistry researchers to improve access to data resulting from their respective programs. In an effort to improve data access, BCO-DMO staff members are collaborating with researchers from the Tetherless World Constellation (Rensselaer Polytechnic Institute) to develop an ontology that formally describes the concepts and relationships in the data managed by the BCO-DMO. The project required transforming a legacy system of human-readable, flat files of metadata to well-ordered controlled vocabularies to a fully developed ontology. To improve semantic interoperability, terms from the BCO-DMO controlled vocabularies are being mapped to controlled vocabulary terms adopted by other oceanographic data management organizations. While the entire process has proven to be difficult, time-consuming and labor-intensive, the work has been rewarding and is a necessary prerequisite for the eventual incorporation of Semantic Web tools. From the beginning of the project, development of the ontology has been guided by a use case based approach. The use cases were derived from data access related requests received from members of the research community served by the BCO-DMO. The resultant ontology satisfies the requirements of the use cases and reflects the information stored in the metadata database. The BCO-DMO metadata database currently contains information that

  2. Towards an “Internet of Food”: Food Ontologies for the Internet of Things

    Directory of Open Access Journals (Sweden)

    Maged N. Kamel Boulos

    2015-10-01

    Full Text Available Automated food and drink recognition methods connect to cloud-based lookup databases (e.g., food item barcodes, previously identified food images, or previously classified NIR (Near Infrared spectra of food and drink items databases to match and identify a scanned food or drink item, and report the results back to the user. However, these methods remain of limited value if we cannot further reason with the identified food and drink items, ingredients and quantities/portion sizes in a proposed meal in various contexts; i.e., understand from a semantic perspective their types, properties, and interrelationships in the context of a given user’s health condition and preferences. In this paper, we review a number of “food ontologies”, such as the Food Products Ontology/FOODpedia (by Kolchin and Zamula, Open Food Facts (by Gigandet et al., FoodWiki (Ontology-driven Mobile Safe Food Consumption System by Celik, FOODS-Diabetes Edition (A Food-Oriented Ontology-Driven System by Snae Namahoot and Bruckner, and AGROVOC multilingual agricultural thesaurus (by the UN Food and Agriculture Organization—FAO. These food ontologies, with appropriate modifications (or as a basis, to be added to and further expanded and together with other relevant non-food ontologies (e.g., about diet-sensitive disease conditions, can supplement the aforementioned lookup databases to enable progression from the mere automated identification of food and drinks in our meals to a more useful application whereby we can automatically reason with the identified food and drink items and their details (quantities and ingredients/bromatological composition in order to better assist users in making the correct, healthy food and drink choices for their particular health condition, age, body weight/BMI (Body Mass Index, lifestyle and preferences, etc.

  3. Development of National Map ontologies for organization and orchestration of hydrologic observations

    Science.gov (United States)

    Lieberman, J. E.

    2014-12-01

    Feature layers in the National Map program (TNM) are a fundamental context for much of the data collection and analysis conducted by the USGS and other governmental and nongovernmental organizations. Their computational usefulness, though, has been constrained by the lack of formal relationships besides superposition between TNM layers, as well as limited means of representing how TNM datasets relate to additional attributes, datasets, and activities. In the field of Geospatial Information Science, there has been a growing recognition of the value of semantic representation and technology for addressing these limitations, particularly in the face of burgeoning information volume and heterogeneity. Fundamental to this approach is the development of formal ontologies for concepts related to that information that can be processed computationally to enhance creation and discovery of new geospatial knowledge. They offer a means of making much of the presently innate knowledge about relationships in and between TNM features accessible for machine processing and distributed computation.A full and comprehensive ontology of all knowledge represented by TNM features is still impractical. The work reported here involves elaboration and integration of a number of small ontology design patterns (ODP's) that represent limited, discrete, but commonly accepted and broadly applicable physical theories for the behavior of TNM features representing surface water bodies and landscape surfaces and the connections between them. These ontology components are validated through use in applications for discovery and aggregation of water science observational data associated with National Hydrography Data features, features from the National Elevation Dataset (NED) and Water Boundary Dataset (WBD) that constrain water occurrence in the continental US. These applications emphasize workflows which are difficult or impossible to automate using existing data structures. Evaluation of the

  4. KneeTex: an ontology-driven system for information extraction from MRI reports.

    Science.gov (United States)

    Spasić, Irena; Zhao, Bo; Jones, Christopher B; Button, Kate

    2015-01-01

    In the realm of knee pathology, magnetic resonance imaging (MRI) has the advantage of visualising all structures within the knee joint, which makes it a valuable tool for increasing diagnostic accuracy and planning surgical treatments. Therefore, clinical narratives found in MRI reports convey valuable diagnostic information. A range of studies have proven the feasibility of natural language processing for information extraction from clinical narratives. However, no study focused specifically on MRI reports in relation to knee pathology, possibly due to the complexity of knee anatomy and a wide range of conditions that may be associated with different anatomical entities. In this paper we describe KneeTex, an information extraction system that operates in this domain. As an ontology-driven information extraction system, KneeTex makes active use of an ontology to strongly guide and constrain text analysis. We used automatic term recognition to facilitate the development of a domain-specific ontology with sufficient detail and coverage for text mining applications. In combination with the ontology, high regularity of the sublanguage used in knee MRI reports allowed us to model its processing by a set of sophisticated lexico-semantic rules with minimal syntactic analysis. The main processing steps involve named entity recognition combined with coordination, enumeration, ambiguity and co-reference resolution, followed by text segmentation. Ontology-based semantic typing is then used to drive the template filling process. We adopted an existing ontology, TRAK (Taxonomy for RehAbilitation of Knee conditions), for use within KneeTex. The original TRAK ontology expanded from 1,292 concepts, 1,720 synonyms and 518 relationship instances to 1,621 concepts, 2,550 synonyms and 560 relationship instances. This provided KneeTex with a very fine-grained lexico-semantic knowledge base, which is highly attuned to the given sublanguage. Information extraction results were evaluated

  5. Unintended consequences of existential quantifications in biomedical ontologies

    Directory of Open Access Journals (Sweden)

    Boeker Martin

    2011-11-01

    Full Text Available Abstract Background The Open Biomedical Ontologies (OBO Foundry is a collection of freely available ontologically structured controlled vocabularies in the biomedical domain. Most of them are disseminated via both the OBO Flatfile Format and the semantic web format Web Ontology Language (OWL, which draws upon formal logic. Based on the interpretations underlying OWL description logics (OWL-DL semantics, we scrutinize the OWL-DL releases of OBO ontologies to assess whether their logical axioms correspond to the meaning intended by their authors. Results We analyzed ontologies and ontology cross products available via the OBO Foundry site http://www.obofoundry.org for existential restrictions (someValuesFrom, from which we examined a random sample of 2,836 clauses. According to a rating done by four experts, 23% of all existential restrictions in OBO Foundry candidate ontologies are suspicious (Cohens' κ = 0.78. We found a smaller proportion of existential restrictions in OBO Foundry cross products are suspicious, but in this case an accurate quantitative judgment is not possible due to a low inter-rater agreement (κ = 0.07. We identified several typical modeling problems, for which satisfactory ontology design patterns based on OWL-DL were proposed. We further describe several usability issues with OBO ontologies, including the lack of ontological commitment for several common terms, and the proliferation of domain-specific relations. Conclusions The current OWL releases of OBO Foundry (and Foundry candidate ontologies contain numerous assertions which do not properly describe the underlying biological reality, or are ambiguous and difficult to interpret. The solution is a better anchoring in upper ontologies and a restriction to relatively few, well defined relation types with given domain and range constraints.

  6. High Performance Descriptive Semantic Analysis of Semantic Graph Databases

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

    2011-06-02

    As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

  7. Designing learning management system interoperability in semantic web

    Science.gov (United States)

    Anistyasari, Y.; Sarno, R.; Rochmawati, N.

    2018-01-01

    The extensive adoption of learning management system (LMS) has set the focus on the interoperability requirement. Interoperability is the ability of different computer systems, applications or services to communicate, share and exchange data, information, and knowledge in a precise, effective and consistent way. Semantic web technology and the use of ontologies are able to provide the required computational semantics and interoperability for the automation of tasks in LMS. The purpose of this study is to design learning management system interoperability in the semantic web which currently has not been investigated deeply. Moodle is utilized to design the interoperability. Several database tables of Moodle are enhanced and some features are added. The semantic web interoperability is provided by exploited ontology in content materials. The ontology is further utilized as a searching tool to match user’s queries and available courses. It is concluded that LMS interoperability in Semantic Web is possible to be performed.

  8. An Ontology-Based Framework for Modeling User Behavior

    DEFF Research Database (Denmark)

    Razmerita, Liana

    2011-01-01

    and classifies its users according to their behavior. The user ontology is the backbone of OntobUMf and has been designed according to the Information Management System Learning Information Package (IMS LIP). The user ontology includes a Behavior concept that extends IMS LIP specification and defines...... characteristics of the users interacting with the system. Concrete examples of how OntobUMf is used in the context of a Knowledge Management (KM) System are provided. This paper discusses some of the implications of ontology-based user modeling for semantically enhanced KM and, in particular, for personal KM....... The results of this research may contribute to the development of other frameworks for modeling user behavior, other semantically enhanced user modeling frameworks, or other semantically enhanced information systems....

  9. Ontologies and Formation Spaces for Conceptual ReDesign of Systems

    Directory of Open Access Journals (Sweden)

    J. Bíla

    2005-01-01

    Full Text Available This paper discusses ontologies, methods for developing them and languages for representing them. A special ontology for computational support of the Conceptual ReDesign Process (CRDP is introduced with a simple illustrative example of an application. The ontology denoted as Global context (GLB combines features of general semantic networks and features of UML language. The ontology is task-oriented and domain-oriented, and contains three basic strata – GLBExpl(stratum of Explanation, GLBFAct (stratum of Fields of Activities and GLBEnv (stratum of Environment, with their sub-strata. The ontology has been developed to represent functions of systems and their components in CRDP. The main difference between this ontology and ontologies which have been developed to identify functions (the semantic details in those ontologies must be as deep as possible is in the style of the description of the functions. In the proposed ontology, Formation Spaces were used as lower semantic categories the semantic deepness of which is variable and depends on the actual solution approach of a specialised Conceptual Designer.

  10. An approach to define semantics for BPM systems interoperability

    Science.gov (United States)

    Rico, Mariela; Caliusco, María Laura; Chiotti, Omar; Rosa Galli, María

    2015-04-01

    This article proposes defining semantics for Business Process Management systems interoperability through the ontology of Electronic Business Documents (EBD) used to interchange the information required to perform cross-organizational processes. The semantic model generated allows aligning enterprise's business processes to support cross-organizational processes by matching the business ontology of each business partner with the EBD ontology. The result is a flexible software architecture that allows dynamically defining cross-organizational business processes by reusing the EBD ontology. For developing the semantic model, a method is presented, which is based on a strategy for discovering entity features whose interpretation depends on the context, and representing them for enriching the ontology. The proposed method complements ontology learning techniques that can not infer semantic features not represented in data sources. In order to improve the representation of these entity features, the method proposes using widely accepted ontologies, for representing time entities and relations, physical quantities, measurement units, official country names, and currencies and funds, among others. When the ontologies reuse is not possible, the method proposes identifying whether that feature is simple or complex, and defines a strategy to be followed. An empirical validation of the approach has been performed through a case study.

  11. The Development of Ontology from Multiple Databases

    Science.gov (United States)

    Kasim, Shahreen; Aswa Omar, Nurul; Fudzee, Mohd Farhan Md; Azhar Ramli, Azizul; Aizi Salamat, Mohamad; Mahdin, Hairulnizam

    2017-08-01

    The area of halal industry is the fastest growing global business across the world. The halal food industry is thus crucial for Muslims all over the world as it serves to ensure them that the food items they consume daily are syariah compliant. Currently, ontology has been widely used in computer sciences area such as web on the heterogeneous information processing, semantic web, and information retrieval. However, ontology has still not been used widely in the halal industry. Today, Muslim community still have problem to verify halal status for products in the market especially foods consisting of E number. This research tried to solve problem in validating the halal status from various halal sources. There are various chemical ontology from multilple databases found to help this ontology development. The E numbers in this chemical ontology are codes for chemicals that can be used as food additives. With this E numbers ontology, Muslim community could identify and verify the halal status effectively for halal products in the market.

  12. Ontology Maintenance using Textual Analysis

    Directory of Open Access Journals (Sweden)

    Yassine Gargouri

    2003-10-01

    Full Text Available Ontologies are continuously confronted to evolution problem. Due to the complexity of the changes to be made, a maintenance process, at least a semi-automatic one, is more and more necessary to facilitate this task and to ensure its reliability. In this paper, we propose a maintenance ontology model for a domain, whose originality is to be language independent and based on a sequence of text processing in order to extract highly related terms from corpus. Initially, we deploy the document classification technique using GRAMEXCO to generate classes of texts segments having a similar information type and identify their shared lexicon, agreed as highly related to a unique topic. This technique allows a first general and robust exploration of the corpus. Further, we apply the Latent Semantic Indexing method to extract from this shared lexicon, the most associated terms that has to be seriously considered by an expert to eventually confirm their relevance and thus updating the current ontology. Finally, we show how the complementarity between these two techniques, based on cognitive foundation, constitutes a powerful refinement process.

  13. An ontology for human-like interaction systems

    OpenAIRE

    Albacete García, Esperanza

    2016-01-01

    This report proposes and describes the development of a Ph.D. Thesis aimed at building an ontological knowledge model supporting Human-Like Interaction systems. The main function of such knowledge model in a human-like interaction system is to unify the representation of each concept, relating it to the appropriate terms, as well as to other concepts with which it shares semantic relations. When developing human-like interactive systems, the inclusion of an ontological module can be valuab...

  14. An Iterative and Incremental Approach for E-Learning Ontology Engineering

    Directory of Open Access Journals (Sweden)

    Sudath Rohitha Heiyanthuduwage

    2009-03-01

    Full Text Available Abstract - There is a boost in the interest on ontology with the developments in Semantic Web technologies. Ontologies play a vital role in semantic web. Even though there is lot of work done on ontology, still a standard framework for ontology engineering has not been defined. Even though current ontology engineering methodologies are available they need improvements. The effort of our work is to integrate various methods, techniques, tools and etc to different stages of proposed ontology engineering life cycle to create a comprehensive framework for ontology engineering. Current methodologies discuss ontology engineering stages and collaborative environments with user collaboration. However, discussion on increasing effectiveness and correct inference has been given less attention. More over, these methodologies provide little discussion on usability of domain ontologies. We consider these aspects as more important in our work. Also, ontology engineering has been done for various domains and for various purposes. Our effort is to propose an iterative and incremental approach for ontology engineering especially for e-learning domain with the intention of achieving a higher usability and effectiveness of e-learning systems. This paper introduces different aspects of the proposed ontology engineering framework and evaluation of it.

  15. Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.

    Science.gov (United States)

    Harrow, Ian; Jiménez-Ruiz, Ernesto; Splendiani, Andrea; Romacker, Martin; Woollard, Peter; Markel, Scott; Alam-Faruque, Yasmin; Koch, Martin; Malone, James; Waaler, Arild

    2017-12-02

    The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.

  16. IfcOWL: A case of transforming EXPRESS schemas into ontologies

    NARCIS (Netherlands)

    Beetz, J.; Leeuwen, van J.P.; Vries, de B.

    2009-01-01

    Ontologies have been successfully applied as a semantic enabler of communication between both users and applications in fragmented, heterogeneous multinational business environments. In this paper we discuss the underlying principles, their current implementation status, and most importantly, their

  17. An ontology for major histocompatibility restriction.

    Science.gov (United States)

    Vita, Randi; Overton, James A; Seymour, Emily; Sidney, John; Kaufman, Jim; Tallmadge, Rebecca L; Ellis, Shirley; Hammond, John; Butcher, Geoff W; Sette, Alessandro; Peters, Bjoern

    2016-01-01

    MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in a specific immune recognition context. No consistent nomenclature exists across different vertebrate species. To correctly represent MHC related data in The Immune Epitope Database (IEDB), we built upon a previously established MHC ontology and created an ontology to represent MHC molecules as they relate to immunological experiments. This ontology models MHC protein chains from 16 species, deals with different approaches used to identify MHC, such as direct sequencing verses serotyping, relates engineered MHC molecules to naturally occurring ones, connects genetic loci, alleles, protein chains and multi-chain proteins, and establishes evidence codes for MHC restriction. Where available, this work is based on existing ontologies from the OBO foundry. Overall, representing MHC molecules provides a challenging and practically important test case for ontology building, and could serve as an example of how to integrate other ontology building efforts into web resources.

  18. Semantic Multimedia

    NARCIS (Netherlands)

    S. Staab; A. Scherp; R. Arndt; R. Troncy (Raphael); M. Grzegorzek; C. Saathoff; S. Schenk; L. Hardman (Lynda)

    2008-01-01

    htmlabstractMultimedia constitutes an interesting field of application for Semantic Web and Semantic Web reasoning, as the access and management of multimedia content and context depends strongly on the semantic descriptions of both. At the same time, multimedia resources constitute complex objects,

  19. Generative Semantics.

    Science.gov (United States)

    King, Margaret

    The first section of this paper deals with the attempts within the framework of transformational grammar to make semantics a systematic part of linguistic description, and outlines the characteristics of the generative semantics position. The second section takes a critical look at generative semantics in its later manifestations, and makes a case…

  20. A UML profile for the OBO relation ontology

    Science.gov (United States)

    2012-01-01

    intuitive form of capturing and representing knowledge than using only text-based notations. The use of the profile requires the domain expert to reason about the underlying semantics of the concepts and relationships being modeled, which helps preventing the introduction of inconsistencies in an ontology under development and facilitates the identification and correction of errors in an already defined ontology. PMID:23095840

  1. Matching biomedical ontologies based on formal concept analysis.

    Science.gov (United States)

    Zhao, Mengyi; Zhang, Songmao; Li, Weizhuo; Chen, Guowei

    2018-03-19

    The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. This motivates the study in this paper, i.e., to empower FCA with as much as ontological knowledge as possible for identifying mappings across ontologies. We propose a method based on Formal Concept Analysis to identify and validate mappings across ontologies, including one-to-one mappings, complex mappings and correspondences between object properties. Our method, called FCA-Map, incrementally generates a total of five types of formal contexts and extracts mappings from the lattices derived. First, the token-based formal context describes how class names, labels and synonyms share lexical tokens, leading to lexical mappings (anchors) across ontologies. Second, the relation-based formal context describes how classes are in taxonomic, partonomic and disjoint relationships with the anchors, leading to positive and negative structural evidence for validating the lexical matching. Third, the positive relation-based context can be used to discover structural mappings. Afterwards, the property-based formal context describes how object properties are used in axioms to connect anchor classes across ontologies, leading to property mappings. Last, the restriction-based formal context describes co-occurrence of classes across ontologies in anonymous ancestors of anchors, from which extended structural mappings and complex mappings can be identified. Evaluation on the Anatomy, the Large Biomedical Ontologies, and the Disease and Phenotype track of the 2016 Ontology Alignment Evaluation Initiative campaign

  2. Application of Pareto optimization method for ontology matching in nuclear reactor domain

    International Nuclear Information System (INIS)

    Meenachi, N. Madurai; Baba, M. Sai

    2017-01-01

    This article describes the need for ontology matching and describes the methods to achieve the same. Efforts are put in the implementation of the semantic web based knowledge management system for nuclear domain which necessitated use of the methods for development of ontology matching. In order to exchange information in a distributed environment, ontology mapping has been used. The constraints in matching the ontology are also discussed. Pareto based ontology matching algorithm is used to find the similarity between two ontologies in the nuclear reactor domain. Algorithms like Jaro Winkler distance, Needleman Wunsch algorithm, Bigram, Kull Back and Cosine divergence are employed to demonstrate ontology matching. A case study was carried out to analysis the ontology matching in diversity in the nuclear reactor domain and same was illustrated.

  3. DeMO: An Ontology for Discrete-event Modeling and Simulation

    Science.gov (United States)

    Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

    2011-01-01

    Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

  4. Application of Pareto optimization method for ontology matching in nuclear reactor domain

    Energy Technology Data Exchange (ETDEWEB)

    Meenachi, N. Madurai [Indira Gandhi Centre for Atomic Research, HBNI, Tamil Nadu (India). Planning and Human Resource Management Div.; Baba, M. Sai [Indira Gandhi Centre for Atomic Research, HBNI, Tamil Nadu (India). Resources Management Group

    2017-12-15

    This article describes the need for ontology matching and describes the methods to achieve the same. Efforts are put in the implementation of the semantic web based knowledge management system for nuclear domain which necessitated use of the methods for development of ontology matching. In order to exchange information in a distributed environment, ontology mapping has been used. The constraints in matching the ontology are also discussed. Pareto based ontology matching algorithm is used to find the similarity between two ontologies in the nuclear reactor domain. Algorithms like Jaro Winkler distance, Needleman Wunsch algorithm, Bigram, Kull Back and Cosine divergence are employed to demonstrate ontology matching. A case study was carried out to analysis the ontology matching in diversity in the nuclear reactor domain and same was illustrated.

  5. Comprehensive Analysis of Semantic Web Reasoners and Tools: A Survey

    Science.gov (United States)

    Khamparia, Aditya; Pandey, Babita

    2017-01-01

    Ontologies are emerging as best representation techniques for knowledge based context domains. The continuing need for interoperation, collaboration and effective information retrieval has lead to the creation of semantic web with the help of tools and reasoners which manages personalized information. The future of semantic web lies in an ontology…

  6. The methodology of semantic analysis for extracting physical effects

    Science.gov (United States)

    Fomenkova, M. A.; Kamaev, V. A.; Korobkin, D. M.; Fomenkov, S. A.

    2017-01-01

    The paper represents new methodology of semantic analysis for physical effects extracting. This methodology is based on the Tuzov ontology that formally describes the Russian language. In this paper, semantic patterns were described to extract structural physical information in the form of physical effects. A new algorithm of text analysis was described.

  7. CoordSS: An Ontology Framework for Heterogeneous Networks Experimentation

    Directory of Open Access Journals (Sweden)

    V. Nejkovic

    2016-11-01

    Full Text Available Experimenting with HetNets environments is of importance because of the role that such environments have in next-generation cellular networks. In this paper, the CoordSS ontology experimentation framework is proposed with an aim to support experimenting with HetNets environments on wireless networking testbeds. In the framework, domain and system ontologies are adopted for formal representation of the knowledge about the context of the problem. This paper outlines implementation details of ontologies in the CoordSS experimentation framework. The synergy between semantic and cognitive computing is introduced as the theoretical foundation of the paper.

  8. The use of ontologies in the spatial planning domain

    CSIR Research Space (South Africa)

    Kaczmarek, I

    2011-07-01

    Full Text Available are based on RDF (Resource Description Framework) and RDFS (Resource Description Framework Schema) model. A CLOSER LOOK The description of datasets and the objects contained therein using ontologies is a way of representing knowledge about space. Having... of these data. The added value here is that knowledge can be derived. INTRODUCTION TO ONTOLOGIES Ontologies are considered to be a core element of the Semantic Web, which is defined as ?the extension of the World Wide Web that enables people to share content...

  9. Application of Ontology Technology in Health Statistic Data Analysis.

    Science.gov (United States)

    Guo, Minjiang; Hu, Hongpu; Lei, Xingyun

    2017-01-01

    Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, and used protégé to define the syntactic and semantic structure of health statistical data. six classes of top-level ontology concepts and their subclasses had been extracted and the object properties and data properties were defined to establish the construction of these classes. By ontology instantiation, we can integrate multi-source heterogeneous data and enable administrators to have an overall understanding and analysis of the health statistic data. ontology technology provides a comprehensive and unified information integration structure of the health management domain and lays a foundation for the efficient analysis of multi-source and heterogeneous health system management data and enhancement of the management efficiency.

  10. The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

    Science.gov (United States)

    Yang, Wang-Dong; Wang, Tao

    On these issues unified representation of urban transport information using urban transport ontology, it defines the statute and the algebraic operations of semantic fusion in ontology level in order to achieve the fusion of urban traffic information in the semantic completeness and consistency. Thus this paper takes advantage of the semantic completeness of the ontology to build urban traffic ontology model with which we resolve the problems as ontology mergence and equivalence verification in semantic fusion of traffic information integration. Information integration in urban transport can increase the function of semantic fusion, and reduce the amount of data integration of urban traffic information as well enhance the efficiency and integrity of traffic information query for the help, through the practical application of intelligent traffic information integration platform of Changde city, the paper has practically proved that the semantic fusion based on ontology increases the effect and efficiency of the urban traffic information integration, reduces the storage quantity, and improve query efficiency and information completeness.

  11. Toward a general ontology for digital forensic disciplines.

    Science.gov (United States)

    Karie, Nickson M; Venter, Hein S

    2014-09-01

    Ontologies are widely used in different disciplines as a technique for representing and reasoning about domain knowledge. However, despite the widespread ontology-related research activities and applications in different disciplines, the development of ontologies and ontology research activities is still wanting in digital forensics. This paper therefore presents the case for establishing an ontology for digital forensic disciplines. Such an ontology would enable better categorization of the digital forensic disciplines, as well as assist in the development of methodologies and specifications that can offer direction in different areas of digital forensics. This includes such areas as professional specialization, certifications, development of digital forensic tools, curricula, and educational materials. In addition, the ontology presented in this paper can be used, for example, to better organize the digital forensic domain knowledge and explicitly describe the discipline's semantics in a common way. Finally, this paper is meant to spark discussions and further research on an internationally agreed ontological distinction of the digital forensic disciplines. Digital forensic disciplines ontology is a novel approach toward organizing the digital forensic domain knowledge and constitutes the main contribution of this paper. © 2014 American Academy of Forensic Sciences.

  12. Ontology Alignment Repair through Modularization and Confidence-Based Heuristics.

    Directory of Open Access Journals (Sweden)

    Emanuel Santos

    Full Text Available Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of repair techniques to improve the coherence of ontology alignments began to be explored. This paper presents a novel modularization technique for ontology alignment repair which extracts fragments of the input ontologies that only contain the necessary classes and relations to resolve all detectable incoherences. The paper presents also an alignment repair algorithm that uses a global repair strategy to minimize both the degree of incoherence and the number of mappings removed from the alignment, while overcoming the scalability problem by employing the proposed modularization technique. Our evaluation shows that our modularization technique produces significantly small fragments of the ontologies and that our repair algorithm produces more complete alignments than other current alignment repair systems, while obtaining an equivalent degree of incoherence. Additionally, we also present a variant of our repair algorithm that makes use of the confidence values of the mappings to improve alignment repair. Our repair algorithm was implemented as part of AgreementMakerLight, a free and open-source ontology matching system.

  13. Ontology Alignment Repair through Modularization and Confidence-Based Heuristics.

    Science.gov (United States)

    Santos, Emanuel; Faria, Daniel; Pesquita, Catia; Couto, Francisco M

    2015-01-01

    Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of repair techniques to improve the coherence of ontology alignments began to be explored. This paper presents a novel modularization technique for ontology alignment repair which extracts fragments of the input ontologies that only contain the necessary classes and relations to resolve all detectable incoherences. The paper presents also an alignment repair algorithm that uses a global repair strategy to minimize both the degree of incoherence and the number of mappings removed from the alignment, while overcoming the scalability problem by employing the proposed modularization technique. Our evaluation shows that our modularization technique produces significantly small fragments of the ontologies and that our repair algorithm produces more complete alignments than other current alignment repair systems, while obtaining an equivalent degree of incoherence. Additionally, we also present a variant of our repair algorithm that makes use of the confidence values of the mappings to improve alignment repair. Our repair algorithm was implemented as part of AgreementMakerLight, a free and open-source ontology matching system.

  14. Knowledge Representation in Patient Safety Reporting: An Ontological Approach

    Directory of Open Access Journals (Sweden)

    Liang Chen

    2016-10-01

    Full Text Available Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/methodology/approach: We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our design, implementation, and evaluation of the ontology at its initial stage. Findings: We describe the design and initial outcomes of the ontology implementation. The evaluation results demonstrate the clinical validity of the ontology by a self-developed survey measurement. Research limitations: The proposed ontology was developed and evaluated using a small number of information sources. Presently, US data are used, but they are not essential for the ultimate structure of the ontology. Practical implications: The goal of improving patient safety can be aided through investigating patient safety reports and providing actionable knowledge to clinical practitioners. As such, constructing a domain specific ontology for patient safety reports serves as a cornerstone in information collection and text mining methods. Originality/value: The use of ontologies provides abstracted representation of semantic information and enables a wealth of applications in a reporting system. Therefore, constructing such a knowledge base is recognized as a high priority in health care.

  15. A Semi-Automatic Approach to Construct Vietnamese Ontology from Online Text

    Science.gov (United States)

    Nguyen, Bao-An; Yang, Don-Lin

    2012-01-01

    An ontology is an effective formal representation of knowledge used commonly in artificial intelligence, semantic web, software engineering, and information retrieval. In open and distance learning, ontologies are used as knowledge bases for e-learning supplements, educational recommenders, and question answering systems that support students with…

  16. Culto: AN Ontology-Based Annotation Tool for Data Curation in Cultural Heritage

    Science.gov (United States)

    Garozzo, R.; Murabito, F.; Santagati, C.; Pino, C.; Spampinato, C.

    2017-08-01

    This paper proposes CulTO, a software tool relying on a computational ontology for Cultural Heritage domain modelling, with a specific focus on religious historical buildings, for supporting cultural heritage experts in their investigations. It is specifically thought to support annotation, automatic indexing, classification and curation of photographic data and text documents of historical buildings. CULTO also serves as a useful tool for Historical Building Information Modeling (H-BIM) by enabling semantic 3D data modeling and further enrichment with non-geometrical information of historical buildings through the inclusion of new concepts about historical documents, images, decay or deformation evidence as well as decorative elements into BIM platforms. CulTO is the result of a joint research effort between the Laboratory of Surveying and Architectural Photogrammetry "Luigi Andreozzi" and the PeRCeiVe Lab (Pattern Recognition and Computer Vision Lab) of the University of Catania,

  17. An Ontology-based Context-aware System for Smart Homes: E-care@home

    Directory of Open Access Journals (Sweden)

    Marjan Alirezaie

    2017-07-01

    Full Text Available Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.

  18. An Ontology-based Context-aware System for Smart Homes: E-care@home.

    Science.gov (United States)

    Alirezaie, Marjan; Renoux, Jennifer; Köckemann, Uwe; Kristoffersson, Annica; Karlsson, Lars; Blomqvist, Eva; Tsiftes, Nicolas; Voigt, Thiemo; Loutfi, Amy

    2017-07-06

    Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.

  19. CULTO: AN ONTOLOGY-BASED ANNOTATION TOOL FOR DATA CURATION IN CULTURAL HERITAGE

    Directory of Open Access Journals (Sweden)

    R. Garozzo

    2017-08-01

    Full Text Available This paper proposes CulTO, a software tool relying on a computational ontology for Cultural Heritage domain modelling, with a specific focus on religious historical buildings, for supporting cultural heritage experts in their investigations. It is specifically thought to support annotation, automatic indexing, classification and curation of photographic data and text documents of historical buildings. CULTO also serves as a useful tool for Historical Building Information Modeling (H-BIM by enabling semantic 3D data modeling and further enrichment with non-geometrical information of historical buildings through the inclusion of new concepts about historical documents, images, decay or deformation evidence as well as decorative elements into BIM platforms. CulTO is the result of a joint research effort between the Laboratory of Surveying and Architectural Photogrammetry “Luigi Andreozzi” and the PeRCeiVe Lab (Pattern Recognition and Computer Vision Lab of the University of Catania,

  20. Distributed and Collaborative Knowledge Management Using an Ontology-Based System

    OpenAIRE

    Adrian , Weronika ,; Ligęza , Antoni; Nalepa , Grzegorz ,; Kaczor , Krzysztof

    2012-01-01

    International audience; Semantic annotations and formally grounded ontologies constitute flexible yet powerful methods of knowledge representation. Using them in a system allows to perform automated reasoning and can enhance the knowledge management. In the paper, we present a system for collaborative knowledge management, in which an ontology and ontological reasoning is used. The main objective of the application is to provide information for citizens about threats in an urban environment. ...

  1. Expert2OWL: A Methodology for Pattern-Based Ontology Development.

    Science.gov (United States)

    Tahar, Kais; Xu, Jie; Herre, Heinrich

    2017-01-01

    The formalization of expert knowledge enables a broad spectrum of applications employing ontologies as underlying technology. These include eLearning, Semantic Web and expert systems. However, the manual construction of such ontologies is time-consuming and thus expensive. Moreover, experts are often unfamiliar with the syntax and semantics of formal ontology languages such as OWL and usually have no experience in developing formal ontologies. To overcome these barriers, we developed a new method and tool, called Expert2OWL that provides efficient features to support the construction of OWL ontologies using GFO (General Formal Ontology) as a top-level ontology. This method allows a close and effective collaboration between ontologists and domain experts. Essentially, this tool integrates Excel spreadsheets as part of a pattern-based ontology development and refinement process. Expert2OWL enables us to expedite the development process and modularize the resulting ontologies. We applied this method in the field of Chinese Herbal Medicine (CHM) and used Expert2OWL to automatically generate an accurate Chinese Herbology ontology (CHO). The expressivity of CHO was tested and evaluated using ontology query languages SPARQL and DL. CHO shows promising results and can generate answers to important scientific questions such as which Chinese herbal formulas contain which substances, which substances treat which diseases, and which ones are the most frequently used in CHM.

  2. Assessment Applications of Ontologies.

    Science.gov (United States)

    Chung, Gregory K. W. K.; Niemi, David; Bewley, William L.

    This paper discusses the use of ontologies and their applications to assessment. An ontology provides a shared and common understanding of a domain that can be communicated among people and computational systems. The ontology captures one or more experts' conceptual representation of a domain expressed in terms of concepts and the relationships…

  3. Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

    KAUST Repository

    Alghamdi, Sarah M.

    2018-05-13

    In biomedical research, ontologies are widely used to represent knowledge as well as to annotate datasets. Many of the existing ontologies cover a single type of phenomena, such as a process, cell type, gene, pathological entity or anatomical structure. Consequently, there is a requirement to use multiple ontologies to fully characterize the observations in the datasets. Although this allows precise annotation of different aspects of a given dataset, it limits our ability to use the ontologies in data analysis, as the ontologies are usually disconnected and their combinations cannot be exploited. Motivated by this, here we present novel ontology design methods for combining pathology and anatomy concepts. To this end, we use a dataset of mouse models which has been characterized through two ontologies: one of them is the mouse pathology ontology (MPATH) covering pathological lesions while the other is the mouse anatomy ontology (MA) covering the anatomical site of the lesions. We propose four novel ontology design patterns for combining these ontologies, and use these patterns to generate four ontologies in a data-driven way. To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

  4. Experience of Developing a Meta-Semantic Search Engine

    OpenAIRE

    Mukhopadhyay, Debajyoti; Sharma, Manoj; Joshi, Gajanan; Pagare, Trupti; Palwe, Adarsha

    2013-01-01

    Thinking of todays web search scenario which is mainly keyword based, leads to the need of effective and meaningful search provided by Semantic Web. Existing search engines are vulnerable to provide relevant answers to users query due to their dependency on simple data available in web pages. On other hand, semantic search engines provide efficient and relevant results as the semantic web manages information with well defined meaning using ontology. A Meta-Search engine is a search tool that ...

  5. An Ontology Design Pattern for Surface Water Features

    Energy Technology Data Exchange (ETDEWEB)

    Sinha, Gaurav [Ohio University; Mark, David [University at Buffalo (SUNY); Kolas, Dave [Raytheon BBN Technologies; Varanka, Dalia [U.S. Geological Survey, Rolla, MO; Romero, Boleslo E [University of California, Santa Barbara; Feng, Chen-Chieh [National University of Singapore; Usery, Lynn [U.S. Geological Survey, Rolla, MO; Liebermann, Joshua [Tumbling Walls, LLC; Sorokine, Alexandre [ORNL

    2014-01-01

    Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities can be found due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology. It can then be used to systematically incor-porate concepts that are specific to a culture, language, or scientific domain. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex surface water ontologies. A fundamental distinction is made in this on-tology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is imple-mented in OWL, but Description Logic axioms and a detailed explanation is provided. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. A discussion about why there is a need to complement the pattern with other ontologies, es-pecially the previously developed Surface Network pattern is also provided. Fi-nally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through a few queries and annotated geospatial datasets.

  6. Integrating systems biology models and biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

    2011-08-11

    Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  7. A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

    Science.gov (United States)

    Möller, Manuel; Tuot, Christopher; Sintek, Michael

    In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

  8. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  9. SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.

    Science.gov (United States)

    Gessler, Damian D G; Schiltz, Gary S; May, Greg D; Avraham, Shulamit; Town, Christopher D; Grant, David; Nelson, Rex T

    2009-09-23

    SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at http://sswap.info (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at http://sswap.info/protocol.jsp, developer tools at http://sswap.info/developer.jsp, and a portal to third-party ontologies at http://sswapmeet.sswap.info (a "swap meet"). SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the

  10. GFVO: the Genomic Feature and Variation Ontology

    KAUST Repository

    Baran, Joachim

    2015-05-05

    Falling costs in genomic laboratory experiments have led to a steady increase of genomic feature and variation data. Multiple genomic data formats exist for sharing these data, and whilst they are similar, they are addressing slightly different data viewpoints and are consequently not fully compatible with each other. The fragmentation of data format specifications makes it hard to integrate and interpret data for further analysis with information from multiple data providers. As a solution, a new ontology is presented here for annotating and representing genomic feature and variation dataset contents. The Genomic Feature and Variation Ontology (GFVO) specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations. Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.

  11. Application of Alignment Methodologies to Spatial Ontologies in the Hydro Domain

    Science.gov (United States)

    Lieberman, J. E.; Cheatham, M.; Varanka, D.

    2015-12-01

    Ontologies are playing an increasing role in facilitating mediation and translation between datasets representing diverse schemas, vocabularies, or knowledge communities. This role is relatively straightforward when there is one ontology comprising all relevant common concepts that can be mapped to entities in each dataset. Frequently, one common ontology has not been agreed to. Either each dataset is represented by a distinct ontology, or there are multiple candidates for commonality. Either the one most appropriate (expressive, relevant, correct) ontology must be chosen, or else concepts and relationships matched across multiple ontologies through an alignment process so that they may be used in concert to carry out mediation or other semantic operations. A resulting alignment can be effective to the extent that entities in in the ontologies represent differing terminology for comparable conceptual knowledge. In cases such as spatial ontologies, though, ontological entities may also represent disparate conceptualizations of space according to the discernment methods and application domains on which they are based. One ontology's wetland concept may overlap in space with another ontology's recharge zone or wildlife range or water feature. In order to evaluate alignment with respect to spatial ontologies, alignment has been applied to a series of ontologies pertaining to surface water that are used variously in hydrography (characterization of water features), hydrology (study of water cycling), and water quality (nutrient and contaminant transport) application domains. There is frequently a need to mediate between datasets in each domain in order to develop broader understanding of surface water systems, so there is a practical as well theoretical value in the alignment. From a domain expertise standpoint, the ontologies under consideration clearly contain some concepts that are spatially as well as conceptually identical and then others with less clear

  12. Query Processing in Ontology-Based Peer-to-Peer Systems

    NARCIS (Netherlands)

    Stuckenschmidt, Heiner; Harmelen, Frank Van; Giunchiglia, Fausto

    2005-01-01

    The unstructured, heterogeneous and dynamic nature of the Web poses a new challenge to query-answering over multiple data sources. The so-called Semantic Web aims at providing more and semantically richer structures in terms of ontologies and meta-data. A problem that remains is the combined use of

  13. Kernel Methods for Mining Instance Data in Ontologies

    Science.gov (United States)

    Bloehdorn, Stephan; Sure, York

    The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

  14. Ontology Based Quality Evaluation for Spatial Data

    Science.gov (United States)

    Yılmaz, C.; Cömert, Ç.

    2015-08-01

    Many institutions will be providing data to the National Spatial Data Infrastructure (NSDI). Current technical background of the NSDI is based on syntactic web services. It is expected that this will be replaced by semantic web services. The quality of the data provided is important in terms of the decision-making process and the accuracy of transactions. Therefore, the data quality needs to be tested. This topic has been neglected in Turkey. Data quality control for NSDI may be done by private or public "data accreditation" institutions. A methodology is required for data quality evaluation. There are studies for data quality including ISO standards, academic studies and software to evaluate spatial data quality. ISO 19157 standard defines the data quality elements. Proprietary software such as, 1Spatial's 1Validate and ESRI's Data Reviewer offers quality evaluation based on their own classification of rules. Commonly, rule based approaches are used for geospatial data quality check. In this study, we look for the technical components to devise and implement a rule based approach with ontologies using free and open source software in semantic web context. Semantic web uses ontologies to deliver well-defined web resources and make them accessible to end-users and processes. We have created an ontology conforming to the geospatial data and defined some sample rules to show how to test data with respect to data quality elements including; attribute, topo-semantic and geometrical consistency using free and open source software. To test data against rules, sample GeoSPARQL queries are created, associated with specifications.

  15. Ontology-Based e-Assessment for Accounting Education

    Science.gov (United States)

    Litherland, Kate; Carmichael, Patrick; Martínez-García, Agustina

    2013-01-01

    This summary reports on a pilot of a novel, ontology-based e-assessment system in accounting. The system, OeLe, uses emerging semantic technologies to offer an online assessment environment capable of marking students' free text answers to questions of a conceptual nature. It does this by matching their response with a "concept map" or…

  16. SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

    Science.gov (United States)

    Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

    2014-01-01

    We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

  17. Fast gene ontology based clustering for microarray experiments.

    Science.gov (United States)

    Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

    2008-11-21

    Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  18. Physical properties of biological entities: an introduction to the ontology of physics for biology.

    Directory of Open Access Journals (Sweden)

    Daniel L Cook

    Full Text Available As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB, a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration.

  19. Physical properties of biological entities: an introduction to the ontology of physics for biology.

    Science.gov (United States)

    Cook, Daniel L; Bookstein, Fred L; Gennari, John H

    2011-01-01

    As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB), a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration. © 2011 Cook et al.

  20. The Proteasix Ontology.

    Science.gov (United States)

    Arguello Casteleiro, Mercedes; Klein, Julie; Stevens, Robert

    2016-06-04

    The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of proteolytic cleavage fragments (peptides) The PxO re-uses parts of the Protein Ontology, the three Gene Ontology sub-ontologies, the Chemical Entities of Biological Interest Ontology, the Sequence Ontology and bespoke extensions to the PxO in support of a series of roles: 1. To describe the known proteases and their target cleaveage sites. 2. To enable the description of proteolytic cleaveage fragments as the outputs of observed and predicted proteolysis. 3. To use knowledge about the function, species and cellular location of a protease and protein substrate to support the prioritisation of proteases in observed and predicted proteolysis. The PxO is designed to describe the biological underpinnings of the generation of peptides. The peptide-centric PxO seeks to support the Proteasix tool by separating domain knowledge from the operational knowledge used in protease prediction by Proteasix and to support the confirmation of its analyses and results. The Proteasix Ontology may be found at: http://bioportal.bioontology.org/ontologies/PXO . This ontology is free and open for use by everyone.

  1. Benchmarking the Applicability of Ontology in Geographic Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Sachit Rajbhandari

    2017-11-01

    Full Text Available In Geographic Object-based Image Analysis (GEOBIA, identification of image objects is normally achieved using rule-based classification techniques supported by appropriate domain knowledge. However, GEOBIA currently lacks a systematic method to formalise the domain knowledge required for image object identification. Ontology provides a representation vocabulary for characterising domain-specific classes. This study proposes an ontological framework that conceptualises domain knowledge in order to support the application of rule-based classifications. The proposed ontological framework is tested with a landslide case study. The Web Ontology Language (OWL is used to construct an ontology in the landslide domain. The segmented image objects with extracted features are incorporated into the ontology as instances. The classification rules are written in Semantic Web Rule Language (SWRL and executed using a semantic reasoner to assign instances to appropriate landslide classes. Machine learning techniques are used to predict new threshold values for feature attributes in the rules. Our framework is compared with published work on landslide detection where ontology was not used for the image classification. Our results demonstrate that a classification derived from the ontological framework accords with non-ontological methods. This study benchmarks the ontological method providing an alternative approach for image classification in the case study of landslides.

  2. HuPSON: the human physiology simulation ontology.

    Science.gov (United States)

    Gündel, Michaela; Younesi, Erfan; Malhotra, Ashutosh; Wang, Jiali; Li, Hui; Zhang, Bijun; de Bono, Bernard; Mevissen, Heinz-Theodor; Hofmann-Apitius, Martin

    2013-11-22

    Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate the exchange of information, of data and of models. Hindering these initiatives is a lack of a comprehensive ontology that covers the essential concepts of the simulation domain. We propose a first version of a newly constructed ontology, HuPSON, as a basis for shared semantics and interoperability of simulations, of models, of algorithms and of other resources in this domain. The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles; the constructed ontology has been evaluated via structural features, competency questions and use case scenarios.The ontology is freely available at: http://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads.html (owl files) and http://bishop.scai.fraunhofer.de/scaiview/ (browser). HuPSON provides a framework for a) annotating simulation experiments, b) retrieving relevant information that are required for modelling, c) enabling interoperability of algorithmic approaches used in biomedical simulation, d) comparing simulation results and e) linking knowledge-based approaches to simulation-based approaches. It is meant to foster a more rapid uptake of semantic technologies in the modelling and simulation domain, with particular focus on the VPH domain.

  3. A Process for the Representation of openEHR ADL Archetypes in OWL Ontologies.

    Science.gov (United States)

    Porn, Alex Mateus; Peres, Leticia Mara; Didonet Del Fabro, Marcos

    2015-01-01

    ADL is a formal language to express archetypes, independent of standards or domain. However, its specification is not precise enough in relation to the specialization and semantic of archetypes, presenting difficulties in implementation and a few available tools. Archetypes may be implemented using other languages such as XML or OWL, increasing integration with Semantic Web tools. Exchanging and transforming data can be better implemented with semantics oriented models, for example using OWL which is a language to define and instantiate Web ontologies defined by W3C. OWL permits defining significant, detailed, precise and consistent distinctions among classes, properties and relations by the user, ensuring the consistency of knowledge than using ADL techniques. This paper presents a process of an openEHR ADL archetypes representation in OWL ontologies. This process consists of ADL archetypes conversion in OWL ontologies and validation of OWL resultant ontologies using the mutation test.

  4. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    Science.gov (United States)

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-08-03

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  5. A Semantic Approach with Decision Support for Safety Service in Smart Home Management

    Directory of Open Access Journals (Sweden)

    Xiaoci Huang

    2016-08-01

    Full Text Available Research on smart homes (SHs has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  6. The EDEN-IW ontology model for sharing knowledge and water quality data between heterogenous databases

    DEFF Research Database (Denmark)

    Stjernholm, M.; Poslad, S.; Zuo, L.

    2004-01-01

    The Environmental Data Exchange Network for Inland Water (EDEN-IW) project's main aim is to develop a system for making disparate and heterogeneous databases of Inland Water quality more accessible to users. The core technology is based upon a combination of: ontological model to represent...... a Semantic Web based data model for IW; software agents as an infrastructure to share and reason about the IW se-mantic data model and XML to make the information accessible to Web portals and mainstream Web services. This presentation focuses on the Semantic Web or Onto-logical model. Currently, we have...

  7. Development and Evaluation of an Ontology for Guiding Appropriate Antibiotic Prescribing

    Science.gov (United States)

    Furuya, E. Yoko; Kuperman, Gilad J.; Cimino, James J.; Bakken, Suzanne

    2011-01-01

    Objectives To develop and apply formal ontology creation methods to the domain of antimicrobial prescribing and to formally evaluate the resulting ontology through intrinsic and extrinsic evaluation studies. Methods We extended existing ontology development methods to create the ontology and implemented the ontology using Protégé-OWL. Correctness of the ontology was assessed using a set of ontology design principles and domain expert review via the laddering technique. We created three artifacts to support the extrinsic evaluation (set of prescribing rules, alerts and an ontology-driven alert module, and a patient database) and evaluated the usefulness of the ontology for performing knowledge management tasks to maintain the ontology and for generating alerts to guide antibiotic prescribing. Results The ontology includes 199 classes, 10 properties, and 1,636 description logic restrictions. Twenty-three Semantic Web Rule Language rules were written to generate three prescribing alerts: 1) antibiotic-microorganism mismatch alert; 2) medication-allergy alert; and 3) non-recommended empiric antibiotic therapy alert. The evaluation studies confirmed the correctness of the ontology, usefulness of the ontology for representing and maintaining antimicrobial treatment knowledge rules, and usefulness of the ontology for generating alerts to provide feedback to clinicians during antibiotic prescribing. Conclusions This study contributes to the understanding of ontology development and evaluation methods and addresses one knowledge gap related to using ontologies as a clinical decision support system component—a need for formal ontology evaluation methods to measure their quality from the perspective of their intrinsic characteristics and their usefulness for specific tasks. PMID:22019377

  8. Towards a semantic web of paleoclimatology

    Science.gov (United States)

    Emile-Geay, J.; Eshleman, J. A.

    2012-12-01

    The paleoclimate record is information-rich, yet signifiant technical barriers currently exist before it can be used to automatically answer scientific questions. Here we make the case for a universal format to structure paleoclimate data. A simple example demonstrates the scientific utility of such a self-contained way of organizing coral data and meta-data in the Matlab language. This example is generalized to a universal ontology that may form the backbone of an open-source, open-access and crowd-sourced paleoclimate database. Its key attributes are: 1. Parsability: the format is self-contained (hence machine-readable), and would therefore enable a semantic web of paleoclimate information. 2. Universality: the format is platform-independent (readable on all computer and operating systems), and language- independent (readable in major programming languages) 3. Extensibility: the format requires a minimum set of fields to appropriately define a paleoclimate record, but allows for the database to grow organically as more records are added, or - equally important - as more metadata are added to existing records. 4. Citability: The format enables the automatic citation of peer- reviewed articles as well as data citations whenever a data record is being used for analysis, making due recognition of scientific work an automatic part and foundational principle of paleoclimate data analysis. 5. Ergonomy: The format will be easy to use, update and manage. This structure is designed to enable semantic searches, and is expected to help accelerate discovery in all workflows where paleoclimate data are being used. Practical steps towards the implementation of such a system at the community level are then discussed.; Preliminary ontology describing relationships between the data and meta-data fields of the Nurhati et al. [2011] climate record. Several fields are viewed as instances of larger classes (ProxyClass,Site,Reference), which would allow computers to perform operations

  9. Montague semantics

    NARCIS (Netherlands)

    Janssen, T.M.V.

    2012-01-01

    Montague semantics is a theory of natural language semantics and of its relation with syntax. It was originally developed by the logician Richard Montague (1930-1971) and subsequently modified and extended by linguists, philosophers, and logicians. The most important features of the theory are its

  10. Towards an Approach of Semantic Access Control for Cloud Computing

    Science.gov (United States)

    Hu, Luokai; Ying, Shi; Jia, Xiangyang; Zhao, Kai

    With the development of cloud computing, the mutual understandability among distributed Access Control Policies (ACPs) has become an important issue in the security field of cloud computing. Semantic Web technology provides the solution to semantic interoperability of heterogeneous applications. In this paper, we analysis existing access control methods and present a new Semantic Access Control Policy Language (SACPL) for describing ACPs in cloud computing environment. Access Control Oriented Ontology System (ACOOS) is designed as the semantic basis of SACPL. Ontology-based SACPL language can effectively solve the interoperability issue of distributed ACPs. This study enriches the research that the semantic web technology is applied in the field of security, and provides a new way of thinking of access control in cloud computing.

  11. Information Pre-Processing using Domain Meta-Ontology and Rule Learning System

    Science.gov (United States)

    Ranganathan, Girish R.; Biletskiy, Yevgen

    Around the globe, extraordinary amounts of documents are being created by Enterprises and by users outside these Enterprises. The documents created in the Enterprises constitute the main focus of the present chapter. These documents are used to perform numerous amounts of machine processing. While using thesedocuments for machine processing, lack of semantics of the information in these documents may cause misinterpretation of the information, thereby inhibiting the productiveness of computer assisted analytical work. Hence, it would be profitable to the Enterprises if they use well defined domain ontologies which will serve as rich source(s) of semantics for the information in the documents. These domain ontologies can be created manually, semi-automatically or fully automatically. The focus of this chapter is to propose an intermediate solution which will enable relatively easy creation of these domain ontologies. The process of extracting and capturing domain ontologies from these voluminous documents requires extensive involvement of domain experts and application of methods of ontology learning that are substantially labor intensive; therefore, some intermediate solutions which would assist in capturing domain ontologies must be developed. This chapter proposes a solution in this direction which involves building a meta-ontology that will serve as an intermediate information source for the main domain ontology. This chapter proposes a solution in this direction which involves building a meta-ontology as a rapid approach in conceptualizing a domain of interest from huge amount of source documents. This meta-ontology can be populated by ontological concepts, attributes and relations from documents, and then refined in order to form better domain ontology either through automatic ontology learning methods or some other relevant ontology building approach.

  12. The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics

    Science.gov (United States)

    Cooper, Laurel; Meier, Austin; Laporte, Marie-Angélique; Elser, Justin L; Mungall, Chris; Sinn, Brandon T; Cavaliere, Dario; Carbon, Seth; Dunn, Nathan A; Smith, Barry; Qu, Botong; Preece, Justin; Zhang, Eugene; Todorovic, Sinisa; Gkoutos, Georgios; Doonan, John H; Stevenson, Dennis W; Arnaud, Elizabeth

    2018-01-01

    Abstract The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository. PMID:29186578

  13. Priming in Episodic and Semantic Memory.

    Science.gov (United States)

    McKoon, Gail; Ratcliff, Roger

    1979-01-01

    Four experiments examined priming between newly learned paired associates through two procedures, lexical decision and item recognition. Results argue against a functional separation of the semantic and episodic memory systems. (Author/AM)

  14. Using Ontologies in Cybersecurity Field

    Directory of Open Access Journals (Sweden)

    Tiberiu Marian GEORGESCU

    2017-01-01

    Full Text Available This paper is an exploratory research which aims to improve the cybersecurity field by means of semantic web technologies. The authors present a framework which uses Semantic Web technologies to automatically extract and analyse text in natural language available online. The system provides results that are further analysed by cybersecurity experts to detect black hat hackers’ activities. The authors examine several characteristics of how hacking communities communicate and collaborate online and how much information can be obtained by analysing different types of internet text communication channels. Having online sources as input data, the model proposed extracts and analyses natural language that relates with cybersecurity field, with the aid of ontologies. The main objective is to generate information about possible black hat hacking actions, which later can be analysed punctually by experts. This paper describes the data flow of the framework and it proposes technological solutions so that the model can be applied. In their future work, the authors plan to implement the framework described as a system software application.

  15. Ontology patterns for complex topographic feature yypes

    Science.gov (United States)

    Varanka, Dalia E.

    2011-01-01

    Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

  16. Model Validation in Ontology Based Transformations

    Directory of Open Access Journals (Sweden)

    Jesús M. Almendros-Jiménez

    2012-10-01

    Full Text Available Model Driven Engineering (MDE is an emerging approach of software engineering. MDE emphasizes the construction of models from which the implementation should be derived by applying model transformations. The Ontology Definition Meta-model (ODM has been proposed as a profile for UML models of the Web Ontology Language (OWL. In this context, transformations of UML models can be mapped into ODM/OWL transformations. On the other hand, model validation is a crucial task in model transformation. Meta-modeling permits to give a syntactic structure to source and target models. However, semantic requirements have to be imposed on source and target models. A given transformation will be sound when source and target models fulfill the syntactic and semantic requirements. In this paper, we present an approach for model validation in ODM based transformations. Adopting a logic programming based transformational approach we will show how it is possible to transform and validate models. Properties to be validated range from structural and semantic requirements of models (pre and post conditions to properties of the transformation (invariants. The approach has been applied to a well-known example of model transformation: the Entity-Relationship (ER to Relational Model (RM transformation.

  17. Web information retrieval based on ontology

    Science.gov (United States)

    Zhang, Jian

    2013-03-01

    The purpose of the Information Retrieval (IR) is to find a set of documents that are relevant for a specific information need of a user. Traditional Information Retrieval model commonly used in commercial search engine is based on keyword indexing system and Boolean logic queries. One big drawback of traditional information retrieval is that they typically retrieve information without an explicitly defined domain of interest to the users so that a lot of no relevance information returns to users, which burden the user to pick up useful answer from these no relevance results. In order to tackle this issue, many semantic web information retrieval models have been proposed recently. The main advantage of Semantic Web is to enhance search mechanisms with the use of Ontology's mechanisms. In this paper, we present our approach to personalize web search engine based on ontology. In addition, key techniques are also discussed in our paper. Compared to previous research, our works concentrate on the semantic similarity and the whole process including query submission and information annotation.

  18. Context-dependent Reasoning for the Semantic Web

    Directory of Open Access Journals (Sweden)

    Neli P. Zlatareva

    2011-08-01

    Full Text Available Ontologies are the backbone of the emerging Semantic Web, which is envisioned to dramatically improve current web services by extending them with intelligent capabilities such as reasoning and context-awareness. They define a shared vocabulary of common domains accessible to both, humans and computers, and support various types of information management including storage and processing of data. Current ontology languages, which are designed to be decidable to allow for automatic data processing, target simple typed ontologies that are completely and consistently specified. As the size of ontologies and the complexity of web applications grow, the need for more flexible representation and reasoning schemes emerges. This article presents a logical framework utilizing context-dependent rules which are intended to support not fully and/or precisely specified ontologies. A hypothetical application scenario is described to illustrate the type of ontologies targeted, and the type of queries that the presented logical framework is intended to address.

  19. Ontological interpretation of biomedical database content.

    Science.gov (United States)

    Santana da Silva, Filipe; Jansen, Ludger; Freitas, Fred; Schulz, Stefan

    2017-06-26

    Biological databases store data about laboratory experiments, together with semantic annotations, in order to support data aggregation and retrieval. The exact meaning of such annotations in the context of a database record is often ambiguous. We address this problem by grounding implicit and explicit database content in a formal-ontological framework. By using a typical extract from the databases UniProt and Ensembl, annotated with content from GO, PR, ChEBI and NCBI Taxonomy, we created four ontological models (in OWL), which generate explicit, distinct interpretations under the BioTopLite2 (BTL2) upper-level ontology. The first three models interpret database entries as individuals (IND), defined classes (SUBC), and classes with dispositions (DISP), respectively; the fourth model (HYBR) is a combination of SUBC and DISP. For the evaluation of these four models, we consider (i) database content retrieval, using ontologies as query vocabulary; (ii) information completeness; and, (iii) DL complexity and decidability. The models were tested under these criteria against four competency questions (CQs). IND does not raise any ontological claim, besides asserting the existence of sample individuals and relations among them. Modelling patterns have to be created for each type of annotation referent. SUBC is interpreted regarding maximally fine-grained defined subclasses under the classes referred to by the data. DISP attempts to extract truly ontological statements from the database records, claiming the existence of dispositions. HYBR is a hybrid of SUBC and DISP and is more parsimonious regarding expressiveness and query answering complexity. For each of the four models, the four CQs were submitted as DL queries. This shows the ability to retrieve individuals with IND, and classes in SUBC and HYBR. DISP does not retrieve anything because the axioms with disposition are embedded in General Class Inclusion (GCI) statements. Ambiguity of biological database content is

  20. Drug target ontology to classify and integrate drug discovery data

    DEFF Research Database (Denmark)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande

    2017-01-01

    using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem...... of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target...... characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein...

  1. The potential for use of semantic web technologies in IK management systems

    CSIR Research Space (South Africa)

    Fogwill, T

    2012-05-01

    Full Text Available Conference on Research and Development in information Retrieval, Philadelphia, Pennsylvania, United States, July 27 - 31, 1997. [27] M. Espinoza, A. G?mez-P?rez, E. Mena, Enriching an Ontology with Multilingual Information. The Semantic Web: Research...

  2. Ontology construction and application in practice case study of health tourism in Thailand.

    Science.gov (United States)

    Chantrapornchai, Chantana; Choksuchat, Chidchanok

    2016-01-01

    Ontology is one of the key components in semantic webs. It contains the core knowledge for an effective search. However, building ontology requires the carefully-collected knowledge which is very domain-sensitive. In this work, we present the practice of ontology construction for a case study of health tourism in Thailand. The whole process follows the METHONTOLOGY approach, which consists of phases: information gathering, corpus study, ontology engineering, evaluation, publishing, and the application construction. Different sources of data such as structure web documents like HTML and other documents are acquired in the information gathering process. The tourism corpora from various tourism texts and standards are explored. The ontology is evaluated in two aspects: automatic reasoning using Pellet, and RacerPro, and the questionnaires, used to evaluate by experts of the domains: tourism domain experts and ontology experts. The ontology usability is demonstrated via the semantic web application and via example axioms. The developed ontology is actually the first health tourism ontology in Thailand with the published application.

  3. Semi Automatic Ontology Instantiation in the domain of Risk Management

    Science.gov (United States)

    Makki, Jawad; Alquier, Anne-Marie; Prince, Violaine

    One of the challenging tasks in the context of Ontological Engineering is to automatically or semi-automatically support the process of Ontology Learning and Ontology Population from semi-structured documents (texts). In this paper we describe a Semi-Automatic Ontology Instantiation method from natural language text, in the domain of Risk Management. This method is composed from three steps 1 ) Annotation with part-of-speech tags, 2) Semantic Relation Instances Extraction, 3) Ontology instantiation process. It's based on combined NLP techniques using human intervention between steps 2 and 3 for control and validation. Since it heavily relies on linguistic knowledge it is not domain dependent which is a good feature for portability between the different fields of risk management application. The proposed methodology uses the ontology of the PRIMA1 project (supported by the European community) as a Generic Domain Ontology and populates it via an available corpus. A first validation of the approach is done through an experiment with Chemical Fact Sheets from Environmental Protection Agency2.

  4. Semantic Desktop

    Science.gov (United States)

    Sauermann, Leo; Kiesel, Malte; Schumacher, Kinga; Bernardi, Ansgar

    In diesem Beitrag wird gezeigt, wie der Arbeitsplatz der Zukunft aussehen könnte und wo das Semantic Web neue Möglichkeiten eröffnet. Dazu werden Ansätze aus dem Bereich Semantic Web, Knowledge Representation, Desktop-Anwendungen und Visualisierung vorgestellt, die es uns ermöglichen, die bestehenden Daten eines Benutzers neu zu interpretieren und zu verwenden. Dabei bringt die Kombination von Semantic Web und Desktop Computern besondere Vorteile - ein Paradigma, das unter dem Titel Semantic Desktop bekannt ist. Die beschriebenen Möglichkeiten der Applikationsintegration sind aber nicht auf den Desktop beschränkt, sondern können genauso in Web-Anwendungen Verwendung finden.

  5. Conceptual querying through ontologies

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2009-01-01

    is motivated by an obvious need for users to survey huge volumes of objects in query answers. An ontology formalism and a special notion of-instantiated ontology" are introduced. The latter is a structure reflecting the content in the document collection in that; it is a restriction of a general world......We present here ail approach to conceptual querying where the aim is, given a collection of textual database objects or documents, to target an abstraction of the entire database content in terms of the concepts appearing in documents, rather than the documents in the collection. The approach...... knowledge ontology to the concepts instantiated in the collection. The notion of ontology-based similarity is briefly described, language constructs for direct navigation and retrieval of concepts in the ontology are discussed and approaches to conceptual summarization are presented....

  6. How Chinese Semantics Capability Improves Interpretation in Visual Communication

    Science.gov (United States)

    Cheng, Chu-Yu; Ou, Yang-Kun; Kin, Ching-Lung

    2017-01-01

    A visual representation involves delivering messages through visually communicated images. The study assumed that semantic recognition can affect visual interpretation ability, and the result showed that students graduating from a general high school achieve satisfactory results in semantic recognition and image interpretation tasks than students…

  7. Social Semantics for an Effective Enterprise

    Science.gov (United States)

    Berndt, Sarah; Doane, Mike

    2012-01-01

    An evolution of the Semantic Web, the Social Semantic Web (s2w), facilitates knowledge sharing with "useful information based on human contributions, which gets better as more people participate." The s2w reaches beyond the search box to move us from a collection of hyperlinked facts, to meaningful, real time context. When focused through the lens of Enterprise Search, the Social Semantic Web facilitates the fluid transition of meaningful business information from the source to the user. It is the confluence of human thought and computer processing structured with the iterative application of taxonomies, folksonomies, ontologies, and metadata schemas. The importance and nuances of human interaction are often deemphasized when focusing on automatic generation of semantic markup, which results in dissatisfied users and unrealized return on investment. Users consistently qualify the value of information sets through the act of selection, making them the de facto stakeholders of the Social Semantic Web. Employers are the ultimate beneficiaries of s2w utilization with a better informed, more decisive workforce; one not achieved with an IT miracle technology, but by improved human-computer interactions. Johnson Space Center Taxonomist Sarah Berndt and Mike Doane, principal owner of Term Management, LLC discuss the planning, development, and maintenance stages for components of a semantic system while emphasizing the necessity of a Social Semantic Web for the Enterprise. Identification of risks and variables associated with layering the successful implementation of a semantic system are also modeled.

  8. BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications.

    Science.gov (United States)

    Whetzel, Patricia L; Noy, Natalya F; Shah, Nigam H; Alexander, Paul R; Nyulas, Csongor; Tudorache, Tania; Musen, Mark A

    2011-07-01

    The National Center for Biomedical Ontology (NCBO) is one of the National Centers for Biomedical Computing funded under the NIH Roadmap Initiative. Contributing to the national computing infrastructure, NCBO has developed BioPortal, a web portal that provides access to a library of biomedical ontologies and terminologies (http://bioportal.bioontology.org) via the NCBO Web services. BioPortal enables community participation in the evaluation and evolution of ontology content by providing features to add mappings between terms, to add comments linked to specific ontology terms and to provide ontology reviews. The NCBO Web services (http://www.bioontology.org/wiki/index.php/NCBO_REST_services) enable this functionality and provide a uniform mechanism to access ontologies from a variety of knowledge representation formats, such as Web Ontology Language (OWL) and Open Biological and Biomedical Ontologies (OBO) format. The Web services provide multi-layered access to the ontology content, from getting all terms in an ontology to retrieving metadata about a term. Users can easily incorporate the NCBO Web services into software applications to generate semantically aware applications and to facilitate structured data collection.

  9. Natural Language Processing (NLP), Machine Learning (ML), and Semantics in Polar Science

    Science.gov (United States)

    Duerr, R.; Ramdeen, S.

    2017-12-01

    One of the interesting features of Polar Science is that it historically has been extremely interdisciplinary, encompassing all of the physical and social sciences. Given the ubiquity of specialized terminology in each field, enabling researchers to find, understand, and use all of the heterogeneous data needed for polar research continues to be a bottleneck. Within the informatics community, semantics has broadly accepted as a solution to these problems, yet progress in developing reusable semantic resources has been slow. The NSF-funded ClearEarth project has been adapting the methods and tools from other communities such as Biomedicine to the Earth sciences with the goal of enhancing progress and the rate at which the needed semantic resources can be created. One of the outcomes of the project has been a better understanding of the differences in the way linguists and physical scientists understand disciplinary text. One example of these differences is the tendency for each discipline and often disciplinary subfields to expend effort in creating discipline specific glossaries where individual terms often are comprised of more than one word (e.g., first-year sea ice). Often each term in a glossary is imbued with substantial contextual or physical meaning - meanings which are rarely explicitly called out within disciplinary texts; meaning which are therefore not immediately accessible to those outside that discipline or subfield; meanings which can often be represented semantically. Here we show how recognition of these difference and the use of glossaries can be used to speed up the annotation processes endemic to NLP, enable inter-community recognition and possible reconciliation of terminology differences. A number of processes and tools will be described, as will progress towards semi-automated generation of ontology structures.

  10. Incorporating Semantic Knowledge into Dynamic Data Processing for Smart Power Grids

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

    2012-11-15

    Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.

  11. BioPortal: An Open-Source Community-Based Ontology Repository

    Science.gov (United States)

    Noy, N.; NCBO Team

    2011-12-01

    Advances in computing power and new computational techniques have changed the way researchers approach science. In many fields, one of the most fruitful approaches has been to use semantically aware software to break down the barriers among disparate domains, systems, data sources, and technologies. Such software facilitates data aggregation, improves search, and ultimately allows the detection of new associations that were previously not detectable. Achieving these analyses requires software systems that take advantage of the semantics and that can intelligently negotiate domains and knowledge sources, identifying commonality across systems that use different and conflicting vocabularies, while understanding apparent differences that may be concealed by the use of superficially similar terms. An ontology, a semantically rich vocabulary for a domain of interest, is the cornerstone of software for bridging systems, domains, and resources. However, as ontologies become the foundation of all semantic technologies in e-science, we must develop an infrastructure for sharing ontologies, finding and evaluating them, integrating and mapping among them, and using ontologies in applications that help scientists process their data. BioPortal [1] is an open-source on-line community-based ontology repository that has been used as a critical component of semantic infrastructure in several domains, including biomedicine and bio-geochemical data. BioPortal, uses the social approaches in the Web 2.0 style to bring structure and order to the collection of biomedical ontologies. It enables users to provide and discuss a wide array of knowledge components, from submitting the ontologies themselves, to commenting on and discussing classes in the ontologies, to reviewing ontologies in the context of their own ontology-based projects, to creating mappings between overlapping ontologies and discussing and critiquing the mappings. Critically, it provides web-service access to all its

  12. The MMI Semantic Framework: Rosetta Stones for Earth Sciences

    Science.gov (United States)

    Rueda, C.; Bermudez, L. E.; Graybeal, J.; Alexander, P.

    2009-12-01

    Semantic interoperability—the exchange of meaning among computer systems—is needed to successfully share data in Ocean Science and across all Earth sciences. The best approach toward semantic interoperability requires a designed framework, and operationally tested tools and infrastructure within that framework. Currently available technologies make a scientific semantic framework feasible, but its development requires sustainable architectural vision and development processes. This presentation outlines the MMI Semantic Framework, including recent progress on it and its client applications. The MMI Semantic Framework consists of tools, infrastructure, and operational and community procedures and best practices, to meet short-term and long-term semantic interoperability goals. The design and prioritization of the semantic framework capabilities are based on real-world scenarios in Earth observation systems. We describe some key uses cases, as well as the associated requirements for building the overall infrastructure, which is realized through the MMI Ontology Registry and Repository. This system includes support for community creation and sharing of semantic content, ontology registration, version management, and seamless integration of user-friendly tools and application programming interfaces. The presentation describes the architectural components for semantic mediation, registry and repository for vocabularies, ontology, and term mappings. We show how the technologies and approaches in the framework can address community needs for managing and exchanging semantic information. We will demonstrate how different types of users and client applications exploit the tools and services for data aggregation, visualization, archiving, and integration. Specific examples from OOSTethys (http://www.oostethys.org) and the Ocean Observatories Initiative Cyberinfrastructure (http://www.oceanobservatories.org) will be cited. Finally, we show how semantic augmentation of web

  13. Spatial Data Integration Using Ontology-Based Approach

    Science.gov (United States)

    Hasani, S.; Sadeghi-Niaraki, A.; Jelokhani-Niaraki, M.

    2015-12-01

    In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

  14. SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH

    Directory of Open Access Journals (Sweden)

    S. Hasani

    2015-12-01

    Full Text Available In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

  15. Ontological foundations for evolutionary economics: A Darwinian social ontology

    NARCIS (Netherlands)

    Stoelhorst, J.W.

    2008-01-01

    The purpose of this paper is to further the project of generalized Darwinism by developing a social ontology on the basis of a combined commitment to ontological continuity and ontological commonality. Three issues that are central to the development of a social ontology are addressed: (1) the

  16. BIM – New rules of measurement ontology for construction cost estimation

    Directory of Open Access Journals (Sweden)

    F.H. Abanda

    2017-04-01

    Full Text Available For generations, the process of cost estimation has been manual, time-consuming and error-prone. Emerging Building Information Modelling (BIM can exploit standard measurement methods to automate cost estimation process and improve inaccuracies. Structuring standard measurement methods in an ontologically and machine readable format for a BIM software can greatly facilitate the process of improving inaccuracies in cost estimation. This study explores the development of an ontology based on New Rules of Measurement (NRM for cost estimation during the tendering stages. The methodology adopted is methontology, one of the most widely used ontology engineering methodologies. To ensure the ontology is fit for purpose, cost estimation experts are employed to check the semantics, descriptive logic-based reasoners are used to syntactically check the ontology and a leading 4D BIM modelling software is used on a case study building to test/validate the proposed ontology.

  17. The Semantic Web: From Representation to Realization

    Science.gov (United States)

    Thórisson, Kristinn R.; Spivack, Nova; Wissner, James M.

    A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

  18. ODISEES: Ontology-Driven Interactive Search Environment for Earth Sciences

    Science.gov (United States)

    Rutherford, Matthew T.; Huffer, Elisabeth B.; Kusterer, John M.; Quam, Brandi M.

    2015-01-01

    This paper discusses the Ontology-driven Interactive Search Environment for Earth Sciences (ODISEES) project currently being developed to aid researchers attempting to find usable data among an overabundance of closely related data. ODISEES' ontological structure relies on a modular, adaptable concept modeling approach, which allows the domain to be modeled more or less as it is without worrying about terminology or external requirements. In the model, variables are individually assigned semantic content based on the characteristics of the measurements they represent, allowing intuitive discovery and comparison of data without requiring the user to sift through large numbers of data sets and variables to find the desired information.

  19. Populating the Semantic Web by Macro-reading Internet Text

    Science.gov (United States)

    Mitchell, Tom M.; Betteridge, Justin; Carlson, Andrew; Hruschka, Estevam; Wang, Richard

    A key question regarding the future of the semantic web is "how will we acquire structured information to populate the semantic web on a vast scale?" One approach is to enter this information manually. A second approach is to take advantage of pre-existing databases, and to develop common ontologies, publishing standards, and reward systems to make this data widely accessible. We consider here a third approach: developing software that automatically extracts structured information from unstructured text present on the web. We also describe preliminary results demonstrating that machine learning algorithms can learn to extract tens of thousands of facts to populate a diverse ontology, with imperfect but reasonably good accuracy.

  20. Superficial Priming in Episodic Recognition

    Science.gov (United States)

    Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.

    2010-01-01

    We explored the effect of superficial priming in episodic recognition and found it to be different from the effect of semantic priming in episodic recognition. Participants made recognition judgments to pairs of items, with each pair consisting of a prime item and a test item. Correct positive responses to the test item were impeded if the prime…

  1. Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.

    Science.gov (United States)

    Jung, Hyesil; Park, Hyeoun-Ae; Song, Tae-Min

    2017-07-24

    Social networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts and their relationships in a specific field could be used as a semantic framework for social media data analytics. The aim of this study was to refine an adolescent depression ontology and terminology as a framework for analyzing social media data and to evaluate description logics between classes and the applicability of this ontology to sentiment analysis. The domain and scope of the ontology were defined using competency questions. The concepts constituting the ontology and terminology were collected from clinical practice guidelines, the literature, and social media postings on adolescent depression. Class concepts, their hierarchy, and the relationships among class concepts were defined. An internal structure of the ontology was designed using the entity-attribute-value (EAV) triplet data model, and superclasses of the ontology were aligned with the upper ontology. Description logics between classes were evaluated by mapping concepts extracted from the answers to frequently asked questions (FAQs) onto the ontology concepts derived from description logic queries. The applicability of the ontology was validated by examining the representability of 1358 sentiment phrases using the ontology EAV model and conducting sentiment analyses of social media data using ontology class concepts. We developed an adolescent depression ontology that comprised 443 classes and 60 relationships among the classes; the terminology comprised 1682 synonyms of the 443 classes. In the description logics test, no error in relationships between classes was found, and about 89% (55/62) of the concepts cited in the answers to FAQs mapped onto the ontology class. Regarding applicability, the EAV triplet models of the ontology class represented about 91

  2. Data mining for ontology development.

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, George S.; Strasburg, Jana (Pacific Northwest National Laboratory, Richland, WA); Stampf, David (Brookhaven National Laboratory, Upton, NY); Neymotin,Lev (Brookhaven National Laboratory, Upton, NY); Czajkowski, Carl (Brookhaven National Laboratory, Upton, NY); Shine, Eugene (Savannah River National Laboratory, Aiken, SC); Bollinger, James (Savannah River National Laboratory, Aiken, SC); Ghosh, Vinita (Brookhaven National Laboratory, Upton, NY); Sorokine, Alexandre (Oak Ridge National Laboratory, Oak Ridge, TN); Ferrell, Regina (Oak Ridge National Laboratory, Oak Ridge, TN); Ward, Richard (Oak Ridge National Laboratory, Oak Ridge, TN); Schoenwald, David Alan

    2010-06-01

    A multi-laboratory ontology construction effort during the summer and fall of 2009 prototyped an ontology for counterfeit semiconductor manufacturing. This effort included an ontology development team and an ontology validation methods team. Here the third team of the Ontology Project, the Data Analysis (DA) team reports on their approaches, the tools they used, and results for mining literature for terminology pertinent to counterfeit semiconductor manufacturing. A discussion of the value of ontology-based analysis is presented, with insights drawn from other ontology-based methods regularly used in the analysis of genomic experiments. Finally, suggestions for future work are offered.

  3. TrhOnt: building an ontology to assist rehabilitation processes.

    Science.gov (United States)

    Berges, Idoia; Antón, David; Bermúdez, Jesús; Goñi, Alfredo; Illarramendi, Arantza

    2016-10-04

    One of the current research efforts in the area of biomedicine is the representation of knowledge in a structured way so that reasoning can be performed on it. More precisely, in the field of physiotherapy, information such as the physiotherapy record of a patient or treatment protocols for specific disorders must be adequately modeled, because they play a relevant role in the management of the evolutionary recovery process of a patient. In this scenario, we introduce TRHONT, an application ontology that can assist physiotherapists in the management of the patients' evolution via reasoning supported by semantic technology. The ontology was developed following the NeOn Methodology. It integrates knowledge from ontological (e.g. FMA ontology) and non-ontological resources (e.g. a database of movements, exercises and treatment protocols) as well as additional physiotherapy-related knowledge. We demonstrate how the ontology fulfills the purpose of providing a reference model for the representation of the physiotherapy-related information that is needed for the whole physiotherapy treatment of patients, since they step for the first time into the physiotherapist's office, until they are discharged. More specifically, we present the results for each of the intended uses of the ontology listed in the document that specifies its requirements, and show how TRHONT can answer the competency questions defined within that document. Moreover, we detail the main steps of the process followed to build the TRHONT ontology in order to facilitate its reproducibility in a similar context. Finally, we show an evaluation of the ontology from different perspectives. TRHONT has achieved the purpose of allowing for a reasoning process that changes over time according to the patient's state and performance.

  4. Morphological Family Size Effects in Young First and Second Language Learners: Evidence of Cross-Language Semantic Activation in Visual Word Recognition

    Science.gov (United States)

    de Zeeuw, Marlies; Verhoeven, Ludo; Schreuder, Robert

    2012-01-01

    This study examined to what extent young second language (L2) learners showed morphological family size effects in L2 word recognition and whether the effects were grade-level related. Turkish-Dutch bilingual children (L2) and Dutch (first language, L1) children from second, fourth, and sixth grade performed a Dutch lexical decision task on words…

  5. VOILA 2015 Visualizations and User Interfaces for Ontologies and Linked Data : Proceedings of the International Workshop on Visualizations and User Interfaces for Ontologies and Linked Data

    OpenAIRE

    2015-01-01

    A picture is worth a thousand words, we often say, yet many areas are in demand of sophisticated visualization techniques, and the Semantic Web is not an exception. The size and complexity of ontologies and Linked Data in the Semantic Web constantly grow and the diverse backgrounds of the users and application areas multiply at the same time. Providing users with visual representations and intuitive user interfaces can significantly aid the understanding of the domains and knowledge represent...

  6. The Semantic Web: opportunities and challenges for next-generation Web applications

    Directory of Open Access Journals (Sweden)

    2002-01-01

    Full Text Available Recently there has been a growing interest in the investigation and development of the next generation web - the Semantic Web. While most of the current forms of web content are designed to be presented to humans, but are barely understandable by computers, the content of the Semantic Web is structured in a semantic way so that it is meaningful to computers as well as to humans. In this paper, we report a survey of recent research on the Semantic Web. In particular, we present the opportunities that this revolution will bring to us: web-services, agent-based distributed computing, semantics-based web search engines, and semantics-based digital libraries. We also discuss the technical and cultural challenges of realizing the Semantic Web: the development of ontologies, formal semantics of Semantic Web languages, and trust and proof models. We hope that this will shed some light on the direction of future work on this field.

  7. Ontology of fractures

    Science.gov (United States)

    Zhong, Jian; Aydina, Atilla; McGuinness, Deborah L.

    2009-03-01

    Fractures are fundamental structures in the Earth's crust and they can impact many societal and industrial activities including oil and gas exploration and production, aquifer management, CO 2 sequestration, waste isolation, the stabilization of engineering structures, and assessing natural hazards (earthquakes, volcanoes, and landslides). Therefore, an ontology which organizes the concepts of fractures could help facilitate a sound education within, and communication among, the highly diverse professional and academic community interested in the problems cited above. We developed a process-based ontology that makes explicit specifications about fractures, their properties, and the deformation mechanisms which lead to their formation and evolution. Our ontology emphasizes the relationships among concepts such as the factors that influence the mechanism(s) responsible for the formation and evolution of specific fracture types. Our ontology is a valuable resource with a potential to applications in a number of fields utilizing recent advances in Information Technology, specifically for digital data and information in computers, grids, and Web services.

  8. Visual Development Environment for Semantically Interoperable Smart Cities Applications

    OpenAIRE

    Roukounaki , Aikaterini; Soldatos , John; Petrolo , Riccardo; Loscri , Valeria; Mitton , Nathalie; Serrano , Martin

    2015-01-01

    International audience; This paper presents an IoT architecture for the semantic interoperability of diverse IoT systems and applications in smart cities. The architecture virtualizes diverse IoT systems and ensures their modelling and representation according to common standards-based IoT ontologies. Furthermore, based on this architecture, the paper introduces a first-of-a-kind visual development environment which eases the development of semantically interoperable applications in smart cit...

  9. A Method for Evaluating and Standardizing Ontologies

    Science.gov (United States)

    Seyed, Ali Patrice

    2012-01-01

    The Open Biomedical Ontology (OBO) Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. The Basic Formal Ontology (BFO) serves as the upper ontology for the domain-level ontologies of OBO. BFO is an upper ontology of types as conceived by defenders of realism. Among the ontologies developed for OBO…

  10. Manufacturing ontology through templates

    Directory of Open Access Journals (Sweden)

    Diciuc Vlad

    2017-01-01

    Full Text Available The manufacturing industry contains a high volume of knowhow and of high value, much of it being held by key persons in the company. The passing of this know-how is the basis of manufacturing ontology. Among other methods like advanced filtering and algorithm based decision making, one way of handling the manufacturing ontology is via templates. The current paper tackles this approach and highlights the advantages concluding with some recommendations.

  11. Spatial cyberinfrastructures, ontologies, and the humanities.

    Science.gov (United States)

    Sieber, Renee E; Wellen, Christopher C; Jin, Yuan

    2011-04-05

    We report on research into building a cyberinfrastructure for Chinese biographical and geographic data. Our cyberinfrastructure contains (i) the McGill-Harvard-Yenching Library Ming Qing Women's Writings database (MQWW), the only online database on historical Chinese women's writings, (ii) the China Biographical Database, the authority for Chinese historical people, and (iii) the China Historical Geographical Information System, one of the first historical geographic information systems. Key to this integration is that linked databases retain separate identities as bases of knowledge, while they possess sufficient semantic interoperability to allow for multidatabase concepts and to support cross-database queries on an ad hoc basis. Computational ontologies create underlying semantics for database access. This paper focuses on the spatial component in a humanities cyberinfrastructure, which includes issues of conflicting data, heterogeneous data models, disambiguation, and geographic scale. First, we describe the methodology for integrating the databases. Then we detail the system architecture, which includes a tier of ontologies and schema. We describe the user interface and applications that allow for cross-database queries. For instance, users should be able to analyze the data, examine hypotheses on spatial and temporal relationships, and generate historical maps with datasets from MQWW for research, teaching, and publication on Chinese women writers, their familial relations, publishing venues, and the literary and social communities. Last, we discuss the social side of cyberinfrastructure development, as people are considered to be as critical as the technical components for its success.

  12. Spatial cyberinfrastructures, ontologies, and the humanities

    Science.gov (United States)

    Sieber, Renee E.; Wellen, Christopher C.; Jin, Yuan

    2011-01-01

    We report on research into building a cyberinfrastructure for Chinese biographical and geographic data. Our cyberinfrastructure contains (i) the McGill-Harvard-Yenching Library Ming Qing Women's Writings database (MQWW), the only online database on historical Chinese women's writings, (ii) the China Biographical Database, the authority for Chinese historical people, and (iii) the China Historical Geographical Information System, one of the first historical geographic information systems. Key to this integration is that linked databases retain separate identities as bases of knowledge, while they possess sufficient semantic interoperability to allow for multidatabase concepts and to support cross-database queries on an ad hoc basis. Computational ontologies create underlying semantics for database access. This paper focuses on the spatial component in a humanities cyberinfrastructure, which includes issues of conflicting data, heterogeneous data models, disambiguation, and geographic scale. First, we describe the methodology for integrating the databases. Then we detail the system architecture, which includes a tier of ontologies and schema. We describe the user interface and applications that allow for cross-database queries. For instance, users should be able to analyze the data, examine hypotheses on spatial and temporal relationships, and generate historical maps with datasets from MQWW for research, teaching, and publication on Chinese women writers, their familial relations, publishing venues, and the literary and social communities. Last, we discuss the social side of cyberinfrastructure development, as people are considered to be as critical as the technical components for its success. PMID:21444819

  13. Ontology Update in the Cognitive Model of Ontology Learning

    Directory of Open Access Journals (Sweden)

    Zhang De-Hai

    2016-01-01

    Full Text Available Ontology has been used in many hot-spot fields, but most ontology construction methods are semiautomatic, and the construction process of ontology is still a tedious and painstaking task. In this paper, a kind of cognitive models is presented for ontology learning which can simulate human being’s learning from world. In this model, the cognitive strategies are applied with the constrained axioms. Ontology update is a key step when the new knowledge adds into the existing ontology and conflict with old knowledge in the process of ontology learning. This proposal designs and validates the method of ontology update based on the axiomatic cognitive model, which include the ontology update postulates, axioms and operations of the learning model. It is proved that these operators subject to the established axiom system.

  14. Development of Ontology and 3D Software for the Diseases of Spine

    Directory of Open Access Journals (Sweden)

    Seungbock Lee

    2015-01-01

    Full Text Available KISTI is carrying out an e-Spine project for spinal diseases to prepare for the aged society, so-called NAP. The purpose of the study is to build a spine ontology that represents the anatomical structure and disease information which is compatible with simulation model of KISTI. The final use of the ontology includes diagnosis of diseases and setting treatment directions by the clinicians. The ontology was represented using 3D software. Twenty diseases were selected to be represented after discussions with a spine specialist. Several ontology studies were reviewed, reference books were selected for each disease and were organized in MS Excel. All the contents were then reviewed by the specialists. Altova SemanticWorks and Protégé were used to code spine ontology with OWL Full model. Links to the images from KISTI and sample images of diseases were included in the ontology. The OWL ontology was also reviewed by the specialists again with Protégé. We represented unidirectional ontology from anatomical structure to disease, images, and treatment. The ontology was human understandable. It would be useful for the education of medical students or residents studying diseases of spine. But in order for the computer to understand the ontology, a new model with OWL DL or Lite is needed.

  15. A Semantics-Based Approach to Retrieving Biomedical Information

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik; Zambach, Sine

    2011-01-01

    This paper describes an approach to representing, organising, and accessing conceptual content of biomedical texts using a formal ontology. The ontology is based on UMLS resources supplemented with domain ontologies developed in the project. The approach introduces the notion of ‘generative ontol...... of data mining of texts identifying paraphrases and concept relations and measuring distances between key concepts in texts. Thus, the project is distinct in its attempt to provide a formal underpinning of conceptual similarity or relatedness of meaning.......This paper describes an approach to representing, organising, and accessing conceptual content of biomedical texts using a formal ontology. The ontology is based on UMLS resources supplemented with domain ontologies developed in the project. The approach introduces the notion of ‘generative...... ontologies’, i.e., ontologies providing increasingly specialised concepts reflecting the phrase structure of natural language. Furthermore, we propose a novel so called ontological semantics which maps noun phrases from texts and queries into nodes in the generative ontology. This enables an advanced form...

  16. Semantic Service Design for Collaborative Business Processes in Internetworked Enterprises

    Science.gov (United States)

    Bianchini, Devis; Cappiello, Cinzia; de Antonellis, Valeria; Pernici, Barbara

    Modern collaborating enterprises can be seen as borderless organizations whose processes are dynamically transformed and integrated with the ones of their partners (Internetworked Enterprises, IE), thus enabling the design of collaborative business processes. The adoption of Semantic Web and service-oriented technologies for implementing collaboration in such distributed and heterogeneous environments promises significant benefits. IE can model their own processes independently by using the Software as a Service paradigm (SaaS). Each enterprise maintains a catalog of available services and these can be shared across IE and reused to build up complex collaborative processes. Moreover, each enterprise can adopt its own terminology and concepts to describe business processes and component services. This brings requirements to manage semantic heterogeneity in process descriptions which are distributed across different enterprise systems. To enable effective service-based collaboration, IEs have to standardize their process descriptions and model them through component services using the same approach and principles. For enabling collaborative business processes across IE, services should be designed following an homogeneous approach, possibly maintaining a uniform level of granularity. In the paper we propose an ontology-based semantic modeling approach apt to enrich and reconcile semantics of process descriptions to facilitate process knowledge management and to enable semantic service design (by discovery, reuse and integration of process elements/constructs). The approach brings together Semantic Web technologies, techniques in process modeling, ontology building and semantic matching in order to provide a comprehensive semantic modeling framework.

  17. Semantic Web technologies in software engineering

    OpenAIRE

    Gall, H C; Reif, G

    2008-01-01

    Over the years, the software engineering community has developed various tools to support the specification, development, and maintainance of software. Many of these tools use proprietary data formats to store artifacts which hamper interoperability. However, the Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. Ontologies are used define the concepts in the domain of discourse and their relationships an...

  18. USE OF ONTOLOGIES FOR KNOWLEDGE BASES CREATION TUTORING COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Cheremisina Lyubov

    2014-11-01

    Full Text Available This paper deals with the use of ontology for the use and development of intelligent tutoring systems. We consider the shortcomings of educational software and distance learning systems and the advantages of using ontology’s in their design. Actuality creates educational computer systems based on systematic knowledge. We consider classification of properties, use and benefits of ontology’s. Characterized approaches to the problem of ontology mapping, the first of which – manual mapping, the second – a comparison of the names of concepts based on their lexical similarity and using special dictionaries. The analysis of languages available for the formal description of ontology. Considered a formal mathematical model of ontology’s and ontology consistency problem, which is that different developers for the same domain ontology can be created, syntactically or semantically heterogeneous, and their use requires a compatible broadcast or display. An algorithm combining ontology’s. The characteristic of the practical value of developing an ontology for electronic educational resources and recommendations for further research and development, such as implementation of other components of the system integration, formalization of the processes of integration and development of a universal expansion algorithms ontology’s software

  19. Practical Experiences for the Development of Educational Systems in the Semantic Web

    Science.gov (United States)

    Sánchez Vera, Ma. del Mar; Tomás Fernández Breis, Jesualdo; Serrano Sánchez, José Luis; Prendes Espinosa, Ma. Paz

    2013-01-01

    Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable…

  20. RoboDB: an application of Semantic Web Technologies to robotics

    NARCIS (Netherlands)

    Juarez, Alex; Hu, J.; Feijs, L.M.G.

    2011-01-01

    RoboDB is a knowledge acquisition system that gathers information about robots. RoboDB uses Semantic Web technologies and tools to help the user in creating semantic descriptions of robot embodiments and their capabilities, as well as in building an ontology of robotics projects, research

  1. Alignment of the UMLS semantic network with BioTop: Methodology and assessment

    NARCIS (Netherlands)

    S. Schulz; E. Beisswanger (Elena); L. van den Hoek (László); O. Bodenreider (Olivier); E.M. van Mulligen (Erik)

    2009-01-01

    textabstractMotivation: For many years, the Unified Medical Language System (UMLS) semantic network (SN) has been used as an upper-level semantic framework for the categorization of terms from terminological resources in biomedicine. BioTop has recently been developed as an upper-level ontology for

  2. Ontology lexicalization: Relationship between content and meaning in the context of Information Retrieval

    Directory of Open Access Journals (Sweden)

    Marcelo SCHIESSL

    Full Text Available Abstract The proposal presented in this study seeks to properly represent natural language to ontologies and vice-versa. Therefore, the semi-automatic creation of a lexical database in Brazilian Portuguese containing morphological, syntactic, and semantic information that can be read by machines was proposed, allowing the link between structured and unstructured data and its integration into an information retrieval model to improve precision. The results obtained demonstrated that the methodology can be used in the risco financeiro (financial risk domain in Portuguese for the construction of an ontology and the lexical-semantic database and the proposal of a semantic information retrieval model. In order to evaluate the performance of the proposed model, documents containing the main definitions of the financial risk domain were selected and indexed with and without semantic annotation. To enable the comparison between the approaches, two databases were created based on the texts with the semantic annotations to represent the semantic search. The first one represents the traditional search and the second contained the index built based on the texts with the semantic annotations to represent the semantic search. The evaluation of the proposal was based on recall and precision. The queries submitted to the model showed that the semantic search outperforms the traditional search and validates the methodology used. Although more complex, the procedure proposed can be used in all kinds of domains.

  3. Generative Semantics

    Science.gov (United States)

    Bagha, Karim Nazari

    2011-01-01

    Generative semantics is (or perhaps was) a research program within linguistics, initiated by the work of George Lakoff, John R. Ross, Paul Postal and later McCawley. The approach developed out of transformational generative grammar in the mid 1960s, but stood largely in opposition to work by Noam Chomsky and his students. The nature and genesis of…

  4. Inferentializing Semantics

    Czech Academy of Sciences Publication Activity Database

    Peregrin, Jaroslav

    2010-01-01

    Roč. 39, č. 3 (2010), s. 255-274 ISSN 0022-3611 R&D Projects: GA ČR(CZ) GA401/07/0904 Institutional research plan: CEZ:AV0Z90090514 Keywords : inference * proof theory * model theory * inferentialism * semantics Subject RIV: AA - Philosophy ; Religion

  5. Reactive Leadership: Divining, Developing, and Demonstrating Community Ontologies

    Science.gov (United States)

    Graybeal, J.

    2008-12-01

    The Marine Metadata Interoperability Project (known as MMI, on the web at http://marinemetadata.org) was formed to provide leadership in metadata practices to the marine science community. In 2004 this meant finding and writing about resources and best practices, which until then were all but invisible. In 2008 the scope is far wider, encompassing comprehensive guidance, collaborative community environments, and introduction and demonstration of advanced technologies to an increasingly interested scientific domain. MMI's technical leadership, based on experiences gained in the hydrologic community, emphasized the role ontologies could play in marine science. An early MMI workshop successfully incorporated a large number of community vocabularies, tools to harmonize them in a common ontological format, and the mapping of terms from vocabularies expressed in that format. That 2005 workshop demonstrated the connections to be made among different community vocabularies, and was well regarded by participants, but did not lead to widespread adoption of the tools, technologies, or even the vocabularies. Ontology development efforts for marine sensors and platforms showed intermittent progress, but again were not adopted or pushed toward completion. It is now 2008, and the marine community is increasingly attentive to a wide range of interoperability issues. A large part of the community has at least heard of "semantic interoperability", and many understand its critical role in finding and working with data. Demand for specific solutions, and for workable approaches, is becoming more vocal in the marine community. Yet there is still no encompassing model in place for achieving semantic interoperability, only simple operational registries have been set up for oceanographic community vocabularies, and only a few isolated applications demonstrate how semantic barriers can be overcome. Why has progress been so slow? Are good answers on the horizon? And if we build it, will the

  6. Semantic Location Extraction from Crowdsourced Data

    Science.gov (United States)

    Koswatte, S.; Mcdougall, K.; Liu, X.

    2016-06-01

    Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

  7. SEMANTIC LOCATION EXTRACTION FROM CROWDSOURCED DATA

    Directory of Open Access Journals (Sweden)

    S. Koswatte

    2016-06-01

    Full Text Available Crowdsourced Data (CSD has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network. This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

  8. Semantic Interoperability Almost Without Using The Same Vocabulary: Is It Possible?

    Science.gov (United States)

    Krisnadhi, A. A.

    2016-12-01

    Semantic interoperability, which is a key requirement in realizing cross-repository data integration, is often understood as using the same ontology or vocabulary. Consequently, within a particular domain, one can easily assume that there has to be one unifying domain ontology covering as many vocabulary terms in the domain as possible in order to realize any form of data integration across multiple data sources. Furthermore, the desire to provide very precise definition of those many terms led to the development of huge, foundational and domain ontologies that are comprehensive, but too complicated, restrictive, monolithic, and difficult to use and reuse, which cause common data providers to avoid using them. This problem is especially true in a domain as diverse as geosciences as it is virtually impossible to reach an agreement to the semantics of many terms (e.g., there are hundreds of definitions of forest used throughout the world). To overcome this challenge, modular ontology architecture has emerged in recent years, fueled among others, by advances in the ontology design pattern research. Each ontology pattern models only one key notion. It can act as a small module of a larger ontology. Such a module is developed in such a way that it is largely independent of how other notions in the same domain are modeled. This leads to an increased reusability. Furthermore, an ontology formed out of such modules would have an improved understandability over large, monolithic ontologies. Semantic interoperability in the aforementioned architecture is not achieved by enforcing the use of the same vocabulary, but rather, promoting alignment to the same ontology patterns. In this work, we elaborate how this architecture realizes the above idea. In particular, we describe how multiple data sources with differing perspectives and vocabularies can interoperate through this architecture. Building the solution upon semantic technologies such as Linked Data and the Web Ontology

  9. OpenBiodiv-O: ontology of the OpenBiodiv knowledge management system.

    Science.gov (United States)

    Senderov, Viktor; Simov, Kiril; Franz, Nico; Stoev, Pavel; Catapano, Terry; Agosti, Donat; Sautter, Guido; Morris, Robert A; Penev, Lyubomir

    2018-01-18

    The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy. OpenBiodiv-O introduces classes, properties, and axioms in the domains of scholarly biodiversity publishing and biological taxonomy and aligns them with several important domain ontologies (FaBiO, DoCO, DwC, Darwin-SW, NOMEN, ENVO). By doing so, it bridges the ontological gap across scholarly biodiversity publishing and biological taxonomy and allows for the creation of a Linked Open Dataset (LOD) of biodiversity information (a biodiversity knowledge graph) and enables the creation of the OpenBiodiv Knowledge Management System. A key feature of the ontology is that it is an ontology of the scientific process of biological taxonomy and not of any particular state of knowledge. This feature allows it to express a multiplicity of scientific opinions. The resulting OpenBiodiv knowledge system may gain a high level of trust in the scientific community as it does not force a scientific opinion on its users (e.g. practicing taxonomists, library researchers, etc.), but rather provides the tools for experts to encode different views as science progresses. OpenBiodiv-O provides a conceptual model of the structure of a biodiversity publication and the development of related taxonomic concepts. It also serves as the basis for the OpenBiodiv Knowledge Management System.

  10. Ant-based extraction of rules in simple decision systems over ontological graphs

    Directory of Open Access Journals (Sweden)

    Pancerz Krzysztof

    2015-06-01

    Full Text Available In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA. In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems

  11. Practical experiences for the development of educational sys-tems in the semantic web

    Directory of Open Access Journals (Sweden)

    Mª del Mar Sánchez Vera

    2013-01-01

    Full Text Available Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable and reusable view of a particular application domain. Ontologies can support different activities in educational settings such as organizing course contents, classifying learning objects or assessing learning levels. Consequently, ontologies can become a very useful tool from a pedagogical perspective. This paper focuses on two different experiences where Semantic Web technologies are used in educational settings, the difference between them lying in how knowledge is obtained and represented. On the one hand, the OeLE platform uses ontologies as a support for assessment processes. Such ontologies have to be designed and implemented in semantic languages apt to be used by OeLE. On the other hand, the ENSEMBLE project pursues the development of semantic web applications by creating specific knowledge representations drawn from user needs. Our paper is consequently going to offer an in-depth analysis of the role played by ontologies, showing how they can be used in different ways drawing a comparison between model patterns and examining the ways in which they can complement each other as well as their practical implications

  12. A Lexical-Ontological Resource for Consumer Healthcare

    Science.gov (United States)

    Cardillo, Elena; Serafini, Luciano; Tamilin, Andrei

    In Consumer Healthcare Informatics it is still difficult for laypeople to find, understand and act on health information, due to the persistent communication gap between specialized medical terminology and that used by healthcare consumers. Furthermore, existing clinically-oriented terminologies cannot provide sufficient support when integrated into consumer-oriented applications, so there is a need to create consumer-friendly terminologies reflecting the different ways healthcare consumers express and think about health topics. Following this direction, this work suggests a way to support the design of an ontology-based system that mitigates this gap, using knowledge engineering and semantic web technologies. The system is based on the development of a consumer-oriented medical terminology that will be integrated with other medical domain ontologies and terminologies into a medical ontology repository. This will support consumer-oriented healthcare systems, such as Personal Health Records, by providing many knowledge services to help users in accessing and managing their healthcare data.

  13. A Lexical-Ontological Resource for Consumer Heathcare

    Science.gov (United States)

    Cardillo, Elena

    In Consumer Healthcare Informatics it is still difficult for laypersons to understand and act on health information, due to the persistent communication gap between specialized medical terminology and that used by healthcare consumers. Furthermore, existing clinically-oriented terminologies cannot provide sufficient support when integrated into consumer-oriented applications, so there is a need to create consumer-friendly terminologies reflecting the different ways healthcare consumers express and think about health topics. Following this direction, this work suggests a way to support the design of an ontology-based system that mitigates this gap, using knowledge engineering and Semantic Web technologies. The system is based on the development of a consumer-oriented medical terminology which will be integrated with other existing domain ontologies/terminologies into a medical ontology repository. This will support consumer-oriented healthcare systems by providing many knowledge services to help users in accessing and managing their healthcare data.

  14. Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.

    Science.gov (United States)

    Charlet, J; Darmoni, S J

    2015-08-13

    To summarize the best papers in the field of Knowledge Representation and Management (KRM). A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014. Four articles were selected, two focused on annotation and information retrieval using an ontology. The two others focused mainly on ontologies, one dealing with the usage of a temporal ontology in order to analyze the content of narrative document, one describing a methodology for building multilingual ontologies. Semantic models began to show their efficiency, coupled with annotation tools.

  15. 8th Chinese Conference on The Semantic Web and Web Science

    CERN Document Server

    Du, Jianfeng; Wang, Haofen; Wang, Peng; Ji, Donghong; Pan, Jeff Z; CSWS 2014

    2014-01-01

    This book constitutes the thoroughly refereed papers of the 8th Chinese Conference on The Semantic Web and Web Science, CSWS 2014, held in Wuhan, China, in August 2014. The 22 research papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in topical sections such as ontology reasoning and learning; semantic data generation and management; and semantic technology and applications.

  16. Semantic framework for mapping object-oriented model to semantic web languages.

    Science.gov (United States)

    Ježek, Petr; Mouček, Roman

    2015-01-01

    The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

  17. Ontology of a scene based on Java 3D architecture.

    Directory of Open Access Journals (Sweden)

    Rubén González Crespo

    2009-12-01

    Full Text Available The present article seeks to make an approach to the class hierarchy of a scene built with the architecture Java 3D, to develop an ontology of a scene as from the semantic essential components for the semantic structuring of the Web3D. Java was selected because the language recommended by the W3C Consortium for the Development of the Web3D oriented applications as from X3D standard is Xj3D which compositionof their Schemas is based the architecture of Java3D In first instance identifies the domain and scope of the ontology, defining classes and subclasses that comprise from Java3D architecture and the essential elements of a scene, as its point of origin, the field of rotation, translation The limitation of the scene and the definition of shaders, then define the slots that are declared in RDF as a framework for describing the properties of the classes established from identifying thedomain and range of each class, then develops composition of the OWL ontology on SWOOP Finally, be perform instantiations of the ontology building for a Iconosphere object as from class expressions defined.

  18. Defining Resilience and Vulnerability Based on Ontology Engineering Approach

    Science.gov (United States)

    Kumazawa, T.; Matsui, T.; Endo, A.

    2014-12-01

    It is necessary to reflect the concepts of resilience and vulnerability into the assessment framework of "Human-Environmental Security", but it is also in difficulty to identify the linkage between both concepts because of the difference of the academic community which has discussed each concept. The authors have been developing the ontology which deals with the sustainability of the social-ecological systems (SESs). Resilience and vulnerability are also the concepts in the target world which this ontology covers. Based on this point, this paper aims at explicating the semantic relationship between the concepts of resilience and vulnerability based on ontology engineering approach. For this purpose, we first examine the definitions of resilience and vulnerability which the existing literatures proposed. Second, we incorporate the definitions in the ontology dealing with sustainability of SESs. Finally, we focus on the "Water-Energy-Food Nexus Index" to assess Human-Environmental Security, and clarify how the concepts of resilience and vulnerability are linked semantically through the concepts included in these index items.

  19. Semantic Blogging : Spreading the Semantic Web Meme

    OpenAIRE

    Cayzer, Steve

    2004-01-01

    This paper is about semantic blogging, an application of the semantic web to blogging. The semantic web promises to make the web more useful by endowing metadata with machine processable semantics. Blogging is a lightweight web publishing paradigm which provides a very low barrier to entry, useful syndication and aggregation behaviour, a simple to understand structure and decentralized construction of a rich information network. Semantic blogging builds upon the success and clear network valu...

  20. A DNA-based semantic fusion model for remote sensing data.

    Directory of Open Access Journals (Sweden)

    Heng Sun

    Full Text Available Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  1. A DNA-based semantic fusion model for remote sensing data.

    Science.gov (United States)

    Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

    2013-01-01

    Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  2. F-OWL: An Inference Engine for Semantic Web

    Science.gov (United States)

    Zou, Youyong; Finin, Tim; Chen, Harry

    2004-01-01

    Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining frame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and compare it with other description logic based approaches. We also describe TAGA, a trading agent environment that we have used as a test bed for F-OWL and to explore how multiagent systems can use semantic web concepts and technology.

  3. Extracting Semantic Information from Visual Data: A Survey

    Directory of Open Access Journals (Sweden)

    Qiang Liu

    2016-03-01

    Full Text Available The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.

  4. GIF Video Sentiment Detection Using Semantic Sequence

    Directory of Open Access Journals (Sweden)

    Dazhen Lin

    2017-01-01

    Full Text Available With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs.

  5. The Quest to Solve Problems That Don’t Exist: Thought Artifacts in Contemporary Ontology

    Directory of Open Access Journals (Sweden)

    Kastrup Bernardo

    2017-10-01

    Full Text Available Questions about the nature of reality and consciousness remain unresolved in philosophy today, but not for lack of hypotheses. Ontologies as varied as physicalism, microexperientialism and cosmopsychism enrich the philosophical menu. Each of these ontologies faces a seemingly fundamental problem: under physicalism, for instance, we have the ‘hard problem of consciousness,’ whereas under microexperientialism we have the ‘subject combination problem.’ I argue that these problems are thought artifacts, having no grounding in empirical reality. In a manner akin to semantic paradoxes, they exist only in the internal logico-conceptual structure of their respective ontologies.

  6. A methodology to migrate the gene ontology to a description logic environment using DAML+OIL.

    Science.gov (United States)

    Wroe, C J; Stevens, R; Goble, C A; Ashburner, M

    2003-01-01

    The Gene Ontology Next Generation Project (GONG) is developing a staged methodology to evolve the current representation of the Gene Ontology into DAML+OIL in order to take advantage of the richer formal expressiveness and the reasoning capabilities of the underlying description logic. Each stage provides a step level increase in formal explicit semantic content with a view to supporting validation, extension and multiple classification of the Gene Ontology. The paper introduces DAML+OIL and demonstrates the activity within each stage of the methodology and the functionality gained.

  7. A web ontology for brain trauma patient computer-assisted rehabilitation.

    Science.gov (United States)

    Zikos, Dimitrios; Galatas, George; Metsis, Vangelis; Makedon, Fillia

    2013-01-01

    In this paper we describe CABROnto, which is a web ontology for the semantic representation of the computer assisted brain trauma rehabilitation. This is a novel and emerging domain, since it employs the use of robotic devices, adaptation software and machine learning to facilitate interactive and adaptive rehabilitation care. We used Protégé 4.2 and Protégé-Owl schema editor. The primary goal of this ontology is to enable the reuse of the domain knowledge. CABROnto has nine main classes, more than 50 subclasses, existential and cardinality restrictions. The ontology can be found online at Bioportal.

  8. ROMIE, une approche d'alignement d'ontologies à base d'instances

    OpenAIRE

    Elbyed , Abdeltif

    2009-01-01

    System interoperability is an important issue, widely recognized in information technology intensive organizations and in the research community of information systems. The wide adoption of the World Wide Web to access and distribute information further stresses the need for system interoperability. Initiative solutions like the Semantic Web facilitate the localization and the integration of the data in a more intelligent way via the use of ontologies. The Semantic Web offers a compelling vis...

  9. SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots

    Science.gov (United States)

    Li, Xin; Bilbao, Sonia; Martín-Wanton, Tamara; Bastos, Joaquim; Rodriguez, Jonathan

    2017-01-01

    In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning. PMID:28287468

  10. A Method for Building Personalized Ontology Summaries

    OpenAIRE

    Queiroz-Sousa, Paulo Orlando; Salgado, Ana Carolina; Pires, Carlos Eduardo

    2013-01-01

    In the context of ontology engineering, the ontology understanding is the basis for its further developmentand reuse. One intuitive eective approach to support ontology understanding is the process of ontology summarizationwhich highlights the most important concepts of an ontology. Ontology summarization identies an excerpt from anontology that contains the most relevant concepts and produces an abridged ontology. In this article, we present amethod for summarizing ontologies that represent ...

  11. Using Assertion Capabilities of an OWL-Based Ontology for Query Formulation

    CERN Document Server

    Munir, Kamran; Bloodsworth, Peter; McClatchey, Richard

    2008-01-01

    This paper reports on the development of a framework to assist users in formulating relational queries without requiring a complete knowledge of the information structure and access mechanisms to underlying data sources. The emphasis here is on exploiting the semantic relationships and assertion capabilities of OWL ontologies to assist clinicians in writing complex queries. This has been achieved using both a bottom-up and top-down approaches to build an ontology model to be the repository for complex end user queries. Relational database schemas are mapped into the newly generated ontology schema to reinforce the current domain ontology being developed. One of the key merits of this approach is that it does not require storing data interpretation, with the added advantage of even not storing database instances as part of the domain ontology, especially for systems with huge volume of data.

  12. Research on presentation and query service of geo-spatial data based on ontology

    Science.gov (United States)

    Li, Hong-wei; Li, Qin-chao; Cai, Chang

    2008-10-01

    The paper analyzed the deficiency on presentation and query of geo-spatial data existed in current GIS, discussed the advantages that ontology possessed in formalization of geo-spatial data and the presentation of semantic granularity, taken land-use classification system as an example to construct domain ontology, and described it by OWL; realized the grade level and category presentation of land-use data benefited from the thoughts of vertical and horizontal navigation; and then discussed query mode of geo-spatial data based on ontology, including data query based on types and grade levels, instances and spatial relation, and synthetic query based on types and instances; these methods enriched query mode of current GIS, and is a useful attempt; point out that the key point of the presentation and query of spatial data based on ontology is to construct domain ontology that can correctly reflect geo-concept and its spatial relation and realize its fine formalization description.

  13. SITRUS: Semantic Infrastructure for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kalil A. Bispo

    2015-10-01

    Full Text Available Wireless sensor networks (WSNs are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks, which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS.

  14. MODEL FOR SEMANTICALLY RICH POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    F. Poux

    2017-10-01

    Full Text Available This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  15. Model for Semantically Rich Point Cloud Data

    Science.gov (United States)

    Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

    2017-10-01

    This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  16. A Framework for Automatic Web Service Discovery Based on Semantics and NLP Techniques

    Directory of Open Access Journals (Sweden)

    Asma Adala

    2011-01-01

    Full Text Available As a greater number of Web Services are made available today, automatic discovery is recognized as an important task. To promote the automation of service discovery, different semantic languages have been created that allow describing the functionality of services in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate knowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework that enables semantic Web service discovery based on keywords written in natural language. We describe a novel approach for automatic discovery of semantic Web services which employs Natural Language Processing techniques to match a user request, expressed in natural language, with a semantic Web service description. Additionally, we present an efficient semantic matching technique to compute the semantic distance between ontological concepts.

  17. Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

    Science.gov (United States)

    Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

    In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

  18. An ontology-driven tool for structured data acquisition using Web forms.

    Science.gov (United States)

    Gonçalves, Rafael S; Tu, Samson W; Nyulas, Csongor I; Tierney, Michael J; Musen, Mark A

    2017-08-01

    Structured data acquisition is a common task that is widely performed in biomedicine. However, current solutions for this task are far from providing a means to structure data in such a way that it can be automatically employed in decision making (e.g., in our example application domain of clinical functional assessment, for determining eligibility for disability benefits) based on conclusions derived from acquired data (e.g., assessment of impaired motor function). To use data in these settings, we need it structured in a way that can be exploited by automated reasoning systems, for instance, in the Web Ontology Language (OWL); the de facto ontology language for the Web. We tackle the problem of generating Web-based assessment forms from OWL ontologies, and aggregating input gathered through these forms as an ontology of "semantically-enriched" form data that can be queried using an RDF query language, such as SPARQL. We developed an ontology-based structured data acquisition system, which we present through its specific application to the clinical functional assessment domain. We found that data gathered through our system is highly amenable to automatic analysis using queries. We demonstrated how ontologies can be used to help structuring Web-based forms and to semantically enrich the data elements of the acquired structured data. The ontologies associated with the enriched data elements enable automated inferences and provide a rich vocabulary for performing queries.

  19. ONTOLOGY IN PHARMACY

    Directory of Open Access Journals (Sweden)

    L. Yu. Babintseva

    2015-05-01

    Full Text Available It’s considered ontological models for formalization of knowledge in pharmacy. There is emphasized the view that the possibility of rapid exchange of information in the pharmaceutical industry, it is necessary to create a single information space. This means not only the establishment of uniform standards for the presentation of information on pharmaceutical groups pharmacotherapeutic classifications, but also the creation of a unified and standardized system for the transfer and renewal of knowledge. It is the organization of information in the ontology helps quickly in the future to build expert systems and applications to work with data.

  20. Semantics of data and service registration to advance interdisciplinary information and data access.

    Science.gov (United States)

    Fox, P. P.; McGuinness, D. L.; Raskin, R.; Sinha, A. K.

    2008-12-01

    In developing an application of semantic web methods and technologies to address the integration of heterogeneous and interdisciplinary earth-science datasets, we have developed methodologies for creating rich semantic descriptions (ontologies) of the application domains. We have leveraged and extended where possible existing ontology frameworks such as SWEET. As a result of this semantic approach, we have also utilized ontologic descriptions of key enabling elements of the application, such as the registration of datasets with ontologies at several levels of granularity. This has enabled the location and usage of the data across disciplines. We are also realizing the need to develop similar semantic registration of web service data holdings as well as those provided with community and/or standard markup languages (e.g. GeoSciML). This level of semantic enablement extending beyond domain terms and relations significantly enhances our ability to provide a coherent semantic data framework for data and information systems. Much of this work is on the frontier of technology development and we will present the current and near-future capabilities we are developing. This work arises from the Semantically-Enabled Science Data Integration (SESDI) project, which is an NASA/ESTO/ACCESS-funded project involving the High Altitude Observatory at the National Center for Atmospheric Research (NCAR), McGuinness Associates Consulting, NASA/JPL and Virginia Polytechnic University.

  1. Modular Knowledge Representation and Reasoning in the Semantic Web

    Science.gov (United States)

    Serafini, Luciano; Homola, Martin

    Construction of modular ontologies by combining different modules is becoming a necessity in ontology engineering in order to cope with the increasing complexity of the ontologies and the domains they represent. The modular ontology approach takes inspiration from software engineering, where modularization is a widely acknowledged feature. Distributed reasoning is the other side of the coin of modular ontologies: given an ontology comprising of a set of modules, it is desired to perform reasoning by combination of multiple reasoning processes performed locally on each of the modules. In the last ten years, a number of approaches for combining logics has been developed in order to formalize modular ontologies. In this chapter, we survey and compare the main formalisms for modular ontologies and distributed reasoning in the Semantic Web. We select four formalisms build on formal logical grounds of Description Logics: Distributed Description Logics, ℰ-connections, Package-based Description Logics and Integrated Distributed Description Logics. We concentrate on expressivity and distinctive modeling features of each framework. We also discuss reasoning capabilities of each framework.

  2. Summarization by domain ontology navigation

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2013-01-01

    of the subject. In between these two extremes, conceptual summaries encompass selected concepts derived using background knowledge. We address in this paper an approach where conceptual summaries are provided through a conceptualization as given by an ontology. The ontology guiding the summarization can...... be a simple taxonomy or a generative domain ontology. A domain ontology can be provided by a preanalysis of a domain corpus and can be used to condense improved summaries that better reflects the conceptualization of a given domain....

  3. An ontological system for interoperable spatial generalisation in biodiversity monitoring

    Science.gov (United States)

    Nieland, Simon; Moran, Niklas; Kleinschmit, Birgit; Förster, Michael

    2015-11-01

    Semantic heterogeneity remains a barrier to data comparability and standardisation of results in different fields of spatial research. Because of its thematic complexity, differing acquisition methods and national nomenclatures, interoperability of biodiversity monitoring information is especially difficult. Since data collection methods and interpretation manuals broadly vary there is a need for automatised, objective methodologies for the generation of comparable data-sets. Ontology-based applications offer vast opportunities in data management and standardisation. This study examines two data-sets of protected heathlands in Germany and Belgium which are based on remote sensing image classification and semantically formalised in an OWL2 ontology. The proposed methodology uses semantic relations of the two data-sets, which are (semi-)automatically derived from remote sensing imagery, to generate objective and comparable information about the status of protected areas by utilising kernel-based spatial reclassification. This automatised method suggests a generalisation approach, which is able to generate delineation of Special Areas of Conservation (SAC) of the European biodiversity Natura 2000 network. Furthermore, it is able to transfer generalisation rules between areas surveyed with varying acquisition methods in different countries by taking into account automated inference of the underlying semantics. The generalisation results were compared with the manual delineation of terrestrial monitoring. For the different habitats in the two sites an accuracy of above 70% was detected. However, it has to be highlighted that the delineation of the ground-truth data inherits a high degree of uncertainty, which is discussed in this study.

  4. Biomedical ontologies: toward scientific debate.

    Science.gov (United States)

    Maojo, V; Crespo, J; García-Remesal, M; de la Iglesia, D; Perez-Rey, D; Kulikowski, C

    2011-01-01

    Biomedical ontologies have been very successful in structuring knowledge for many different applications, receiving widespread praise for their utility and potential. Yet, the role of computational ontologies in scientific research, as opposed to knowledge management applications, has not been extensively discussed. We aim to stimulate further discussion on the advantages and challenges presented by biomedical ontologies from a scientific perspective. We review various aspects of biomedical ontologies going beyond their practical successes, and focus on some key scientific questions in two ways. First, we analyze and discuss current approaches to improve biomedical ontologies that are based largely on classical, Aristotelian ontological models of reality. Second, we raise various open questions about biomedical ontologies that require further research, analyzing in more detail those related to visual reasoning and spatial ontologies. We outline significant scientific issues that biomedical ontologies should consider, beyond current efforts of building practical consensus between them. For spatial ontologies, we suggest an approach for building "morphospatial" taxonomies, as an example that could stimulate research on fundamental open issues for biomedical ontologies. Analysis of a large number of problems with biomedical ontologies suggests that the field is very much open to alternative interpretations of current work, and in need of scientific debate and discussion that can lead to new ideas and research directions.

  5. Jigsaw Semantics

    Directory of Open Access Journals (Sweden)

    Paul J. E. Dekker

    2010-12-01

    Full Text Available In the last decade the enterprise of formal semantics has been under attack from several philosophical and linguistic perspectives, and it has certainly suffered from its own scattered state, which hosts quite a variety of paradigms which may seem to be incompatible. It will not do to try and answer the arguments of the critics, because the arguments are often well-taken. The negative conclusions, however, I believe are not. The only adequate reply seems to be a constructive one, which puts several pieces of formal semantics, in particular dynamic semantics, together again. In this paper I will try and sketch an overview of tasks, techniques, and results, which serves to at least suggest that it is possible to develop a coherent overall picture of undeniably important and structural phenomena in the interpretation of natural language. The idea is that the concept of meanings as truth conditions after all provides an excellent start for an integrated study of the meaning and use of natural language, and that an extended notion of goal directed pragmatics naturally complements this picture. None of the results reported here are really new, but we think it is important to re-collect them.ReferencesAsher, Nicholas & Lascarides, Alex. 1998. ‘Questions in Dialogue’. Linguistics and Philosophy 23: 237–309.http://dx.doi.org/10.1023/A:1005364332007Borg, Emma. 2007. ‘Minimalism versus contextualism in semantics’. In Gerhard Preyer & Georg Peter (eds. ‘Context-Sensitivity and Semantic Minimalism’, pp. 339–359. Oxford: Oxford University Press.Cappelen, Herman & Lepore, Ernest. 1997. ‘On an Alleged Connection between Indirect Quotation and Semantic Theory’. Mind and Language 12: pp. 278–296.Cappelen, Herman & Lepore, Ernie. 2005. Insensitive Semantics. Oxford: Blackwell.http://dx.doi.org/10.1002/9780470755792Dekker, Paul. 2002. ‘Meaning and Use of Indefinite Expressions’. Journal of Logic, Language and Information 11: pp. 141–194

  6. Representations of spacetime: Formalism and ontological commitment

    Science.gov (United States)

    Bain, Jonathan Stanley

    This dissertation consists of two parts. The first is on the relation between formalism and ontological commitment in the context of theories of spacetime, and the second is on scientific realism. The first part begins with a look at how the substantivalist/relationist debate over the ontological status of spacetime has been influenced by a particular mathematical formalism, that of tensor analysis on differential manifolds (TADM). This formalism has motivated the substantivalist position known as manifold substantivalism. Chapter 1 focuses on the hole argument which maintains that manifold substantivalism is incompatible with determinism. I claim that the realist motivations underlying manifold substantivalism can be upheld, and the hole argument avoided, by adopting structural realism with respect to spacetime. In this context, this is the claim that it is the structure that spacetime points enter into that warrants belief and not the points themselves. In Chapter 2, an elimination principle is defined by means of which a distinction can be made between surplus structure and essential structure with respect to formulations of a theory in two distinct mathematical formulations and some prior ontological commitments. This principle is then used to demonstrate that manifold points may be considered surplus structure in the formulation of field theories. This suggests that, if we are disposed to read field theories literally, then, at most, it should be the essential structure common to all alternative formulations of such theories that should be taken literally. I also investigate how the adoption of alternative formalisms informs other issues in the philosophy of spacetime. Chapter 3 offers a realist position which takes a semantic moral from the preceding investigation and an epistemic moral from work done on reliability. The semantic moral advises us to read only the essential structure of our theories literally. The epistemic moral shows us that such structure

  7. Semantic Support for Complex Ecosystem Research Environments

    Science.gov (United States)

    Klawonn, M.; McGuinness, D. L.; Pinheiro, P.; Santos, H. O.; Chastain, K.

    2015-12-01

    As ecosystems come under increasing stresses from diverse sources, there is growing interest in research efforts aimed at monitoring, modeling, and improving understanding of ecosystems and protection options. We aimed to provide a semantic infrastructure capable of representing data initially related to one large aquatic ecosystem research effort - the Jefferson project at Lake George. This effort includes significant historical observational data, extensive sensor-based monitoring data, experimental data, as well as model and simulation data covering topics including lake circulation, watershed runoff, lake biome food webs, etc. The initial measurement representation has been centered on monitoring data and related provenance. We developed a human-aware sensor network ontology (HASNetO) that leverages existing ontologies (PROV-O, OBOE, VSTO*) in support of measurement annotations. We explicitly support the human-aware aspects of human sensor deployment and collection activity to help capture key provenance that often is lacking. Our foundational ontology has since been generalized into a family of ontologies and used to create our human-aware data collection infrastructure that now supports the integration of measurement data along with simulation data. Interestingly, we have also utilized the same infrastructure to work with partners who have some more specific needs for specifying the environmental conditions where measurements occur, for example, knowing that an air temperature is not an external air temperature, but of the air temperature when windows are shut and curtains are open. We have also leveraged the same infrastructure to work with partners more interested in modeling smart cities with data feeds more related to people, mobility, environment, and living. We will introduce our human-aware data collection infrastructure, and demonstrate how it uses HASNetO and its supporting SOLR-based search platform to support data integration and semantic browsing

  8. An Ontology-supported Approach for Automatic Chaining of Web Services in Geospatial Knowledge Discovery

    Science.gov (United States)

    di, L.; Yue, P.; Yang, W.; Yu, G.

    2006-12-01

    Recent developments in geospatial semantic Web have shown promise for automatic discovery, access, and use of geospatial Web services to quickly and efficiently solve particular application problems. With the semantic Web technology, it is highly feasible to construct intelligent geospatial knowledge systems that can provide answers to many geospatial application questions. A key challenge in constructing such intelligent knowledge system is to automate the creation of a chain or process workflow that involves multiple services and highly diversified data and can generate the answer to a specific question of users. This presentation discusses an approach for automating composition of geospatial Web service chains by employing geospatial semantics described by geospatial ontologies. It shows how ontology-based geospatial semantics are used for enabling the automatic discovery, mediation, and chaining of geospatial Web services. OWL-S is used to represent the geospatial semantics of individual Web services and the type of the services it belongs to and the type of the data it can handle. The hierarchy and classification of service types are described in the service ontology. The hierarchy and classification of data types are presented in the data ontology. For answering users' geospatial questions, an Artificial Intelligent (AI) planning algorithm is used to construct the service chain by using the service and data logics expressed in the ontologies. The chain can be expressed as a graph with nodes representing services and connection weights representing degrees of semantic matching between nodes. The graph is a visual representation of logical geo-processing path for answering users' questions. The graph can be instantiated to a physical service workflow for execution to generate the answer to a user's question. A prototype system, which includes real world geospatial applications, is implemented to demonstrate the concept and approach.

  9. An ontology approach to comparative phenomics in plants

    KAUST Repository

    Oellrich, Anika

    2015-02-25

    Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. Results: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. Conclusions: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics

  10. An ontology approach to comparative phenomics in plants

    KAUST Repository

    Oellrich, Anika; Walls, Ramona L; Cannon, Ethalinda KS; Cannon, Steven B; Cooper, Laurel; Gardiner, Jack; Gkoutos, Georgios V; Harper, Lisa; He, Mingze; Hoehndorf, Robert; Jaiswal, Pankaj; Kalberer, Scott R; Lloyd, John P; Meinke, David; Menda, Naama; Moore, Laura; Nelson, Rex T; Pujar, Anuradha; Lawrence, Carolyn J; Huala, Eva

    2015-01-01

    Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. Results: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. Conclusions: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics

  11. Type-specific proactive interference in patients with semantic and phonological STM deficits.

    Science.gov (United States)

    Harris, Lara; Olson, Andrew; Humphreys, Glyn

    2014-01-01

    Prior neuropsychological evidence suggests that semantic and phonological components of short-term memory (STM) are functionally and neurologically distinct. The current paper examines proactive interference (PI) from semantic and phonological information in two STM-impaired patients, DS (semantic STM deficit) and AK (phonological STM deficit). In Experiment 1 probe recognition tasks with open and closed sets of stimuli were used. Phonological PI was assessed using nonword items, and semantic and phonological PI was assessed using words. In Experiment 2 phonological and semantic PI was elicited by an item recognition probe test with stimuli that bore phonological and semantic relations to the probes. The data suggested heightened phonological PI for the semantic STM patient, and exaggerated effects of semantic PI in the phonological STM case. The findings are consistent with an account of extremely rapid decay of activated type-specific representations in cases of severely impaired phonological and semantic STM.

  12. The design ontology

    DEFF Research Database (Denmark)

    Storga, Mario; Andreasen, Mogens Myrup; Marjanovic, Dorian

    2010-01-01

    The article presents the research of the nature, building and practical role of a Design Ontology as a potential framework for the more efficient product development (PD) data-, information- and knowledge- description, -explanation, -understanding and -reusing. In the methodology for development ...

  13. Dahlbeck and Pure Ontology

    Science.gov (United States)

    Mackenzie, Jim

    2016-01-01

    This article responds to Johan Dahlbeck's "Towards a pure ontology: Children's bodies and morality" ["Educational Philosophy and Theory," vol. 46 (1), 2014, pp. 8-23 (EJ1026561)]. His arguments from Nietzsche and Spinoza do not carry the weight he supposes, and the conclusions he draws from them about pedagogy would be…

  14. Audit Validation Using Ontologies

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2015-01-01

    Full Text Available Requirements to increase quality audit processes in enterprises are defined. It substantiates the need for assessment and management audit processes using ontologies. Sets of rules, ways to assess the consistency of rules and behavior within the organization are defined. Using ontologies are obtained qualifications that assess the organization's audit. Elaboration of the audit reports is a perfect algorithm-based activity characterized by generality, determinism, reproducibility, accuracy and a well-established. The auditors obtain effective levels. Through ontologies obtain the audit calculated level. Because the audit report is qualitative structure of information and knowledge it is very hard to analyze and interpret by different groups of users (shareholders, managers or stakeholders. Developing ontology for audit reports validation will be a useful instrument for both auditors and report users. In this paper we propose an instrument for validation of audit reports contain a lot of keywords that calculates indicators, a lot of indicators for each key word there is an indicator, qualitative levels; interpreter who builds a table of indicators, levels of actual and calculated levels.

  15. Biomedicine: an ontological dissection.

    Science.gov (United States)

    Baronov, David

    2008-01-01

    Though ubiquitous across the medical social sciences literature, the term "biomedicine" as an analytical concept remains remarkably slippery. It is argued here that this imprecision is due in part to the fact that biomedicine is comprised of three interrelated ontological spheres, each of which frames biomedicine as a distinct subject of investigation. This suggests that, depending upon one's ontological commitment, the meaning of biomedicine will shift. From an empirical perspective, biomedicine takes on the appearance of a scientific enterprise and is defined as a derivative category of Western science more generally. From an interpretive perspective, biomedicine represents a symbolic-cultural expression whose adherence to the principles of scientific objectivity conceals an ideological agenda. From a conceptual perspective, biomedicine represents an expression of social power that reflects structures of power and privilege within capitalist society. No one perspective exists in isolation and so the image of biomedicine from any one presents an incomplete understanding. It is the mutually-conditioning interrelations between these ontological spheres that account for biomedicine's ongoing development. Thus, the ontological dissection of biomedicine that follows, with particular emphasis on the period of its formal crystallization in the latter nineteenth and early twentieth century, is intended to deepen our understanding of biomedicine as an analytical concept across the medical social sciences literature.

  16. Towards a Consistent and Scientifically Accurate Drug Ontology.

    Science.gov (United States)

    Hogan, William R; Hanna, Josh; Joseph, Eric; Brochhausen, Mathias

    2013-01-01

    Our use case for comparative effectiveness research requires an ontology of drugs that enables querying National Drug Codes (NDCs) by active ingredient, mechanism of action, physiological effect, and therapeutic class of the drug products they represent. We conducted an ontological analysis of drugs from the realist perspective, and evaluated existing drug terminology, ontology, and database artifacts from (1) the technical perspective, (2) the perspective of pharmacology and medical science (3) the perspective of description logic semantics (if they were available in Web Ontology Language or OWL), and (4) the perspective of our realism-based analysis of the domain. No existing resource was sufficient. Therefore, we built the Drug Ontology (DrOn) in OWL, which we populated with NDCs and other classes from RxNorm using only content created by the National Library of Medicine. We also built an application that uses DrOn to query for NDCs as outlined above, available at: http://ingarden.uams.edu/ingredients. The application uses an OWL-based description logic reasoner to execute end-user queries. DrOn is available at http://code.google.com/p/dr-on.

  17. Semantic Annotation of Unstructured Documents Using Concepts Similarity

    Directory of Open Access Journals (Sweden)

    Fernando Pech

    2017-01-01

    Full Text Available There is a large amount of information in the form of unstructured documents which pose challenges in the information storage, search, and retrieval. This situation has given rise to several information search approaches. Some proposals take into account the contextual meaning of the terms specified in the query. Semantic annotation technique can help to retrieve and extract information in unstructured documents. We propose a semantic annotation strategy for unstructured documents as part of a semantic search engine. In this proposal, ontologies are used to determine the context of the entities specified in the query. Our strategy for extracting the context is focused on concepts similarity. Each relevant term of the document is associated with an instance in the ontology. The similarity between each of the explicit relationships is measured through the combination of two types of associations: the association between each pair of concepts and the calculation of the weight of the relationships.

  18. Exploring and linking biomedical resources through multidimensional semantic spaces.

    Science.gov (United States)

    Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

    2012-01-25

    The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for

  19. Epistemology and ontology in core ontologies: FOLaw and LRI-Core, two core ontologies for law

    NARCIS (Netherlands)

    Breukers, J.A.P.J.; Hoekstra, R.J.

    2004-01-01

    For more than a decade constructing ontologies for legal domains, we, at the Leibniz Center for Law, felt really the need to develop a core ontology for law that would enable us to re-use the common denominator of the various legal domains. In this paper we present two core ontologies for law. The

  20. Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud

    Directory of Open Access Journals (Sweden)

    Bahar Sateli

    2015-12-01

    Full Text Available Motivation. Finding relevant scientific literature is one of the essential tasks researchers are facing on a daily basis. Digital libraries and web information retrieval techniques provide rapid access to a vast amount of scientific literature. However, no further automated support is available that would enable fine-grained access to the knowledge ‘stored’ in these documents. The emerging domain of Semantic Publishing aims at making scientific knowledge accessible to both humans and machines, by adding semantic annotations to content, such as a publication’s contributions, methods, or application domains. However, despite the promises of better knowledge access, the manual annotation of existing research literature is prohibitively expensive for wide-spread adoption. We argue that a novel combination of three distinct methods can significantly advance this vision in a fully-automated way: (i Natural Language Processing (NLP for Rhetorical Entity (RE detection; (ii Named Entity (NE recognition based on the Linked Open Data (LOD cloud; and (iii automatic knowledge base construction for both NEs and REs using semantic web ontologies that interconnect entities in documents with the machine-readable LOD cloud.Results. We present a complete workflow to transform scientific literature into a semantic knowledge base, based on the W3C standards RDF and RDFS. A text mining pipeline, implemented based on the GATE framework, automatically extracts rhetorical entities of type Claims and Contributions from full-text scientific literature. These REs are further enriched with named entities, represented as URIs to the linked open data cloud, by integrating the DBpedia Spotlight tool into our workflow. Text mining results are stored in a knowledge base through a flexible export process that provides for a dynamic mapping of semantic annotations to LOD vocabularies through rules stored in the knowledge base. We created a gold standard corpus from computer