Query Migration from Object Oriented World to Semantic World

Directory of Open Access Journals (Sweden)

Nassima Soussi

2016-06-01

Full Text Available In the last decades, object-oriented approach was able to take a large share of databases market aiming to design and implement structured and reusable software through the composition of independent elements in order to have programs with a high performance. On the other hand, the mass of information stored in the web is increasing day after day with a vertiginous speed, exposing the currently web faced with the problem of creating a bridge so as to facilitate access to data between different applications and systems as well as to look for relevant and exact information wished by users. In addition, all existing approach of rewriting object oriented languages to SPARQL language rely on models transformation process to guarantee this mapping. All the previous raisons has prompted us to write this paper in order to bridge an important gap between these two heterogeneous worlds (object oriented and semantic web world by proposing the first provably semantics preserving OQLto-SPARQL translation algorithm for each element of OQL Query (SELECT clause, FROM clause, FILTER constraint, implicit/ explicit join and union/intersection SELECT queries.

Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

Science.gov (United States)

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

Optimizing queries in distributed systems

Directory of Open Access Journals (Sweden)

Ion LUNGU

2006-01-01

Full Text Available This research presents the main elements of query optimizations in distributed systems. First, data architecture according with system level architecture in a distributed environment is presented. Then the architecture of a distributed database management system (DDBMS is described on conceptual level followed by the presentation of the distributed query execution steps on these information systems. The research ends with presentation of some aspects of distributed database query optimization and strategies used for that.

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of Cerebrotendinous xanthomatosis.

Science.gov (United States)

Taboada, María; Martínez, Diego; Pilo, Belén; Jiménez-Escrig, Adriano; Robinson, Peter N; Sobrido, María J

2012-07-31

Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction. Due to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies. A framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption. This work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms

Heuristic query optimization for query multiple table and multiple clausa on mobile finance application

Science.gov (United States)

Indrayana, I. N. E.; P, N. M. Wirasyanti D.; Sudiartha, I. KG

2018-01-01

Mobile application allow many users to access data from the application without being limited to space, space and time. Over time the data population of this application will increase. Data access time will cause problems if the data record has reached tens of thousands to millions of records.The objective of this research is to maintain the performance of data execution for large data records. One effort to maintain data access time performance is to apply query optimization method. The optimization used in this research is query heuristic optimization method. The built application is a mobile-based financial application using MySQL database with stored procedure therein. This application is used by more than one business entity in one database, thus enabling rapid data growth. In this stored procedure there is an optimized query using heuristic method. Query optimization is performed on a “Select” query that involves more than one table with multiple clausa. Evaluation is done by calculating the average access time using optimized and unoptimized queries. Access time calculation is also performed on the increase of population data in the database. The evaluation results shown the time of data execution with query heuristic optimization relatively faster than data execution time without using query optimization.

Enabling Incremental Query Re-Optimization.

Science.gov (United States)

Liu, Mengmeng; Ives, Zachary G; Loo, Boon Thau

2016-01-01

As declarative query processing techniques expand to the Web, data streams, network routers, and cloud platforms, there is an increasing need to re-plan execution in the presence of unanticipated performance changes. New runtime information may affect which query plan we prefer to run. Adaptive techniques require innovation both in terms of the algorithms used to estimate costs , and in terms of the search algorithm that finds the best plan. We investigate how to build a cost-based optimizer that recomputes the optimal plan incrementally given new cost information, much as a stream engine constantly updates its outputs given new data. Our implementation especially shows benefits for stream processing workloads. It lays the foundations upon which a variety of novel adaptive optimization algorithms can be built. We start by leveraging the recently proposed approach of formulating query plan enumeration as a set of recursive datalog queries ; we develop a variety of novel optimization approaches to ensure effective pruning in both static and incremental cases. We further show that the lessons learned in the declarative implementation can be equally applied to more traditional optimizer implementations.

Algebra-Based Optimization of XML-Extended OLAP Queries

DEFF Research Database (Denmark)

Yin, Xuepeng; Pedersen, Torben Bach

In today’s OLAP systems, integrating fast changing data, e.g., stock quotes, physically into a cube is complex and time-consuming. The widespread use of XML makes it very possible that this data is available in XML format on the WWW; thus, making XML data logically federated with OLAP systems...... is desirable. This report presents a complete foundation for such OLAP-XML federations. This includes a prototypical query engine, a simplified query semantics based on previous work, and a complete physical algebra which enables precise modeling of the execution tasks of an OLAP-XML query. Effective algebra...

XAL: An algebra for XML query optimization

NARCIS (Netherlands)

Frasincar, F.; Houben, G.J.P.M.; Pau, C.D.; Zhou, Xiaofang

2002-01-01

This paper proposes XAL, an XML ALgebra. Its novelty is based on the simplicity of its data model and its well-defined logical operators, which makes it suitable for composability, optimizability, and semantics definition of a query language for XML data. At the heart of the algebra resides the

A Multi-Query Optimizer for Monet

NARCIS (Netherlands)

S. Manegold (Stefan); A.J. Pellenkoft (Jan); M.L. Kersten (Martin)

2000-01-01

textabstractDatabase systems allow for concurrent use of several applications (and query interfaces). Each application generates an ``optimal'' plan---a sequence of low-level database operators---for accessing the database. The queries posed by users through the same application can be optimized

A multi-query optimizer for Monet

NARCIS (Netherlands)

S. Manegold (Stefan); A.J. Pellenkoft (Jan); M.L. Kersten (Martin)

2000-01-01

textabstractDatabase systems allow for concurrent use of several applications (and query interfaces). Each application generates an ``optimal'' plan---a sequence of low-level database operators---for accessing the database. The queries posed by users through the same application can be optimized

Mining Genotype-Phenotype Associations from Public Knowledge Sources via Semantic Web Querying

Science.gov (United States)

Kiefer, Richard C.; Freimuth, Robert R.; Chute, Christopher G; Pathak, Jyotishman

Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evaluation and analysis is required before such information can be applied and used effectively. PMID:24303249

Mining Genotype-Phenotype Associations from Public Knowledge Sources via Semantic Web Querying.

Science.gov (United States)

Kiefer, Richard C; Freimuth, Robert R; Chute, Christopher G; Pathak, Jyotishman

2013-01-01

Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evaluation and analysis is required before such information can be applied and used effectively.

Query optimization over crowdsourced data

KAUST Repository

Park, Hyunjung; Widom, Jennifer

2013-01-01

Deco is a comprehensive system for answering declarative queries posed over stored relational data together with data obtained on-demand from the crowd. In this paper we describe Deco's cost-based query optimizer, building on Deco's data model

Privacy-Aware Relevant Data Access with Semantically Enriched Search Queries for Untrusted Cloud Storage Services.

Science.gov (United States)

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Lee, Sungyoung; Chung, Tae Choong

2016-01-01

Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify secure outsourced data which contains semantically equivalent information. In addition, trapdoor-based methodologies are confined to pre-defined trapdoors and prevent subscribers from searching outsourced data with arbitrarily defined search criteria. To solve the problem of relevant data access, we have proposed an index-based privacy-aware search methodology that ensures semantic retrieval of data from an untrusted domain. This method ensures oblivious execution of a search query and leverages authorized subscribers to model conjunctive search queries without relying on predefined trapdoors. A security analysis of our proposed methodology shows that, in a conspired attack, unauthorized subscribers and untrusted cloud service providers cannot deduce any information that can lead to the potential loss of data privacy. A computational time analysis on commodity hardware demonstrates that our proposed methodology requires moderate computational resources to model a privacy-aware search query and for its oblivious evaluation on a cloud service provider.

How Good Are Query Optimizers, Really?

NARCIS (Netherlands)

Leis, Viktor; Gubichev, Andrey; Mirchev, Atanas; Boncz, Peter; Kemper, Alfons; Neumann, Thomas

2016-01-01

Finding a good join order is crucial for query performance. In this paper, we introduce the Join Order Benchmark (JOB) and experimentally revisit the main components in the classic query optimizer architecture using a complex, real-world data set and realistic multi-join queries. We investigate the

Data management and query processing in semantic web databases

CERN Document Server

Groppe, Sven

2011-01-01

The Semantic Web, which is intended to establish a machine-understandable Web, is currently changing from being an emerging trend to a technology used in complex real-world applications. A number of standards and techniques have been developed by the World Wide Web Consortium (W3C), e.g., the Resource Description Framework (RDF), which provides a general method for conceptual descriptions for Web resources, and SPARQL, an RDF querying language. Recent examples of large RDF data with billions of facts include the UniProt comprehensive catalog of protein sequence, function and annotation data, t

Querying and Mining Strings Made Easy

KAUST Repository

Sahli, Majed

2017-10-13

With the advent of large string datasets in several scientific and business applications, there is a growing need to perform ad-hoc analysis on strings. Currently, strings are stored, managed, and queried using procedural codes. This limits users to certain operations supported by existing procedural applications and requires manual query planning with limited tuning opportunities. This paper presents StarQL, a generic and declarative query language for strings. StarQL is based on a native string data model that allows StarQL to support a large variety of string operations and provide semantic-based query optimization. String analytic queries are too intricate to be solved on one machine. Therefore, we propose a scalable and efficient data structure that allows StarQL implementations to handle large sets of strings and utilize large computing infrastructures. Our evaluation shows that StarQL is able to express workloads of application-specific tools, such as BLAST and KAT in bioinformatics, and to mine Wikipedia text for interesting patterns using declarative queries. Furthermore, the StarQL query optimizer shows an order of magnitude reduction in query execution time.

A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs

Science.gov (United States)

Ennis, Andrew; Nugent, Chris; Morrow, Philip; Chen, Liming; Ioannidis, George; Stan, Alexandru; Rachev, Preslav

2015-01-01

With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for. PMID:26205265

Query Optimizations over Decentralized RDF Graphs

KAUST Repository

Abdelaziz, Ibrahim; Mansour, Essam; Ouzzani, Mourad; Aboulnaga, Ashraf; Kalnis, Panos

2017-01-01

Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query

Optimizing Temporal Queries: Efficient Handling of Duplicates

DEFF Research Database (Denmark)

Toman, David; Bowman, Ivan Thomas

2001-01-01

, these query languages are implemented by translating temporal queries into standard relational queries. However, the compiled queries are often quite cumbersome and expensive to execute even using state-of-the- art relational products. This paper presents an optimization technique that produces more efficient...... translated SQL queries by taking into account the properties of the encoding used for temporal attributes. For concreteness, this translation technique is presented in the context of SQL/TP; however, these techniques are also applicable to other temporal query languages....

Query Optimizations over Decentralized RDF Graphs

KAUST Repository

Abdelaziz, Ibrahim

2017-05-18

Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query processing over a small number of heterogeneous data sources by utilizing schema information. In the case of schema similarity and interlinks among sources, these approaches cause unnecessary data retrieval and communication, leading to poor scalability and response time. This paper addresses these limitations and presents Lusail, a system for scalable and efficient SPARQL query processing over decentralized graphs. Lusail achieves scalability and low query response time through various optimizations at compile and run times. At compile time, we use a novel locality-aware query decomposition technique that maximizes the number of query triple patterns sent together to a source based on the actual location of the instances satisfying these triple patterns. At run time, we use selectivity-awareness and parallel query execution to reduce network latency and to increase parallelism by delaying the execution of subqueries expected to return large results. We evaluate Lusail using real and synthetic benchmarks, with data sizes up to billions of triples on an in-house cluster and a public cloud. We show that Lusail outperforms state-of-the-art systems by orders of magnitude in terms of scalability and response time.

Answering SPARQL queries modulo RDF Schema with paths

OpenAIRE

Alkhateeb, Faisal; Euzenat, Jérôme

2013-01-01

alkhateeb2013a; SPARQL is the standard query language for RDF graphs. In its strict instantiation, it only offers querying according to the RDF semantics and would thus ignore the semantics of data expressed with respect to (RDF) schemas or (OWL) ontologies. Several extensions to SPARQL have been proposed to query RDF data modulo RDFS, i.e., interpreting the query with RDFS semantics and/or considering external ontologies. We introduce a general framework which allows for expressing query ans...

Optimizing RDF Data Cubes for Efficient Processing of Analytical Queries

DEFF Research Database (Denmark)

Jakobsen, Kim Ahlstrøm; Andersen, Alex B.; Hose, Katja

2015-01-01

data warehouses and data cubes. Today, external data sources are essential for analytics and, as the Semantic Web gains popularity, more and more external sources are available in native RDF. With the recent SPARQL 1.1 standard, performing analytical queries over RDF data sources has finally become...

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

Science.gov (United States)

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

Incremental Query Rewriting with Resolution

Science.gov (United States)

Riazanov, Alexandre; Aragão, Marcelo A. T.

We address the problem of semantic querying of relational databases (RDB) modulo knowledge bases using very expressive knowledge representation formalisms, such as full first-order logic or its various fragments. We propose to use a resolution-based first-order logic (FOL) reasoner for computing schematic answers to deductive queries, with the subsequent translation of these schematic answers to SQL queries which are evaluated using a conventional relational DBMS. We call our method incremental query rewriting, because an original semantic query is rewritten into a (potentially infinite) series of SQL queries. In this chapter, we outline the main idea of our technique - using abstractions of databases and constrained clauses for deriving schematic answers, and provide completeness and soundness proofs to justify the applicability of this technique to the case of resolution for FOL without equality. The proposed method can be directly used with regular RDBs, including legacy databases. Moreover, we propose it as a potential basis for an efficient Web-scale semantic search technology.

A semantic-based approach for querying linked data using natural language

KAUST Repository

Paredes-Valverde, Mario André s; Valencia-Garcí a, Rafael; Rodriguez-Garcia, Miguel Angel; Colomo-Palacios, Ricardo; Alor-Herná ndez, Giner

2016-01-01

The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question's structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users. © The Author(s) 2015.

A semantic-based approach for querying linked data using natural language

KAUST Repository

Paredes-Valverde, Mario Andrés

2016-01-11

The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question\\'s structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users. © The Author(s) 2015.

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases.

Science.gov (United States)

Wollbrett, Julien; Larmande, Pierre; de Lamotte, Frédéric; Ruiz, Manuel

2013-04-15

In recent years, a large amount of "-omics" data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.

Towards Optimal Multi-Dimensional Query Processing with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2005-09-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex, multi-dimensional queries where traditional tree-based indices would not work efficiently. This paper studies strategies for minimizing the access costs for processing multi-dimensional queries using bitmap indices with binning. Innovative features of our algorithm include (a) optimally placing the bin boundaries and (b) dynamically reordering the evaluation of the query terms. In addition, we derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

Robust Optimization of Database Queries

Indian Academy of Sciences (India)

JAYANT

2011-07-06

Jul 6, 2011 ... Based on first-order logic. ○ Edgar ... Cost-based Query Optimizer s choice of execution plan ... Determines the values of goods shipped between nations in a time period select ..... Born: 1881 Elected: 1934 Section: Medicine.

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

Science.gov (United States)

2013-01-01

Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394

Developing A Web-based User Interface for Semantic Information Retrieval

Science.gov (United States)

Berrios, Daniel C.; Keller, Richard M.

2003-01-01

While there are now a number of languages and frameworks that enable computer-based systems to search stored data semantically, the optimal design for effective user interfaces for such systems is still uncle ar. Such interfaces should mask unnecessary query detail from users, yet still allow them to build queries of arbitrary complexity without significant restrictions. We developed a user interface supporting s emantic query generation for Semanticorganizer, a tool used by scient ists and engineers at NASA to construct networks of knowledge and dat a. Through this interface users can select node types, node attribute s and node links to build ad-hoc semantic queries for searching the S emanticOrganizer network.

Design and analysis of stochastic DSS query optimizers in a distributed database system

Directory of Open Access Journals (Sweden)

Manik Sharma

2016-07-01

Full Text Available Query optimization is a stimulating task of any database system. A number of heuristics have been applied in recent times, which proposed new algorithms for substantially improving the performance of a query. The hunt for a better solution still continues. The imperishable developments in the field of Decision Support System (DSS databases are presenting data at an exceptional rate. The massive volume of DSS data is consequential only when it is able to access and analyze by distinctive researchers. Here, an innovative stochastic framework of DSS query optimizer is proposed to further optimize the design of existing query optimization genetic approaches. The results of Entropy Based Restricted Stochastic Query Optimizer (ERSQO are compared with the results of Exhaustive Enumeration Query Optimizer (EAQO, Simple Genetic Query Optimizer (SGQO, Novel Genetic Query Optimizer (NGQO and Restricted Stochastic Query Optimizer (RSQO. In terms of Total Costs, EAQO outperforms SGQO, NGQO, RSQO and ERSQO. However, stochastic approaches dominate in terms of runtime. The Total Costs produced by ERSQO is better than SGQO, NGQO and RGQO by 12%, 8% and 5% respectively. Moreover, the effect of replicating data on the Total Costs of DSS query is also examined. In addition, the statistical analysis revealed a 2-tailed significant correlation between the number of join operations and the Total Costs of distributed DSS query. Finally, in regard to the consistency of stochastic query optimizers, the results of SGQO, NGQO, RSQO and ERSQO are 96.2%, 97.2%, 97.45 and 97.8% consistent respectively.

Research in Mobile Database Query Optimization and Processing

Directory of Open Access Journals (Sweden)

Agustinus Borgy Waluyo

2005-01-01

Full Text Available The emergence of mobile computing provides the ability to access information at any time and place. However, as mobile computing environments have inherent factors like power, storage, asymmetric communication cost, and bandwidth limitations, efficient query processing and minimum query response time are definitely of great interest. This survey groups a variety of query optimization and processing mechanisms in mobile databases into two main categories, namely: (i query processing strategy, and (ii caching management strategy. Query processing includes both pull and push operations (broadcast mechanisms. We further classify push operation into on-demand broadcast and periodic broadcast. Push operation (on-demand broadcast relates to designing techniques that enable the server to accommodate multiple requests so that the request can be processed efficiently. Push operation (periodic broadcast corresponds to data dissemination strategies. In this scheme, several techniques to improve the query performance by broadcasting data to a population of mobile users are described. A caching management strategy defines a number of methods for maintaining cached data items in clients' local storage. This strategy considers critical caching issues such as caching granularity, caching coherence strategy and caching replacement policy. Finally, this survey concludes with several open issues relating to mobile query optimization and processing strategy.

Enhancing Recall in Semantic Querying

DEFF Research Database (Denmark)

Rouces, Jacobo

2013-01-01

lexically and structurally different, which we will introduce in the next section. As RDF graphs from different sources are expected to be linked, the modeling heterogeneities will make the federated graph become sparser and inconsistent. This is detrimental to the recall of SPARQL queries, as the query...

Towards Verbalizing SPARQL Queries in Arabic

Directory of Open Access Journals (Sweden)

I. Al Agha

2016-04-01

Full Text Available With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.

Semantic Query Processing : Estimating Relational Purity

NARCIS (Netherlands)

Kalo, Jan-Christoph; Lofi, C.; Maseli, René Pascal; Balke, Wolf-Tilo; Leyer, M.

2017-01-01

The use of semantic information found in structured knowledge bases has become an integral part of the processing pipeline of modern intelligent in-
formation systems. However, such semantic information is frequently insuffi-cient to capture the rich semantics demanded by the applications, and

Querying XML Data with SPARQL

Science.gov (United States)

Bikakis, Nikos; Gioldasis, Nektarios; Tsinaraki, Chrisa; Christodoulakis, Stavros

SPARQL is today the standard access language for Semantic Web data. In the recent years XML databases have also acquired industrial importance due to the widespread applicability of XML in the Web. In this paper we present a framework that bridges the heterogeneity gap and creates an interoperable environment where SPARQL queries are used to access XML databases. Our approach assumes that fairly generic mappings between ontology constructs and XML Schema constructs have been automatically derived or manually specified. The mappings are used to automatically translate SPARQL queries to semantically equivalent XQuery queries which are used to access the XML databases. We present the algorithms and the implementation of SPARQL2XQuery framework, which is used for answering SPARQL queries over XML databases.

SPARQL Assist language-neutral query composer

Science.gov (United States)

2012-01-01

Background SPARQL query composition is difficult for the lay-person, and even the experienced bioinformatician in cases where the data model is unfamiliar. Moreover, established best-practices and internationalization concerns dictate that the identifiers for ontological terms should be opaque rather than human-readable, which further complicates the task of synthesizing queries manually. Results We present SPARQL Assist: a Web application that addresses these issues by providing context-sensitive type-ahead completion during SPARQL query construction. Ontological terms are suggested using their multi-lingual labels and descriptions, leveraging existing support for internationalization and language-neutrality. Moreover, the system utilizes the semantics embedded in ontologies, and within the query itself, to help prioritize the most likely suggestions. Conclusions To ensure success, the Semantic Web must be easily available to all users, regardless of locale, training, or preferred language. By enhancing support for internationalization, and moreover by simplifying the manual construction of SPARQL queries through the use of controlled-natural-language interfaces, we believe we have made some early steps towards simplifying access to Semantic Web resources. PMID:22373327

SPARQL assist language-neutral query composer.

Science.gov (United States)

McCarthy, Luke; Vandervalk, Ben; Wilkinson, Mark

2012-01-25

SPARQL query composition is difficult for the lay-person, and even the experienced bioinformatician in cases where the data model is unfamiliar. Moreover, established best-practices and internationalization concerns dictate that the identifiers for ontological terms should be opaque rather than human-readable, which further complicates the task of synthesizing queries manually. We present SPARQL Assist: a Web application that addresses these issues by providing context-sensitive type-ahead completion during SPARQL query construction. Ontological terms are suggested using their multi-lingual labels and descriptions, leveraging existing support for internationalization and language-neutrality. Moreover, the system utilizes the semantics embedded in ontologies, and within the query itself, to help prioritize the most likely suggestions. To ensure success, the Semantic Web must be easily available to all users, regardless of locale, training, or preferred language. By enhancing support for internationalization, and moreover by simplifying the manual construction of SPARQL queries through the use of controlled-natural-language interfaces, we believe we have made some early steps towards simplifying access to Semantic Web resources.

Pareto-depth for multiple-query image retrieval.

Science.gov (United States)

Hsiao, Ko-Jen; Calder, Jeff; Hero, Alfred O

2015-02-01

Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.

An Object-Oriented Approach of Keyword Querying over Fuzzy XML

Directory of Open Access Journals (Sweden)

Ting Li

2016-09-01

Full Text Available As the fuzzy data management has become one of the main research topics and directions, the question of how to obtain the useful information by means of keyword query from fuzzy XML documents is becoming a subject of an increasing needed investigation. Considering the keyword query methods on crisp XML documents, smallest lowest common ancestor (SLCA semantics is one of the most widely accepted semantics. When users propose the keyword query on fuzzy XML documents with the SLCA semantics, the query results are always incomplate, with low precision, and with no possibilities values returned. Most of keyword query semantics on XML documents only consider query results matching all keywords, yet users may also be interested in the query results matching partial keywords. To overcome these limitations, in this paper, we investigate how to obtain more comprehensive and meaningful results of keyword querying on fuzzy XML documents. We propose a semantics of object-oriented keyword querying on fuzzy XML documents. First, we introduce the concept of "object tree", analyze different types of matching result object trees and find the "minimum result object trees" which contain all keywords and "result object trees" which contain partial keywords. Then an object-oriented keyword query algorithm ROstack is proposed to obtain the root nodes of these matching result object trees, together with their possibilities. At last, experiments are conducted to verify the effectiveness and efficiency of our proposed algorithm.

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries

OpenAIRE

Vellev, Stoyan

2008-01-01

The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...

A framework for query optimization to support data mining

NARCIS (Netherlands)

S.R. Choenni (Sunil); A.P.J.M. Siebes (Arno)

1996-01-01

textabstractIn order to extract knowledge from databases, data mining algorithms heavily query the databases. Inefficient processing of these queries will inevitably have its impact on the performance of these algorithms, making them less valuable. In this paper, we describe an optimization

Evolutionary Multiobjective Query Workload Optimization of Cloud Data Warehouses

Science.gov (United States)

Dokeroglu, Tansel; Sert, Seyyit Alper; Cinar, Muhammet Serkan

2014-01-01

With the advent of Cloud databases, query optimizers need to find paretooptimal solutions in terms of response time and monetary cost. Our novel approach minimizes both objectives by deploying alternative virtual resources and query plans making use of the virtual resource elasticity of the Cloud. We propose an exact multiobjective branch-and-bound and a robust multiobjective genetic algorithm for the optimization of distributed data warehouse query workloads on the Cloud. In order to investigate the effectiveness of our approach, we incorporate the devised algorithms into a prototype system. Finally, through several experiments that we have conducted with different workloads and virtual resource configurations, we conclude remarkable findings of alternative deployments as well as the advantages and disadvantages of the multiobjective algorithms we propose. PMID:24892048

Processing Incomplete Query Specifications in a Context-Dependent Reasoning Framework

Directory of Open Access Journals (Sweden)

Neli P. Zlatareva

2013-04-01

Full Text Available Search is the most prominent web service, which is about to change dramatically with the transition to the Semantic Web. Semantic Web applications are expected to deal with complex conjunctive queries, and not always such queries can be completely and precisely defined. Current Semantic Web reasoners built upon Description Logics have limited processing power in such environments. We discuss some of their limitations, and show how an alternative logical framework utilizing context-dependent rules can be extended to handle incomplete or imprecise query specifications.

Optimizing queries in SQL Server 2008

Directory of Open Access Journals (Sweden)

Ion LUNGU

2010-05-01

Full Text Available Starting from the need to develop efficient IT systems, we intend to review theoptimization methods and tools that can be used by SQL Server database administratorsand developers of applications based on Microsoft technology, focusing on the latestversion of the proprietary DBMS, SQL Server 2008. We’ll reflect on the objectives tobe considered in improving the performance of SQL Server instances, we will tackle themostly used techniques for analyzing and optimizing queries and we will describe the“Optimize for ad hoc workloads”, “Plan Freezing” and “Optimize for unknown" newoptions, accompanied by relevant code examples.

Performance of Distributed Query Optimization in Client/Server Systems

NARCIS (Netherlands)

Skowronek, J.; Blanken, Henk; Wilschut, A.N.

The design, implementation and performance of an optimizer for a nested query language is considered. The optimizer operates in a client/server environment, in particular an Intranet setting. The paper deals with the scalability challenge by tackling the load of many clients by allocating optimizer

Usage of the Jess Engine, Rules and Ontology to Query a Relational Database

Science.gov (United States)

Bak, Jaroslaw; Jedrzejek, Czeslaw; Falkowski, Maciej

We present a prototypical implementation of a library tool, the Semantic Data Library (SDL), which integrates the Jess (Java Expert System Shell) engine, rules and ontology to query a relational database. The tool extends functionalities of previous OWL2Jess with SWRL implementations and takes full advantage of the Jess engine, by separating forward and backward reasoning. The optimization of integration of all these technologies is an advancement over previous tools. We discuss the complexity of the query algorithm. As a demonstration of capability of the SDL library, we execute queries using crime ontology which is being developed in the Polish PPBW project.

Smart Query Answering for Marine Sensor Data

Directory of Open Access Journals (Sweden)

Paulo de Souza

2011-03-01

Full Text Available We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks.

Smart query answering for marine sensor data.

Science.gov (United States)

Shahriar, Md Sumon; de Souza, Paulo; Timms, Greg

2011-01-01

We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks.

The SQL++ Query Language: Configurable, Unifying and Semi-structured

OpenAIRE

Ong, Kian Win; Papakonstantinou, Yannis; Vernoux, Romain

2014-01-01

NoSQL databases support semi-structured data, typically modeled as JSON. They also provide limited (but expanding) query languages. Their idiomatic, non-SQL language constructs, the many variations, and the lack of formal semantics inhibit deep understanding of the query languages, and also impede progress towards clean, powerful, declarative query languages. This paper specifies the syntax and semantics of SQL++, which is applicable to both JSON native stores and SQL databases. The SQL++ sem...

SCRY: Enabling quantitative reasoning in SPARQL queries

NARCIS (Netherlands)

Meroño-Peñuela, A.; Stringer, Bas; Loizou, Antonis; Abeln, Sanne; Heringa, Jaap

2015-01-01

The inability to include quantitative reasoning in SPARQL queries slows down the application of Semantic Web technology in the life sciences. SCRY, our SPARQL compatible service layer, improves this by executing services at query time and making their outputs query-accessible, generating RDF data on

Applying GA for Optimizing the User Query in Image and Video Retrieval

OpenAIRE

Ehsan Lotfi

2014-01-01

In an information retrieval system, the query can be made by user sketch. The new method presented here, optimizes the user sketch and applies the optimized query to retrieval the information. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extraction. To optimize the retrieval process, one stage of retrieval is performed by the user sketch. The retrieval criterion is based on the proposed distance met...

EquiX-A Search and Query Language for XML.

Science.gov (United States)

Cohen, Sara; Kanza, Yaron; Kogan, Yakov; Sagiv, Yehoshua; Nutt, Werner; Serebrenik, Alexander

2002-01-01

Describes EquiX, a search language for XML that combines querying with searching to query the data and the meta-data content of Web pages. Topics include search engines; a data model for XML documents; search query syntax; search query semantics; an algorithm for evaluating a query on a document; and indexing EquiX queries. (LRW)

Data Cleaning and Semantic Improvement in Biological Databases

Directory of Open Access Journals (Sweden)

Apiletti Daniele

2006-12-01

Full Text Available Public genomic and proteomic databases can be affected by a variety of errors. These errors may involve either the description or the meaning of data (namely, syntactic or semantic errors. We focus our analysis on the detection of semantic errors, in order to verify the accuracy of the stored information. In particular, we address the issue of data constraints and functional dependencies among attributes in a given relational database. Constraints and dependencies show semantics among attributes in a database schema and their knowledge may be exploited to improve data quality and integration in database design, and to perform query optimization and dimensional reduction.

A Streams-Based Framework for Defining Location-Based Queries

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Xuegang, Huang

2007-01-01

n infrastructure is emerging that supports the delivery of on-line, location-enabled services to mobile users. Such services involve novel database queries, and the database research community is quite active in proposing techniques for the efficient processing of such queries. In parallel to this......, the management of data streams has become an active area of research. While most research in mobile services concerns performance issues, this paper aims to establish a formal framework for defining the semantics of queries encountered in mobile services, most notably the so-called continuous queries...... that are particularly relevant in this context. Rather than inventing an entirely new framework, the paper proposes a framework that builds on concepts from data streams and temporal databases. Definitions of example queries demonstrates how the framework enables clear formulation of query semantics and the comparison...

Federated query processing for the semantic web

CERN Document Server

Buil-Aranda, C

2014-01-01

During the last years, the amount of RDF data has increased exponentially over the Web, exposed via SPARQL endpoints. These SPARQL endpoints allow users to direct SPARQL queries to the RDF data. Federated SPARQL query processing allows to query several of these RDF databases as if they were a single one, integrating the results from all of them. This is a key concept in the Web of Data and it is also a hot topic in the community. Besides of that, the W3C SPARQL-WG has standardized it in the new Recommendation SPARQL 1.1.This book provides a formalisation of the W3C proposed recommendation. Thi

Towards Intelligible Query Processing in Relevance Feedback-Based Image Retrieval Systems

OpenAIRE

Mohammed, Belkhatir

2008-01-01

We have specified within the scope of this paper a framework combining semantics and relational (spatial) characterizations within a coupled architecture in order to address the semantic gap. This framework is instantiated by an operational model based on a sound logic-based formalism, allowing to define a representation for image documents and a matching function to compare index and query structures. We have specified a query framework coupling keyword-based querying with a relevance feedba...

Optimizing Cost of Continuous Overlapping Queries over Data Streams by Filter Adaption

KAUST Repository

Xie, Qing

2016-01-12

The problem we aim to address is the optimization of cost management for executing multiple continuous queries on data streams, where each query is defined by several filters, each of which monitors certain status of the data stream. Specially the filter can be shared by different queries and expensive to evaluate. The conventional objective for such a problem is to minimize the overall execution cost to solve all queries, by planning the order of filter evaluation in shared strategy. However, in streaming scenario, the characteristics of data items may change in process, which can bring some uncertainty to the outcome of individual filter evaluation, and affect the plan of query execution as well as the overall execution cost. In our work, considering the influence of the uncertain variation of data characteristics, we propose a framework to deal with the dynamic adjustment of filter ordering for query execution on data stream, and focus on the issues of cost management. By incrementally monitoring and analyzing the results of filter evaluation, our proposed approach can be effectively adaptive to the varied stream behavior and adjust the optimal ordering of filter evaluation, so as to optimize the execution cost. In order to achieve satisfactory performance and efficiency, we also discuss the trade-off between the adaptivity of our framework and the overhead incurred by filter adaption. The experimental results on synthetic and two real data sets (traffic and multimedia) show that our framework can effectively reduce and balance the overall query execution cost and keep high adaptivity in streaming scenario.

Optimizing Cost of Continuous Overlapping Queries over Data Streams by Filter Adaption

KAUST Repository

Xie, Qing; Zhang, Xiangliang; Li, Zhixu; Zhou, Xiaofang

2016-01-01

The problem we aim to address is the optimization of cost management for executing multiple continuous queries on data streams, where each query is defined by several filters, each of which monitors certain status of the data stream. Specially

Evaluating XML-Extended OLAP Queries Based on a Physical Algebra

DEFF Research Database (Denmark)

Yin, Xuepeng; Pedersen, Torben Bach

2006-01-01

. In this paper, we extend previous work on the logical federation of OLAP and XML data sources by presenting a simplified query semantics, a physical query algebra and a robust OLAP-XML query engine as well as the query evaluation techniques. Performance experiments with a prototypical implementation suggest...

Querying Workflow Logs

Directory of Open Access Journals (Sweden)

Yan Tang

2018-01-01

Full Text Available A business process or workflow is an assembly of tasks that accomplishes a business goal. Business process management is the study of the design, configuration/implementation, enactment and monitoring, analysis, and re-design of workflows. The traditional methodology for the re-design and improvement of workflows relies on the well-known sequence of extract, transform, and load (ETL, data/process warehousing, and online analytical processing (OLAP tools. In this paper, we study the ad hoc queryiny of process enactments for (data-centric business processes, bypassing the traditional methodology for more flexibility in querying. We develop an algebraic query language based on “incident patterns” with four operators inspired from Business Process Model and Notation (BPMN representation, allowing the user to formulate ad hoc queries directly over workflow logs. A formal semantics of this query language, a preliminary query evaluation algorithm, and a group of elementary properties of the operators are provided.

Processing of extreme moving-object update and query workloads in main memory

DEFF Research Database (Denmark)

Sidlauskas, Darius; Saltenis, Simonas; Jensen, Christian S.

2014-01-01

traditional transaction processing in the context of our target domain and propose new semantics that enable a high degree of parallelism and ensure up-to-date query results. We define the new semantics for range and k-nearest neighbor queries. Then, we present a main-memory indexing technique called parallel...... grid that implements the proposed semantics as well as two other variants supporting different semantics. This enables us to quantify the effects that different degrees of consistency have on performance. We also present an alternative time-partitioning approach. Empirical studies with the above...

Querying Sentiment Development over Time

DEFF Research Database (Denmark)

Andreasen, Troels; Christiansen, Henning; Have, Christian Theil

2013-01-01

A new language is introduced for describing hypotheses about fluctuations of measurable properties in streams of timestamped data, and as prime example, we consider trends of emotions in the constantly flowing stream of Twitter messages. The language, called EmoEpisodes, has a precise semantics...... that measures how well a hypothesis characterizes a given time interval; the semantics is parameterized so it can be adjusted to different views of the data. EmoEpisodes is extended to a query language with variables standing for unknown topics and emotions, and the query-answering mechanism will return...... instantiations for topics and emotions as well as time intervals that provide the largest deflections in this measurement. Experiments are performed on a selection of Twitter data to demonstrates the usefulness of the approach....

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.

A Query Cache Tool for Optimizing Repeatable and Parallel OLAP Queries

Science.gov (United States)

Santos, Ricardo Jorge; Bernardino, Jorge

On-line analytical processing against data warehouse databases is a common form of getting decision making information for almost every business field. Decision support information oftenly concerns periodic values based on regular attributes, such as sales amounts, percentages, most transactioned items, etc. This means that many similar OLAP instructions are periodically repeated, and simultaneously, between the several decision makers. Our Query Cache Tool takes advantage of previously executed queries, storing their results and the current state of the data which was accessed. Future queries only need to execute against the new data, inserted since the queries were last executed, and join these results with the previous ones. This makes query execution much faster, because we only need to process the most recent data. Our tool also minimizes the execution time and resource consumption for similar queries simultaneously executed by different users, putting the most recent ones on hold until the first finish and returns the results for all of them. The stored query results are held until they are considered outdated, then automatically erased. We present an experimental evaluation of our tool using a data warehouse based on a real-world business dataset and use a set of typical decision support queries to discuss the results, showing a very high gain in query execution time.

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.

High-performance analysis of filtered semantic graphs

OpenAIRE

Buluç, A; Fox, A; Gilbert, JR; Kamil, S; Lugowski, A; Oliker, L; Williams, S

2012-01-01

High performance is a crucial consideration when executing a complex analytic query on a massive semantic graph. In a semantic graph, vertices and edges carry \\attributes" of various types. Analytic queries on semantic graphs typically depend on the values of these attributes; thus, the computation must either view the graph through a filter that passes only those individual vertices and edges of interest, or else must first materialize a subgraph or subgraphs consisting of only the vertices ...

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.

A SURVEY ON OPTIMIZATION APPROACHES TO SEMANTIC SERVICE DISCOVERY TOWARDS AN INTEGRATED SOLUTION

Directory of Open Access Journals (Sweden)

Chellammal Surianarayanan

2012-07-01

Full Text Available The process of semantic service discovery using an ontology reasoner such as Pellet is time consuming. This restricts the usage of web services in real time applications having dynamic composition requirements. As performance of semantic service discovery is crucial in service composition, it should be optimized. Various optimization methods are being proposed to improve the performance of semantic discovery. In this work, we investigate the existing optimization methods and broadly classify optimization mechanisms into two categories, namely optimization by efficient reasoning and optimization by efficient matching. Optimization by efficient matching is further classified into subcategories such as optimization by clustering, optimization by inverted indexing, optimization by caching, optimization by hybrid methods, optimization by efficient data structures and optimization by efficient matching algorithms. With a detailed study of different methods, an integrated optimization infrastructure along with matching method has been proposed to improve the performance of semantic matching component. To achieve better optimization the proposed method integrates the effects of caching, clustering and indexing. Theoretical aspects of performance evaluation of the proposed method are discussed.

Evaluating XML-Extended OLAP Queries Based on a Physical Algebra

DEFF Research Database (Denmark)

Yin, Xuepeng; Pedersen, Torben Bach

2004-01-01

is desirable. In this paper, we extend previous work on the logical federation of OLAP and XML data sources by presenting a simplified query semantics,a physical query algebra and a robust OLAP-XML query engine.Performance experiments with a prototypical implementation suggest that the performance for OLAP...

Flexible Query Answering Systems

DEFF Research Database (Denmark)

This book constitutes the refereed proceedings of the 10th International Conference on Flexible Query Answering Systems, FQAS 2013, held in Granada, Spain, in September 2013. The 59 full papers included in this volume were carefully reviewed and selected from numerous submissions. The papers...... are organized in a general session train and a parallel special session track. The general session train covers the following topics: querying-answering systems; semantic technology; patterns and classification; personalization and recommender systems; searching and ranking; and Web and human...

Adaptive and Optimized RDF Query Interface for Distributed WFS Data

Directory of Open Access Journals (Sweden)

Tian Zhao

2017-04-01

Full Text Available Web Feature Service (WFS is a protocol for accessing geospatial data stores such as databases and Shapefiles over the Web. However, WFS does not provide direct access to data distributed in multiple servers. In addition, WFS features extracted from their original sources are not convenient for user access due to the lack of connection to high-level concepts. Users are facing the choices of either querying each WFS server first and then integrating the results, or converting the data from all WFS servers to a more expressive format such as RDF (Resource Description Framework and then querying the integrated data. The first choice requires additional programming while the second choice is not practical for large or frequently updated datasets. The new contribution of this paper is that we propose a novel adaptive and optimized RDF query interface to overcome the aforementioned limitation. Specifically, in this paper, we propose a novel algorithm to query and synthesize distributed WFS data through an RDF query interface, where users can specify data requests to multiple WFS servers using a single RDF query. Users can also define a simple configuration to associate WFS feature types, attributes, and values with RDF classes, properties, and values so that user queries can be written using a more uniform and informative vocabulary. The algorithm translates each RDF query written in SPARQL-like syntax to multiple WFS GetFeature requests, and then converts and integrates the multiple WFS results to get the answers to the original query. The generated GetFeature requests are sent asynchronously and simultaneously to WFS servers to take advantage of the server parallelism. The results of each GetFeature request are cached to improve query response time for subsequent queries that involve one or more of the cached requests. A JavaScript-based prototype is implemented and experimental results show that the query response time can be greatly reduced through

Counting, Enumerating and Sampling of Execution Plans in a Cost-Based Query Optimizer

NARCIS (Netherlands)

F. Waas; C.A. Galindo-Legaria

2000-01-01

textabstractTesting an SQL database system by running large sets of deterministic or stochastic SQL statements is common practice in commercial database development. However, code defects often remain undetected as the query optimizer's choice of an execution plan is not only depending on the query

Video Stream Retrieval of Unseen Queries using Semantic Memory

NARCIS (Netherlands)

Cappallo, S.; Mensink, T.; Snoek, C.G.M.; Wilson, R.C.; Hancock, E.R.; Smith, W.A.P.

2016-01-01

Retrieval of live, user-broadcast video streams is an under-addressed and increasingly relevant challenge. The on-line nature of the problem requires temporal evaluation and the unforeseeable scope of potential queries motivates an approach which can accommodate arbitrary search queries. To account

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

Academic Program Administration via Semantic Web – A Case Study

OpenAIRE

Qurban A Memon; Shakeel A. Khoja

2009-01-01

Generally, administrative systems in an academic environment are disjoint and support independent queries. The objective in this work is to semantically connect these independent systems to provide support to queries run on the integrated platform. The proposed framework, by enriching educational material in the legacy systems, provides a value-added semantics layer where activities such as annotation, query and reasoning can be carried out to support management requirements. We discuss the d...

AQBE — QBE Style Queries for Archetyped Data

Science.gov (United States)

Sachdeva, Shelly; Yaginuma, Daigo; Chu, Wanming; Bhalla, Subhash

Large-scale adoption of electronic healthcare applications requires semantic interoperability. The new proposals propose an advanced (multi-level) DBMS architecture for repository services for health records of patients. These also require query interfaces at multiple levels and at the level of semi-skilled users. In this regard, a high-level user interface for querying the new form of standardized Electronic Health Records system has been examined in this study. It proposes a step-by-step graphical query interface to allow semi-skilled users to write queries. Its aim is to decrease user effort and communication ambiguities, and increase user friendliness.

Temporal Representation in Semantic Graphs

Energy Technology Data Exchange (ETDEWEB)

Levandoski, J J; Abdulla, G M

2007-08-07

A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

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.

Graph Mining Meets the Semantic Web

Energy Technology Data Exchange (ETDEWEB)

Lee, Sangkeun (Matt) [ORNL; Sukumar, Sreenivas R [ORNL; Lim, Seung-Hwan [ORNL

2015-01-01

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.

Optimal Planar Orthogonal Skyline Counting Queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Larsen, Kasper Green

2014-01-01

counting queries, i.e. given a query rectangle R to report the size of the skyline of P\\cap R. We present a data structure for storing n points with integer coordinates having query time O(lg n/lglg n) and space usage O(n). The model of computation is a unit cost RAM with logarithmic word size. We prove...

A Semantic-Based Indexing for Indoor Moving Objects

OpenAIRE

Tingting Ben; Xiaolin Qin; Ning Wang

2014-01-01

The increasing availability of indoor positioning, driven by techniques like RFID, Bluetooth, and smart phones, enables a variety of indoor location-based services (LBSs). Efficient queries based on semantic-constraint in indoor spaces play an important role in supporting and boosting LBSs. However, the existing indoor index techniques cannot support these semantic constraints-based queries. To solve this problem, this paper addresses the challenge of indexing moving objects in indoor spaces,...

Recommendation Sets and Choice Queries

DEFF Research Database (Denmark)

Viappiani, Paolo Renato; Boutilier, Craig

2011-01-01

Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query users about their preferences and offer recommendations based on the system's belief about the user's utility function. We analyze the connection between...... the problem of generating optimal recommendation sets and the problem of generating optimal choice queries, considering both Bayesian and regret-based elicitation. Our results show that, somewhat surprisingly, under very general circumstances, the optimal recommendation set coincides with the optimal query....

Semantic Complex Event Processing over End-to-End Data Flows

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi [University of Southern California; Simmhan, Yogesh; Prasanna, Viktor K.

2012-04-01

Emerging Complex Event Processing (CEP) applications in cyber physical systems like SmartPower Grids present novel challenges for end-to-end analysis over events, flowing from heterogeneous information sources to persistent knowledge repositories. CEP for these applications must support two distinctive features - easy specification patterns over diverse information streams, and integrated pattern detection over realtime and historical events. Existing work on CEP has been limited to relational query patterns, and engines that match events arriving after the query has been registered. We propose SCEPter, a semantic complex event processing framework which uniformly processes queries over continuous and archived events. SCEPteris built around an existing CEP engine with innovative support for semantic event pattern specification and allows their seamless detection over past, present and future events. Specifically, we describe a unified semantic query model that can operate over data flowing through event streams to event repositories. Compile-time and runtime semantic patterns are distinguished and addressed separately for efficiency. Query rewriting is examined and analyzed in the context of temporal boundaries that exist between event streams and their repository to avoid duplicate or missing results. The design and prototype implementation of SCEPterare analyzed using latency and throughput metrics for scenarios from the Smart Grid domain.

A natural language interface plug-in for cooperative query answering in biological databases.

Science.gov (United States)

Jamil, Hasan M

2012-06-11

One of the many unique features of biological databases is that the mere existence of a ground data item is not always a precondition for a query response. It may be argued that from a biologist's standpoint, queries are not always best posed using a structured language. By this we mean that approximate and flexible responses to natural language like queries are well suited for this domain. This is partly due to biologists' tendency to seek simpler interfaces and partly due to the fact that questions in biology involve high level concepts that are open to interpretations computed using sophisticated tools. In such highly interpretive environments, rigidly structured databases do not always perform well. In this paper, our goal is to propose a semantic correspondence plug-in to aid natural language query processing over arbitrary biological database schema with an aim to providing cooperative responses to queries tailored to users' interpretations. Natural language interfaces for databases are generally effective when they are tuned to the underlying database schema and its semantics. Therefore, changes in database schema become impossible to support, or a substantial reorganization cost must be absorbed to reflect any change. We leverage developments in natural language parsing, rule languages and ontologies, and data integration technologies to assemble a prototype query processor that is able to transform a natural language query into a semantically equivalent structured query over the database. We allow knowledge rules and their frequent modifications as part of the underlying database schema. The approach we adopt in our plug-in overcomes some of the serious limitations of many contemporary natural language interfaces, including support for schema modifications and independence from underlying database schema. The plug-in introduced in this paper is generic and facilitates connecting user selected natural language interfaces to arbitrary databases using a

Secure Skyline Queries on Cloud Platform.

Science.gov (United States)

Liu, Jinfei; Yang, Juncheng; Xiong, Li; Pei, Jian

2017-04-01

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposed solutions.

Towards Hybrid Online On-Demand Querying of Realtime Data with Stateful Complex Event Processing

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor K.

2013-10-09

Emerging Big Data applications in areas like e-commerce and energy industry require both online and on-demand queries to be performed over vast and fast data arriving as streams. These present novel challenges to Big Data management systems. Complex Event Processing (CEP) is recognized as a high performance online query scheme which in particular deals with the velocity aspect of the 3-V’s of Big Data. However, traditional CEP systems do not consider data variety and lack the capability to embed ad hoc queries over the volume of data streams. In this paper, we propose H2O, a stateful complex event processing framework, to support hybrid online and on-demand queries over realtime data. We propose a semantically enriched event and query model to address data variety. A formal query algebra is developed to precisely capture the stateful and containment semantics of online and on-demand queries. We describe techniques to achieve the interactive query processing over realtime data featured by efficient online querying, dynamic stream data persistence and on-demand access. The system architecture is presented and the current implementation status reported.

Semantic concept-enriched dependence model for medical information retrieval.

Science.gov (United States)

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

Regular paths in SparQL: querying the NCI Thesaurus.

Science.gov (United States)

Detwiler, Landon T; Suciu, Dan; Brinkley, James F

2008-11-06

OWL, the Web Ontology Language, provides syntax and semantics for representing knowledge for the semantic web. Many of the constructs of OWL have a basis in the field of description logics. While the formal underpinnings of description logics have lead to a highly computable language, it has come at a cognitive cost. OWL ontologies are often unintuitive to readers lacking a strong logic background. In this work we describe GLEEN, a regular path expression library, which extends the RDF query language SparQL to support complex path expressions over OWL and other RDF-based ontologies. We illustrate the utility of GLEEN by showing how it can be used in a query-based approach to defining simpler, more intuitive views of OWL ontologies. In particular we show how relatively simple GLEEN-enhanced SparQL queries can create views of the OWL version of the NCI Thesaurus that match the views generated by the web-based NCI browser.

Algebraic Optimization of Recursive Database Queries

DEFF Research Database (Denmark)

Hansen, Michael Reichhardt

1988-01-01

Queries are expressed by relational algebra expressions including a fixpoint operation. A condition is presented under which a natural join commutes with a fixpoint operation. This condition is a simple check of attribute sets of sub-expressions of the query. The work may be considered a generali......Queries are expressed by relational algebra expressions including a fixpoint operation. A condition is presented under which a natural join commutes with a fixpoint operation. This condition is a simple check of attribute sets of sub-expressions of the query. The work may be considered...... a generalization of Aho and Ullman, (1979). The result is interpreted in function free logic database terms as a transformation of the recursively defined predicate involving: (a) elimination of an argument, and (b) propagation of selections (instantiations) to the extensionally defined predicates. A collection...

Practical querying of temporal data via OWL 2 QL and SQL: 2011

CSIR Research Space (South Africa)

Klarman, S

2013-12-01

Full Text Available We develop a practical approach to querying temporal data stored in temporal SQL:2011 databases through the semantic layer of OWL 2 QL ontologies. An interval-based temporal query language (TQL), which we propose for this task, is defined via...

Indexing for summary queries

DEFF Research Database (Denmark)

Yi, Ke; Wang, Lu; Wei, Zhewei

2014-01-01

), of a particular attribute of these records. Aggregation queries are especially useful in business intelligence and data analysis applications where users are interested not in the actual records, but some statistics of them. They can also be executed much more efficiently than reporting queries, by embedding...... returned by reporting queries. In this article, we design indexing techniques that allow for extracting a statistical summary of all the records in the query. The summaries we support include frequent items, quantiles, and various sketches, all of which are of central importance in massive data analysis....... Our indexes require linear space and extract a summary with the optimal or near-optimal query cost. We illustrate the efficiency and usefulness of our designs through extensive experiments and a system demonstration....

An algorithm to transform natural language into SQL queries for relational databases

Directory of Open Access Journals (Sweden)

Garima Singh

2016-09-01

Full Text Available Intelligent interface, to enhance efficient interactions between user and databases, is the need of the database applications. Databases must be intelligent enough to make the accessibility faster. However, not every user familiar with the Structured Query Language (SQL queries as they may not aware of structure of the database and they thus require to learn SQL. So, non-expert users need a system to interact with relational databases in their natural language such as English. For this, Database Management System (DBMS must have an ability to understand Natural Language (NL. In this research, an intelligent interface is developed using semantic matching technique which translates natural language query to SQL using set of production rules and data dictionary. The data dictionary consists of semantics sets for relations and attributes. A series of steps like lower case conversion, tokenization, speech tagging, database element and SQL element extraction is used to convert Natural Language Query (NLQ to SQL Query. The transformed query is executed and the results are obtained by the user. Intelligent Interface is the need of database applications to enhance efficient interaction between user and DBMS.

Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases

Directory of Open Access Journals (Sweden)

Yingqi Wang

2017-01-01

Full Text Available Due to the ambiguity and impreciseness of keyword query in relational databases, the research on keyword query expansion has attracted wide attention. Existing query expansion methods expose users’ query intention to a certain extent, but most of them cannot balance the precision and recall. To address this problem, a novel two-step query expansion approach is proposed based on query recommendation and query interpretation. First, a probabilistic recommendation algorithm is put forward by constructing a term similarity matrix and Viterbi model. Second, by using the translation algorithm of triples and construction algorithm of query subgraphs, query keywords are translated to query subgraphs with structural and semantic information. Finally, experimental results on a real-world dataset demonstrate the effectiveness and rationality of the proposed method.

Towards A Streams-Based Framework for Defining Location-Based Queries

DEFF Research Database (Denmark)

Huang, Xuegang; Jensen, Christian S.

2004-01-01

An infrastructure is emerging that supports the delivery of on-line, location-enabled services to mobile users. Such services involve novel database queries, and the database research community is quite active in proposing techniques for the effi- cient processing of such queries. In parallel...... to this, the management of data streams has become an active area of research. While most research in mobile services concerns performance issues, this paper aims to establish a formal framework for defining the semantics of queries encountered in mobile services, most notably the so-called continuous...... queries that are particularly relevant in this context. Rather than inventing an entirely new framework, the paper proposes a framework that builds on concepts from data streams and temporal databases. Definitions of example queries demonstrates how the framework enables clear formulation of query...

EFFECTIVELY SEARCHING SPECIMEN AND OBSERVATION DATA WITH TOQE, THE THESAURUS OPTIMIZED QUERY EXPANDER

Directory of Open Access Journals (Sweden)

Anton Güntsch

2009-09-01

Full Text Available Today’s specimen and observation data portals lack a flexible mechanism, able to link up thesaurus-enabled data sources such as taxonomic checklist databases and expand user queries to related terms, significantly enhancing result sets. The TOQE system (Thesaurus Optimized Query Expander is a REST-like XML web-service implemented in Python and designed for this purpose. Acting as an interface between portals and thesauri, TOQE allows the implementation of specialized portal systems with a set of thesauri supporting its specific focus. It is both easy to use for portal programmers and easy to configure for thesaurus database holders who want to expose their system as a service for query expansions. Currently, TOQE is used in four specimen and observation data portals. The documentation is available from http://search.biocase.org/toqe/.

Introducing glycomics data into the Semantic Web

Science.gov (United States)

2013-01-01

Background Glycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as “switches” that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases. Results In order to implement support for the Semantic Web most efficiently for glycomics research, the developers of major glycomics databases agreed on a minimal standard for representing glycan structure and annotation information using RDF (Resource Description Framework). Moreover, all of the participants implemented this standard prototype and generated preliminary RDF versions of their data. To test the utility of the converted data, all of the data sets were uploaded into a Virtuoso triple store, and several SPARQL queries were tested as “proofs-of-concept” to illustrate the utility of the Semantic Web in querying across databases which were originally difficult to implement. Conclusions We were able to successfully retrieve information by linking UniCarbKB, GlycomeDB and JCGGDB in a single SPARQL query to obtain our target information. We also tested queries linking UniProt with GlycoEpitope as well as lectin data with GlycomeDB through PDB. As a result, we have been able to link proteomics data with glycomics data through the implementation of Semantic Web technologies, allowing for more flexible queries across these domains. PMID:24280648

Introducing glycomics data into the Semantic Web.

Science.gov (United States)

Aoki-Kinoshita, Kiyoko F; Bolleman, Jerven; Campbell, Matthew P; Kawano, Shin; Kim, Jin-Dong; Lütteke, Thomas; Matsubara, Masaaki; Okuda, Shujiro; Ranzinger, Rene; Sawaki, Hiromichi; Shikanai, Toshihide; Shinmachi, Daisuke; Suzuki, Yoshinori; Toukach, Philip; Yamada, Issaku; Packer, Nicolle H; Narimatsu, Hisashi

2013-11-26

Glycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as "switches" that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases. In order to implement support for the Semantic Web most efficiently for glycomics research, the developers of major glycomics databases agreed on a minimal standard for representing glycan structure and annotation information using RDF (Resource Description Framework). Moreover, all of the participants implemented this standard prototype and generated preliminary RDF versions of their data. To test the utility of the converted data, all of the data sets were uploaded into a Virtuoso triple store, and several SPARQL queries were tested as "proofs-of-concept" to illustrate the utility of the Semantic Web in querying across databases which were originally difficult to implement. We were able to successfully retrieve information by linking UniCarbKB, GlycomeDB and JCGGDB in a single SPARQL query to obtain our target information. We also tested queries linking UniProt with GlycoEpitope as well as lectin data with GlycomeDB through PDB. As a result, we have been able to link proteomics data with glycomics data through the implementation of Semantic Web technologies, allowing for more flexible queries across these domains.

Modeling Views for Semantic Web Using eXtensible Semantic (XSemantic) Nets

NARCIS (Netherlands)

Rajugan, R.; Chang, E.; Feng, L.; Dillon, T.; meersman, R; Tari, Z; herrero, p; Méndez, G.; Cavedon, L.; Martin, D.; Hinze, A.; Buchanan, G.

2005-01-01

The emergence of Semantic Web (SW) and the related technologies promise to make the web a meaningful experience. Yet, high level modeling, design and querying techniques proves to be a challenging task for organizations that are hoping utilize the SW paradigm for their industrial applications, which

Query Language for Location-Based Services: A Model Checking Approach

Science.gov (United States)

Hoareau, Christian; Satoh, Ichiro

We present a model checking approach to the rationale, implementation, and applications of a query language for location-based services. Such query mechanisms are necessary so that users, objects, and/or services can effectively benefit from the location-awareness of their surrounding environment. The underlying data model is founded on a symbolic model of space organized in a tree structure. Once extended to a semantic model for modal logic, we regard location query processing as a model checking problem, and thus define location queries as hybrid logicbased formulas. Our approach is unique to existing research because it explores the connection between location models and query processing in ubiquitous computing systems, relies on a sound theoretical basis, and provides modal logic-based query mechanisms for expressive searches over a decentralized data structure. A prototype implementation is also presented and will be discussed.

Improving integrative searching of systems chemical biology data using semantic annotation.

Science.gov (United States)

Chen, Bin; Ding, Ying; Wild, David J

2012-03-08

Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i) simplifies the process of building SPARQL queries, (ii) enables useful new kinds of queries on the data and (iii) makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

Information management on the basis of semantic-web techniques, or a Google for developers; Informationsmanagement auf der Basis von Semantic-Web Techniken oder Ein Google fuer Entwickler

Energy Technology Data Exchange (ETDEWEB)

Thelen, B. [Schenck Pegasus GmbH, Darmstadt (Germany); Sevilmis, N.; Stork, A. [Fraunhofer Inst. fuer Graphische Datenverarbeitung, Darmstadt (Germany); Castro, R. [Centro de Computacao Grafica, Guimaraes (Portugal); Jimenez, I.; Marcos, G.; Posada, J.; Smithers, T. [VICOMTech, San Sebastian (Spain); Mauri, M.; Pianciamore, M.; Selvini, P. [CEFRIEL, Milano (Italy); Zecchino, V. [Italdesign - Giugiaro SpA, Moncalieri, Torino (Italy)

2005-07-01

Information retrieval often suffers from the lack of suitable search tools or the query complexity. The search of some concrete information on the base of file names or the coincidental occurrence of key words in files is little helpful because the obtainable matches are too much subject to chance. Therefore an effective search must be based on the semantic interpretation of the query and additionally casts of the query into the context of an application domain. Here the development of the search machine prototype WIDE is presented, which builds up the query interpretation on Semantic Web techniques. The search machine can be configured for application domains and is able to map a query to different data sources in parallel. The search machine processes the retrieved results graphically and associates the concepts used in the Query with thematically related concepts. The search machine can be used to retrieve text documents or test bed results of experiments archived in ASAM-ODS data sources. (orig.)

Counting, enumerating and sampling of execution plans in a cost-based query optimizer

NARCIS (Netherlands)

F. Waas; C.A. Galindo-Legaria

1999-01-01

textabstractTesting an SQL database system by running large sets of deterministic or stochastic SQL statements is common practice in commercial database development. However, code defects often remain undetected as the query optimizer's choice of an execution plan is not only depending on

Improving integrative searching of systems chemical biology data using semantic annotation

Directory of Open Access Journals (Sweden)

Chen Bin

2012-03-01

Full Text Available Abstract Background Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. Results We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i simplifies the process of building SPARQL queries, (ii enables useful new kinds of queries on the data and (iii makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Availability Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

Design and development of semantic web-based system for computer science domain-specific information retrieval

Directory of Open Access Journals (Sweden)

Ritika Bansal

2016-09-01

Full Text Available In semantic web-based system, the concept of ontology is used to search results by contextual meaning of input query instead of keyword matching. From the research literature, there seems to be a need for a tool which can provide an easy interface for complex queries in natural language that can retrieve the domain-specific information from the ontology. This research paper proposes an IRSCSD system (Information retrieval system for computer science domain as a solution. This system offers advanced querying and browsing of structured data with search results automatically aggregated and rendered directly in a consistent user-interface, thus reducing the manual effort of users. So, the main objective of this research is design and development of semantic web-based system for integrating ontology towards domain-specific retrieval support. Methodology followed is a piecemeal research which involves the following stages. First Stage involves the designing of framework for semantic web-based system. Second stage builds the prototype for the framework using Protégé tool. Third Stage deals with the natural language query conversion into SPARQL query language using Python-based QUEPY framework. Fourth Stage involves firing of converted SPARQL queries to the ontology through Apache's Jena API to fetch the results. Lastly, evaluation of the prototype has been done in order to ensure its efficiency and usability. Thus, this research paper throws light on framework development for semantic web-based system that assists in efficient retrieval of domain-specific information, natural language query interpretation into semantic web language, creation of domain-specific ontology and its mapping with related ontology. This research paper also provides approaches and metrics for ontology evaluation on prototype ontology developed to study the performance based on accessibility of required domain-related information.

The Role of Semantic Clustering in Optimal Memory Foraging

Science.gov (United States)

Montez, Priscilla; Thompson, Graham; Kello, Christopher T.

2015-01-01

Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in…

Semantic Web Without SPARQL.pdf

OpenAIRE

Szekely, Pedro

2016-01-01

Discuss the creation of large Semantic Web applications with billions of triples. Instead of using a traditional SPARQL endpoint, our toolchain is a pure JSON toolchain using JSON-LD and ElasticSearch to support queries. The toolchain is familiar to all developers, does not require knowledge of Semantic Web technologies, and performance is 10X better than using SPARQL endpoints. The presentation illustrates the approach in the context of an application to fight human trafficking, using data f...

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 ...

Query-Time Optimization Techniques for Structured Queries in Information Retrieval

Science.gov (United States)

Cartright, Marc-Allen

2013-01-01

The use of information retrieval (IR) systems is evolving towards larger, more complicated queries. Both the IR industrial and research communities have generated significant evidence indicating that in order to continue improving retrieval effectiveness, increases in retrieval model complexity may be unavoidable. From an operational perspective,…

Semantic Indexing and Retrieval based on Formal Concept Analysis

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

Semantic indexing and retrieval has become an important research area, as the available amount of information on the Web is growing more and more. In this paper, we introduce an original approach to semantic indexing and retrieval based on Formal Concept Analysis. The concept lattice is used as a semantic index and we propose an original algorithm for traversing the lattice and answering user queries. This framework has been used and evaluated on song datasets.

Non-Spatial and Geospatial Semantic Query of Health Information

DEFF Research Database (Denmark)

Gao, S.; Anton, François; Mioc, Darka

2012-01-01

With the growing amount of health information and frequent outbreaks of diseases, the retrieval of health information is given more concern. Machine understanding of spatial information can improve the interpretation of health data semantics. Most of the current research focused on the non-spatia...

Domainwise Web Page Optimization Based On Clustered Query Sessions Using Hybrid Of Trust And ACO For Effective Information Retrieval

Directory of Open Access Journals (Sweden)

Dr. Suruchi Chawla

2015-08-01

Full Text Available Abstract In this paper hybrid of Ant Colony OptimizationACO and trust has been used for domainwise web page optimization in clustered query sessions for effective Information retrieval. The trust of the web page identifies its degree of relevance in satisfying specific information need of the user. The trusted web pages when optimized using pheromone updates in ACO will identify the trusted colonies of web pages which will be relevant to users information need in a given domain. Hence in this paper the hybrid of Trust and ACO has been used on clustered query sessions for identifying more and more relevant number of documents in a given domain in order to better satisfy the information need of the user. Experiment was conducted on the data set of web query sessions to test the effectiveness of the proposed approach in selected three domains Academics Entertainment and Sports and the results confirm the improvement in the precision of search results.

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.

jQuery Mobile

CERN Document Server

Reid, Jon

2011-01-01

Native apps have distinct advantages, but the future belongs to mobile web apps that function on a broad range of smartphones and tablets. Get started with jQuery Mobile, the touch-optimized framework for creating apps that look and behave consistently across many devices. This concise book provides HTML5, CSS3, and JavaScript code examples, screen shots, and step-by-step guidance to help you build a complete working app with jQuery Mobile. If you're already familiar with the jQuery JavaScript library, you can use your existing skills to build cross-platform mobile web apps right now. This b

Analysis and visualization of disease courses in a semantically-enabled cancer registry.

Science.gov (United States)

Esteban-Gil, Angel; Fernández-Breis, Jesualdo Tomás; Boeker, Martin

2017-09-29

Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays. However, the lack of a well-defined common semantic model is a problem when user-defined analyses and data linking to external resources are required. The objectives of this study are: (1) design of a semantic model for local cancer registries; (2) development of a semantically-enabled cancer registry based on this model; and (3) semantic exploitation of the cancer registry for analysing and visualising disease courses. Our proposal is based on our previous results and experience working with semantic technologies. Data stored in a cancer registry database were transformed into RDF employing a process driven by OWL ontologies. The semantic representation of the data was then processed to extract semantic patient profiles, which were exploited by means of SPARQL queries to identify groups of similar patients and to analyse the disease timelines of patients. Based on the requirements analysis, we have produced a draft of an ontology that models the semantics of a local cancer registry in a pragmatic extensible way. We have implemented a Semantic Web platform that allows transforming and storing data from cancer registries in RDF. This platform also permits users to formulate incremental user-defined queries through a graphical user interface. The query results can be displayed in several customisable ways. The complex disease timelines of individual patients can be clearly represented. Different events, e.g. different therapies and disease courses, are presented according to their temporal and causal relations. The presented platform is an example of the parallel development of ontologies and applications that take advantage of semantic web technologies in the medical field. The semantic structure of the representation renders it easy to

Intelligent Agent Based Semantic Web in Cloud Computing Environment

OpenAIRE

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

2013-01-01

Considering today's web scenario, there is a need of effective and meaningful search over the web which is provided by Semantic Web. Existing search engines are keyword based. They are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. While semantic search engines provides efficient and relevant results as the semantic web is an extension of the current web in which information is given well defined meaning....

The role of economics in the QUERI program: QUERI Series.

Science.gov (United States)

Smith, Mark W; Barnett, Paul G

2008-04-22

The United States (U.S.) Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has implemented economic analyses in single-site and multi-site clinical trials. To date, no one has reviewed whether the QUERI Centers are taking an optimal approach to doing so. Consistent with the continuous learning culture of the QUERI Program, this paper provides such a reflection. We present a case study of QUERI as an example of how economic considerations can and should be integrated into implementation research within both single and multi-site studies. We review theoretical and applied cost research in implementation studies outside and within VA. We also present a critique of the use of economic research within the QUERI program. Economic evaluation is a key element of implementation research. QUERI has contributed many developments in the field of implementation but has only recently begun multi-site implementation trials across multiple regions within the national VA healthcare system. These trials are unusual in their emphasis on developing detailed costs of implementation, as well as in the use of business case analyses (budget impact analyses). Economics appears to play an important role in QUERI implementation studies, only after implementation has reached the stage of multi-site trials. Economic analysis could better inform the choice of which clinical best practices to implement and the choice of implementation interventions to employ. QUERI economics also would benefit from research on costing methods and development of widely accepted international standards for implementation economics.

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

Science.gov (United States)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Genre-Specific Semantic Video Indexing

NARCIS (Netherlands)

Wu, J.; Worring, M.

2010-01-01

In many applications, we find large video collections from different genres where the user is often only interested in one or two specific video genres. So, when users are querying the system with a specific semantic concept, they are likely aiming a genre specific instantiation of this concept.

Multi-weighted tree based query optimization method for parallel relational database systems%基于多重加权树的并行关系数据库系统的查询优化方法

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

The author investigates the query optimization problem for parallel relational databases. A multi-weighted tree based query optimization method is proposed. The method consists of a multi-weighted tree based parallel query plan model, a cost model for parallel qury plans and a query optimizer. The parallel query plan model is the first one to model all basic relational operations, all three types of parallelism of query execution, processor and memory allocation to operations, memory allocation to the buffers between operations in pipelines and data redistribution among processors.The cost model takes the waiting time of the operations in pipelining execution into consideration and is computable in a bottom-up fashion. The query optimizer addresses the query optimization problem in the context of Select-Project-Join queries that are widely used in commercial DBMSs. Several heuristics determining the processor allocation to operations are derived and used in the query optimizer. The query optimizer is aware of memory resources in order to generate good-quality plans. It includes the heuristics for determining the memory allocation to operations and buffers between operations in pipelines so that the memory resourse is fully exploit. In addition, multiple algorithms for implementing join operations are consided in the query optimizer. The query optimizer can make an optimal choice of join algorithm for each join operation in a query. The proposed query optimization method has been used in a prototype parallel database management system designed and implemented by the author.

Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores

OpenAIRE

Konstantopoulos, Stasinos; Charalambidis, Angelos; Mouchakis, Giannis; Troumpoukis, Antonis; Jakobitsch, Jürgen; Karkaletsis, Vangelis

2016-01-01

The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges invo...

AMATCHMETHOD BASED ON LATENT SEMANTIC ANALYSIS FOR EARTHQUAKEHAZARD EMERGENCY PLAN

Directory of Open Access Journals (Sweden)

D. Sun

2017-09-01

Full Text Available The structure of the emergency plan on earthquake is complex, and it’s difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA. After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.

Amatchmethod Based on Latent Semantic Analysis for Earthquakehazard Emergency Plan

Science.gov (United States)

Sun, D.; Zhao, S.; Zhang, Z.; Shi, X.

2017-09-01

The structure of the emergency plan on earthquake is complex, and it's difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA). After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.

DBPQL: A view-oriented query language for the Intel Data Base Processor

Science.gov (United States)

Fishwick, P. A.

1983-01-01

An interactive query language (BDPQL) for the Intel Data Base Processor (DBP) is defined. DBPQL includes a parser generator package which permits the analyst to easily create and manipulate the query statement syntax and semantics. The prototype language, DBPQL, includes trace and performance commands to aid the analyst when implementing new commands and analyzing the execution characteristics of the DBP. The DBPQL grammar file and associated key procedures are included as an appendix to this report.

The role of economics in the QUERI program: QUERI Series

Directory of Open Access Journals (Sweden)

Smith Mark W

2008-04-01

Full Text Available Abstract Background The United States (U.S. Department of Veterans Affairs (VA Quality Enhancement Research Initiative (QUERI has implemented economic analyses in single-site and multi-site clinical trials. To date, no one has reviewed whether the QUERI Centers are taking an optimal approach to doing so. Consistent with the continuous learning culture of the QUERI Program, this paper provides such a reflection. Methods We present a case study of QUERI as an example of how economic considerations can and should be integrated into implementation research within both single and multi-site studies. We review theoretical and applied cost research in implementation studies outside and within VA. We also present a critique of the use of economic research within the QUERI program. Results Economic evaluation is a key element of implementation research. QUERI has contributed many developments in the field of implementation but has only recently begun multi-site implementation trials across multiple regions within the national VA healthcare system. These trials are unusual in their emphasis on developing detailed costs of implementation, as well as in the use of business case analyses (budget impact analyses. Conclusion Economics appears to play an important role in QUERI implementation studies, only after implementation has reached the stage of multi-site trials. Economic analysis could better inform the choice of which clinical best practices to implement and the choice of implementation interventions to employ. QUERI economics also would benefit from research on costing methods and development of widely accepted international standards for implementation economics.

Querying clinical data in HL7 RIM based relational model with morph-RDB.

Science.gov (United States)

Priyatna, Freddy; Alonso-Calvo, Raul; Paraiso-Medina, Sergio; Corcho, Oscar

2017-10-05

Semantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshness. In this paper we present a solution that uses an ontology based on the HL7 v3 Reference Information Model and a set of R2RML mappings that relate this ontology to an underlying relational database implementation, and where morph-RDB is used to expose a virtual, non-materialized SPARQL endpoint over the data. By applying a set of optimization techniques on the SPARQL-to-SQL query translation algorithm, we can now issue SPARQL queries to the underlying relational data with generally acceptable performance.

Combining semantic technologies with a content-based image retrieval system - Preliminary considerations

Science.gov (United States)

Chmiel, P.; Ganzha, M.; Jaworska, T.; Paprzycki, M.

2017-10-01

Nowadays, as a part of systematic growth of volume, and variety, of information that can be found on the Internet, we observe also dramatic increase in sizes of available image collections. There are many ways to help users browsing / selecting images of interest. One of popular approaches are Content-Based Image Retrieval (CBIR) systems, which allow users to search for images that match their interests, expressed in the form of images (query by example). However, we believe that image search and retrieval could take advantage of semantic technologies. We have decided to test this hypothesis. Specifically, on the basis of knowledge captured in the CBIR, we have developed a domain ontology of residential real estate (detached houses, in particular). This allows us to semantically represent each image (and its constitutive architectural elements) represented within the CBIR. The proposed ontology was extended to capture not only the elements resulting from image segmentation, but also "spatial relations" between them. As a result, a new approach to querying the image database (semantic querying) has materialized, thus extending capabilities of the developed system.

How semantics can inform the geological mapping process and support intelligent queries

Science.gov (United States)

Lombardo, Vincenzo; Piana, Fabrizio; Mimmo, Dario

2017-04-01

The geologic mapping process requires the organization of data according to the general knowledge about the objects, namely the geologic units, and to the objectives of a graphic representation of such objects in a map, following an established model of geotectonic evolution. Semantics can greatly help such a process in two concerns: the provision of a terminological base to name and classify the objects of the map; on the other, the implementation of a machine-readable encoding of the geologic knowledge base supports the application of reasoning mechanisms and the derivation of novel properties and relations about the objects of the map. The OntoGeonous initiative has built a terminological base of geological knowledge in a machine-readable format, following the Semantic Web tenets and the Linked Data paradigm. The major knowledge sources of the OntoGeonous initiative are GeoScience Markup Language schemata and vocabularies (through its last version, GeoSciML 4, 2015, published by the IUGS CGI Commission) and the INSPIRE "Data Specification on Geology" directives (an operative simplification of GeoSciML, published by INSPIRE Thematic Working Group Geology of the European Commission). The Linked Data paradigm has been exploited by linking (without replicating, to avoid inconsistencies) the already existing machine-readable encoding for some specific domains, such as the lithology domain (vocabulary Simple Lithology) and the geochronologic time scale (ontology "gts"). Finally, for the upper level knowledge, shared across several geologic domains, we have resorted to NASA SWEET ontology. The OntoGeonous initiative has also produced a wiki that explains how the geologic knowledge has been encoded from shared geoscience vocabularies (https://www.di.unito.it/wikigeo/). In particular, the sections dedicated to axiomatization will support the construction of an appropriate data base schema that can be then filled with the objects of the map. This contribution will discuss

Structuring Legacy Pathology Reports by openEHR Archetypes to Enable Semantic Querying.

Science.gov (United States)

Kropf, Stefan; Krücken, Peter; Mueller, Wolf; Denecke, Kerstin

2017-05-18

Clinical information is often stored as free text, e.g. in discharge summaries or pathology reports. These documents are semi-structured using section headers, numbered lists, items and classification strings. However, it is still challenging to retrieve relevant documents since keyword searches applied on complete unstructured documents result in many false positive retrieval results. We are concentrating on the processing of pathology reports as an example for unstructured clinical documents. The objective is to transform reports semi-automatically into an information structure that enables an improved access and retrieval of relevant data. The data is expected to be stored in a standardized, structured way to make it accessible for queries that are applied to specific sections of a document (section-sensitive queries) and for information reuse. Our processing pipeline comprises information modelling, section boundary detection and section-sensitive queries. For enabling a focused search in unstructured data, documents are automatically structured and transformed into a patient information model specified through openEHR archetypes. The resulting XML-based pathology electronic health records (PEHRs) are queried by XQuery and visualized by XSLT in HTML. Pathology reports (PRs) can be reliably structured into sections by a keyword-based approach. The information modelling using openEHR allows saving time in the modelling process since many archetypes can be reused. The resulting standardized, structured PEHRs allow accessing relevant data by retrieving data matching user queries. Mapping unstructured reports into a standardized information model is a practical solution for a better access to data. Archetype-based XML enables section-sensitive retrieval and visualisation by well-established XML techniques. Focussing the retrieval to particular sections has the potential of saving retrieval time and improving the accuracy of the retrieval.

The Data Cyclotron query processing scheme

NARCIS (Netherlands)

Goncalves, R.; Kersten, M.

2011-01-01

A grand challenge of distributed query processing is to devise a self-organizing architecture which exploits all hardware resources optimally to manage the database hot set, minimize query response time, and maximize throughput without single point global coordination. The Data Cyclotron

A Framework for WWW Query Processing

Science.gov (United States)

Wu, Binghui Helen; Wharton, Stephen (Technical Monitor)

2000-01-01

Query processing is the most common operation in a DBMS. Sophisticated query processing has been mainly targeted at a single enterprise environment providing centralized control over data and metadata. Submitting queries by anonymous users on the web is different in such a way that load balancing or DBMS' accessing control becomes the key issue. This paper provides a solution by introducing a framework for WWW query processing. The success of this framework lies in the utilization of query optimization techniques and the ontological approach. This methodology has proved to be cost effective at the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC).

The Data Cyclotron query processing scheme.

NARCIS (Netherlands)

R.A. Goncalves (Romulo); M.L. Kersten (Martin)

2011-01-01

htmlabstractA grand challenge of distributed query processing is to devise a self-organizing architecture which exploits all hardware resources optimally to manage the database hot set, minimize query response time, and maximize throughput without single point global coordination. The Data Cyclotron

Generating and Executing Complex Natural Language Queries across Linked Data.

Science.gov (United States)

Hamon, Thierry; Mougin, Fleur; Grabar, Natalia

2015-01-01

With the recent and intensive research in the biomedical area, the knowledge accumulated is disseminated through various knowledge bases. Links between these knowledge bases are needed in order to use them jointly. Linked Data, SPARQL language, and interfaces in Natural Language question-answering provide interesting solutions for querying such knowledge bases. We propose a method for translating natural language questions in SPARQL queries. We use Natural Language Processing tools, semantic resources, and the RDF triples description. The method is designed on 50 questions over 3 biomedical knowledge bases, and evaluated on 27 questions. It achieves 0.78 F-measure on the test set. The method for translating natural language questions into SPARQL queries is implemented as Perl module available at http://search.cpan.org/ thhamon/RDF-NLP-SPARQLQuery.

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.

Geo-Enrichment and Semantic Enhancement of Metadata Sets to Augment Discovery in Geoportals

Directory of Open Access Journals (Sweden)

Bernhard Vockner

2014-03-01

Full Text Available Geoportals are established to function as main gateways to find, evaluate, and start “using” geographic information. Still, current geoportal implementations face problems in optimizing the discovery process due to semantic heterogeneity issues, which leads to low recall and low precision in performing text-based searches. Therefore, we propose an enhanced semantic discovery approach that supports multilingualism and information domain context. Thus, we present workflow that enriches existing structured metadata with synonyms, toponyms, and translated terms derived from user-defined keywords based on multilingual thesauri and ontologies. To make the results easier and understandable, we also provide automated translation capabilities for the resource metadata to support the user in conceiving the thematic content of the descriptive metadata, even if it has been documented using a language the user is not familiar with. In addition, to text-enable spatial filtering capabilities, we add additional location name keywords to metadata sets. These are based on the existing bounding box and shall tweak discovery scores when performing single text line queries. In order to improve the user’s search experience, we tailor faceted search strategies presenting an enhanced query interface for geo-metadata discovery that are transparently leveraging the underlying thesauri and ontologies.

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.

Graph-Based Semantic Web Service Composition for Healthcare Data Integration.

Science.gov (United States)

Arch-Int, Ngamnij; Arch-Int, Somjit; Sonsilphong, Suphachoke; Wanchai, Paweena

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement.

Evolutionary Algorithms for Boolean Queries Optimization

Czech Academy of Sciences Publication Activity Database

Húsek, Dušan; Snášel, Václav; Neruda, Roman; Owais, S.S.J.; Krömer, P.

2006-01-01

Roč. 3, č. 1 (2006), s. 15-20 ISSN 1790-0832 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * information retrieval * Boolean query Subject RIV: BA - General Mathematics

QueryArch3D: Querying and Visualising 3D Models of a Maya Archaeological Site in a Web-Based Interface

Directory of Open Access Journals (Sweden)

Giorgio Agugiaro

2011-12-01

Full Text Available Constant improvements in the field of surveying, computing and distribution of digital-content are reshaping the way Cultural Heritage can be digitised and virtually accessed, even remotely via web. A traditional 2D approach for data access, exploration, retrieval and exploration may generally suffice, however more complex analyses concerning spatial and temporal features require 3D tools, which, in some cases, have not yet been implemented or are not yet generally commercially available. Efficient organisation and integration strategies applicable to the wide array of heterogeneous data in the field of Cultural Heritage represent a hot research topic nowadays. This article presents a visualisation and query tool (QueryArch3D conceived to deal with multi-resolution 3D models. Geometric data are organised in successive levels of detail (LoD, provided with geometric and semantic hierarchies and enriched with attributes coming from external data sources. The visualisation and query front-end enables the 3D navigation of the models in a virtual environment, as well as the interaction with the objects by means of queries based on attributes or on geometries. The tool can be used as a standalone application, or served through the web. The characteristics of the research work, along with some implementation issues and the developed QueryArch3D tool will be discussed and presented.

Boolean Queries Optimization by Genetic Algorithms

Czech Academy of Sciences Publication Activity Database

Húsek, Dušan; Owais, S.S.J.; Krömer, P.; Snášel, Václav

2005-01-01

Roč. 15, - (2005), s. 395-409 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * genetic programming * information retrieval * Boolean query Subject RIV: BB - Applied Statistics, Operational Research

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.

Science.gov (United States)

Sernadela, Pedro; González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Posada, Manuel; Taruscio, Domenica; Lochmüller, Hanns; Robinson, Peter; Roos, Marco; Oliveira, José Luís

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.

Efficient genre-specific semantic video indexing

NARCIS (Netherlands)

Wu, J.; Worring, M.

2012-01-01

Large video collections such as YouTube contain many different video genres, while in many applications the user might be interested in one or two specific video genres only. Thus, when users are querying the system with a specific semantic concept like AnchorPerson, and MovieStars, they are likely

Semantic knowledge representation for information retrieval

CERN Document Server

Gödert, Winfried; Nagelschmidt, Matthias

2014-01-01

This book covers the basics of semantic web technologies and indexing languages, and describes their contribution to improve languages as a tool for subject queries and knowledge exploration. The book is relevant to information scientists, knowledge workers and indexers. It provides a suitable combination of theoretical foundations and practical applications.

XSemantic: An Extension of LCA Based XML Semantic Search

Science.gov (United States)

Supasitthimethee, Umaporn; Shimizu, Toshiyuki; Yoshikawa, Masatoshi; Porkaew, Kriengkrai

One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge of XML structure or learning a new user interface. However, the keyword search is ambiguous. The users may use different terms to search for the same information. Furthermore, it is difficult for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address these challenges, we propose an XML semantic search based on keywords called XSemantic. On the one hand, we give three definitions to complete in terms of semantics. Firstly, the semantic term expansion, our system is robust from the ambiguous keywords by using the domain ontology. Secondly, to return semantic meaningful answers, we automatically infer the return information from the user queries and take advantage of the shortest path to return meaningful connections between keywords. Thirdly, we present the semantic ranking that reflects the degree of similarity as well as the semantic relationship so that the search results with the higher relevance are presented to the users first. On the other hand, in the LCA and the proximity search approaches, we investigated the problem of information included in the search results. Therefore, we introduce the notion of the Lowest Common Element Ancestor (LCEA) and define our simple rule without any requirement on the schema information such as the DTD or XML Schema. The first experiment indicated that XSemantic not only properly infers the return information but also generates compact meaningful results. Additionally, the benefits of our proposed semantics are demonstrated by the second experiment.

Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories

Science.gov (United States)

Tao, Shiqiang; Cui, Licong; Wu, Xi; Zhang, Guo-Qiang

2017-01-01

To help researchers better access clinical data, we developed a prototype query engine called DataSphere for exploring large-scale integrated clinical data repositories. DataSphere expedites data importing using a NoSQL data management system and dynamically renders its user interface for concept-based querying tasks. DataSphere provides an interactive query-building interface together with query translation and optimization strategies, which enable users to build and execute queries effectively and efficiently. We successfully loaded a dataset of one million patients for University of Kentucky (UK) Healthcare into DataSphere with more than 300 million clinical data records. We evaluated DataSphere by comparing it with an instance of i2b2 deployed at UK Healthcare, demonstrating that DataSphere provides enhanced user experience for both query building and execution. PMID:29854239

Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories.

Science.gov (United States)

Tao, Shiqiang; Cui, Licong; Wu, Xi; Zhang, Guo-Qiang

2017-01-01

To help researchers better access clinical data, we developed a prototype query engine called DataSphere for exploring large-scale integrated clinical data repositories. DataSphere expedites data importing using a NoSQL data management system and dynamically renders its user interface for concept-based querying tasks. DataSphere provides an interactive query-building interface together with query translation and optimization strategies, which enable users to build and execute queries effectively and efficiently. We successfully loaded a dataset of one million patients for University of Kentucky (UK) Healthcare into DataSphere with more than 300 million clinical data records. We evaluated DataSphere by comparing it with an instance of i2b2 deployed at UK Healthcare, demonstrating that DataSphere provides enhanced user experience for both query building and execution.

Gazetteer Brokering through Semantic Mediation

Science.gov (United States)

Hobona, G.; Bermudez, L. E.; Brackin, R.

2013-12-01

A gazetteer is a geographical directory containing some information regarding places. It provides names, location and other attributes for places which may include points of interest (e.g. buildings, oilfields and boreholes), and other features. These features can be published via web services conforming to the Gazetteer Application Profile of the Web Feature Service (WFS) standard of the Open Geospatial Consortium (OGC). Against the backdrop of advances in geophysical surveys, there has been a significant increase in the amount of data referenced to locations. Gazetteers services have played a significant role in facilitating access to such data, including through provision of specialized queries such as text, spatial and fuzzy search. Recent developments in the OGC have led to advances in gazetteers such as support for multilingualism, diacritics, and querying via advanced spatial constraints (e.g. search by radial search and nearest neighbor). A challenge remaining however, is that gazetteers produced by different organizations have typically been modeled differently. Inconsistencies from gazetteers produced by different organizations may include naming the same feature in a different way, naming the attributes differently, locating the feature in a different location, and providing fewer or more attributes than the other services. The Gazetteer application profile of the WFS is a starting point to address such inconsistencies by providing a standardized interface based on rules specified in ISO 19112, the international standard for spatial referencing by geographic identifiers. The profile, however, does not provide rules to deal with semantic inconsistencies. The USGS and NGA commissioned research into the potential for a Single Point of Entry Global Gazetteer (SPEGG). The research was conducted by the Cross Community Interoperability thread of the OGC testbed, referenced OWS-9. The testbed prototyped approaches for brokering gazetteers through use of semantic

Query construction, entropy, and generalization in neural-network models

Science.gov (United States)

Sollich, Peter

1994-05-01

We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

Science.gov (United States)

Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

Sharing-Aware Horizontal Partitioning for Exploiting Correlations during Query Processing

DEFF Research Database (Denmark)

Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian Søndergaard

2010-01-01

Optimization of join queries based on average selectivities is suboptimal in highly correlated databases. In such databases, relations are naturally divided into partitions, each partition having substantially different statistical characteristics. It is very compelling to discover such data...... partitions during query optimization and create multiple plans for a given query, one plan being optimal for a particular combination of data partitions. This scenario calls for the sharing of state among plans, so that common intermediate results are not recomputed. We study this problem in a setting...

HyQue: evaluating hypotheses using Semantic Web technologies

Directory of Open Access Journals (Sweden)

Callahan Alison

2011-05-01

Full Text Available Abstract Background Key to the success of e-Science is the ability to computationally evaluate expert-composed hypotheses for validity against experimental data. Researchers face the challenge of collecting, evaluating and integrating large amounts of diverse information to compose and evaluate a hypothesis. Confronted with rapidly accumulating data, researchers currently do not have the software tools to undertake the required information integration tasks. Results We present HyQue, a Semantic Web tool for querying scientific knowledge bases with the purpose of evaluating user submitted hypotheses. HyQue features a knowledge model to accommodate diverse hypotheses structured as events and represented using Semantic Web languages (RDF/OWL. Hypothesis validity is evaluated against experimental and literature-sourced evidence through a combination of SPARQL queries and evaluation rules. Inference over OWL ontologies (for type specifications, subclass assertions and parthood relations and retrieval of facts stored as Bio2RDF linked data provide support for a given hypothesis. We evaluate hypotheses of varying levels of detail about the genetic network controlling galactose metabolism in Saccharomyces cerevisiae to demonstrate the feasibility of deploying such semantic computing tools over a growing body of structured knowledge in Bio2RDF. Conclusions HyQue is a query-based hypothesis evaluation system that can currently evaluate hypotheses about the galactose metabolism in S. cerevisiae. Hypotheses as well as the supporting or refuting data are represented in RDF and directly linked to one another allowing scientists to browse from data to hypothesis and vice versa. HyQue hypotheses and data are available at http://semanticscience.org/projects/hyque.

HyQue: evaluating hypotheses using Semantic Web technologies

Science.gov (United States)

2011-01-01

Background Key to the success of e-Science is the ability to computationally evaluate expert-composed hypotheses for validity against experimental data. Researchers face the challenge of collecting, evaluating and integrating large amounts of diverse information to compose and evaluate a hypothesis. Confronted with rapidly accumulating data, researchers currently do not have the software tools to undertake the required information integration tasks. Results We present HyQue, a Semantic Web tool for querying scientific knowledge bases with the purpose of evaluating user submitted hypotheses. HyQue features a knowledge model to accommodate diverse hypotheses structured as events and represented using Semantic Web languages (RDF/OWL). Hypothesis validity is evaluated against experimental and literature-sourced evidence through a combination of SPARQL queries and evaluation rules. Inference over OWL ontologies (for type specifications, subclass assertions and parthood relations) and retrieval of facts stored as Bio2RDF linked data provide support for a given hypothesis. We evaluate hypotheses of varying levels of detail about the genetic network controlling galactose metabolism in Saccharomyces cerevisiae to demonstrate the feasibility of deploying such semantic computing tools over a growing body of structured knowledge in Bio2RDF. Conclusions HyQue is a query-based hypothesis evaluation system that can currently evaluate hypotheses about the galactose metabolism in S. cerevisiae. Hypotheses as well as the supporting or refuting data are represented in RDF and directly linked to one another allowing scientists to browse from data to hypothesis and vice versa. HyQue hypotheses and data are available at http://semanticscience.org/projects/hyque. PMID:21624158

HyQue: evaluating hypotheses using Semantic Web technologies.

Science.gov (United States)

Callahan, Alison; Dumontier, Michel; Shah, Nigam H

2011-05-17

Key to the success of e-Science is the ability to computationally evaluate expert-composed hypotheses for validity against experimental data. Researchers face the challenge of collecting, evaluating and integrating large amounts of diverse information to compose and evaluate a hypothesis. Confronted with rapidly accumulating data, researchers currently do not have the software tools to undertake the required information integration tasks. We present HyQue, a Semantic Web tool for querying scientific knowledge bases with the purpose of evaluating user submitted hypotheses. HyQue features a knowledge model to accommodate diverse hypotheses structured as events and represented using Semantic Web languages (RDF/OWL). Hypothesis validity is evaluated against experimental and literature-sourced evidence through a combination of SPARQL queries and evaluation rules. Inference over OWL ontologies (for type specifications, subclass assertions and parthood relations) and retrieval of facts stored as Bio2RDF linked data provide support for a given hypothesis. We evaluate hypotheses of varying levels of detail about the genetic network controlling galactose metabolism in Saccharomyces cerevisiae to demonstrate the feasibility of deploying such semantic computing tools over a growing body of structured knowledge in Bio2RDF. HyQue is a query-based hypothesis evaluation system that can currently evaluate hypotheses about the galactose metabolism in S. cerevisiae. Hypotheses as well as the supporting or refuting data are represented in RDF and directly linked to one another allowing scientists to browse from data to hypothesis and vice versa. HyQue hypotheses and data are available at http://semanticscience.org/projects/hyque.

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

Presenting results as dynamically generated co-authorship subgraphs in semantic digital library collections

Directory of Open Access Journals (Sweden)

James Powell

2012-02-01

Full Text Available Semantic web representations of data are by definition graphs, and these graphs can be explored using concepts from graph theory. This paper demonstrates how semantically mapped bibliographic metadata, combined with a lightweight software architecture and Web-based graph visualization tools, can be used to generate dynamic authorship graphs in response to typical user queries, as an alternative to more common text-based results presentations. It also shows how centrality measures and path analysis techniques from social network analysis can be used to enhance the visualization of query results. The resulting graphs require modestly more cognitive engagement from the user but offer insights not available from text.

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.

Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

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Mauro Castelli

2015-01-01

Full Text Available Energy consumption forecasting (ECF is an important policy issue in today’s economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

Robust Query Processing for Personalized Information Access on the Semantic Web

DEFF Research Database (Denmark)

Dolog, Peter; Stuckenschmidt, Heiner; Wache, Holger

and user preferences. We describe a framework for information access that combines query refinement and relaxation in order to provide robust, personalized access to heterogeneous RDF data as well as an implementation in terms of rewriting rules and explain its application in the context of e-learning...

Optimizing Vector-Quantization Processor Architecture for Intelligent Query-Search Applications

Science.gov (United States)

Xu, Huaiyu; Mita, Yoshio; Shibata, Tadashi

2002-04-01

The architecture of a very large scale integration (VLSI) vector-quantization processor (VQP) has been optimized to develop a general-purpose intelligent query-search agent. The agent performs a similarity-based search in a large-volume database. Although similarity-based search processing is computationally very expensive, latency-free searches have become possible due to the highly parallel maximum-likelihood search architecture of the VQP chip. Three architectures of the VQP chip have been studied and their performances are compared. In order to give reasonable searching results according to the different policies, the concept of penalty function has been introduced into the VQP. An E-commerce real-estate agency system has been developed using the VQP chip implemented in a field-programmable gate array (FPGA) and the effectiveness of such an agency system has been demonstrated.

PERANGKAT BANTU UNTUK OPTIMASI QUERY PADA ORACLE DENGAN RESTRUKTURISASI SQL

Directory of Open Access Journals (Sweden)

Darlis Heru Murti

2006-07-01

Full Text Available Query merupakan bagian dari bahasa pemrograman SQL (Structured Query Language yang berfungsi untuk mengambil data (read dalam DBMS (Database Management System, termasuk Oracle [3]. Pada Oracle, ada tiga tahap proses yang dilakukan dalam pengeksekusian query, yaitu Parsing, Execute dan Fetch. Sebelum proses execute dijalankan, Oracle terlebih dahulu membuat execution plan yang akan menjadi skenario dalam proses excute.Dalam proses pengeksekusian query, terdapat faktor-faktor yang mempengaruhi kinerja query, di antaranya access path (cara pengambilan data dari sebuah tabel dan operasi join (cara menggabungkan data dari dua tabel. Untuk mendapatkan query dengan kinerja optimal, maka diperlukan pertimbangan-pertimbangan dalam menyikapi faktor-faktor tersebut.  Optimasi query merupakan suatu cara untuk mendapatkan query dengan kinerja seoptimal mungkin, terutama dilihat dari sudut pandang waktu. Ada banyak metode untuk mengoptimasi query, tapi pada Penelitian ini, penulis membuat sebuah aplikasi untuk mengoptimasi query dengan metode restrukturisasi SQL statement. Pada metode ini, objek yang dianalisa adalah struktur klausa yang membangun sebuah query. Aplikasi ini memiliki satu input dan lima jenis output. Input dari aplikasi ini adalah sebuah query sedangkan kelima jenis output aplikasi ini adalah berupa query hasil optimasi, saran perbaikan, saran pembuatan indeks baru, execution plan dan data statistik. Cara kerja aplikasi ini dibagi menjadi empat tahap yaitu mengurai query menjadi sub query, mengurai query per-klausa, menentukan access path dan operasi join dan restrukturisasi query.Dari serangkaian ujicoba yang dilakukan penulis, aplikasi telah dapat berjalan sesuai dengan tujuan pembuatan Penelitian ini, yaitu mendapatkan query dengan kinerja optimal.Kata Kunci : Query, SQL, DBMS, Oracle, Parsing, Execute, Fetch, Execution Plan, Access Path, Operasi Join, Restrukturisasi SQL statement.

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.

Memory aware query scheduling in a database cluster

NARCIS (Netherlands)

F. Waas; M.L. Kersten (Martin)

2000-01-01

textabstractQuery throughput is one of the primary optimization goals in interactive web-based information systems in order to achieve the performance necessary to serve large user communities. Queries in this application domain differ significantly from those in traditional database applications:

Semantic web data warehousing for caGrid.

Science.gov (United States)

McCusker, James P; Phillips, Joshua A; González Beltrán, Alejandra; Finkelstein, Anthony; Krauthammer, Michael

2009-10-01

The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.

Spatial Relation Predicates in Topographic Feature Semantics

Science.gov (United States)

Varanka, Dalia E.; Caro, Holly K.

2013-01-01

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Automatically exposing OpenLifeData via SADI semantic Web Services.

Science.gov (United States)

González, Alejandro Rodríguez; Callahan, Alison; Cruz-Toledo, José; Garcia, Adrian; Egaña Aranguren, Mikel; Dumontier, Michel; Wilkinson, Mark D

2014-01-01

Two distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location. We use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries. We show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.

Semantic integration of information about orthologs and diseases: the OGO system.

Science.gov (United States)

Miñarro-Gimenez, Jose Antonio; Egaña Aranguren, Mikel; Martínez Béjar, Rodrigo; Fernández-Breis, Jesualdo Tomás; Madrid, Marisa

2011-12-01

Semantic Web technologies like RDF and OWL are currently applied in life sciences to improve knowledge management by integrating disparate information. Many of the systems that perform such task, however, only offer a SPARQL query interface, which is difficult to use for life scientists. We present the OGO system, which consists of a knowledge base that integrates information of orthologous sequences and genetic diseases, providing an easy to use ontology-constrain driven query interface. Such interface allows the users to define SPARQL queries through a graphical process, therefore not requiring SPARQL expertise. Copyright © 2011 Elsevier Inc. All rights reserved.

Review: Implementasi Holap Untuk Optimasi Query Sistem Basis Data Terdistribusi Dengan Pendekatan Algoritma Genetik

Directory of Open Access Journals (Sweden)

Rahmad Syaifudin

2016-01-01

Full Text Available Distributed Database is one of database that is under control of the Database Management System (DBMS was focused on storage devices are separated from one and another. Optimization data query on distributed database system not be separated from data processing methods that used. Then for fast query optimization this database need some required methods that can optimize it. Hybrid online analytical processing (HOLAP or often to call Hybrid-OLAP is one of technology for optimization query on distributed database. Genetic Algorithm is one of algorithm for heuristic searching was based on the mechanisms of biological evolution. Process of genetic algorithm is combining a selection process, using a crossover operator and mutation to get the best solution. From the reviews about implementation HOLAP with Genetic Algorithm approach was expected being used as a basis research on HOLAP implementation for query optimization on distributed database with genetic algorithm approach. Keywords : Query Optimization; Distributed database; HOLAP; OLAP; Genetetic algorithm.

Constraint-based query distribution framework for an integrated global schema

DEFF Research Database (Denmark)

Malik, Ahmad Kamran; Qadir, Muhammad Abdul; Iftikhar, Nadeem

2009-01-01

and replicated data sources. The provided system is all XML-based which poses query in XML form, transforms, and integrates local results in an XML document. Contributions include the use of constraints in our existing global schema which help in source selection and query optimization, and a global query...

Location-Dependent Query Processing Under Soft Real-Time Constraints

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Zoubir Mammeri

2009-01-01

Full Text Available In recent years, mobile devices and applications achieved an increasing development. In database field, this development required methods to consider new query types like location-dependent queries (i.e. the query results depend on the query issuer location. Although several researches addressed problems related to location-dependent query processing, a few works considered timing requirements that may be associated with queries (i.e., the query results must be delivered to mobile clients on time. The main objective of this paper is to propose a solution for location-dependent query processing under soft real-time constraints. Hence, we propose methods to take into account client location-dependency and to maximize the percentage of queries respecting their deadlines. We validate our proposal by implementing a prototype based on Oracle DBMS. Performance evaluation results show that the proposed solution optimizes the percentage of queries meeting their deadlines and the communication cost.

Path Minima Queries in Dynamic Weighted Trees

DEFF Research Database (Denmark)

Davoodi, Pooya; Brodal, Gerth Stølting; Satti, Srinivasa Rao

2011-01-01

In the path minima problem on a tree, each edge is assigned a weight and a query asks for the edge with minimum weight on a path between two nodes. For the dynamic version of the problem, where the edge weights can be updated, we give data structures that achieve optimal query time\\todo{what about...

Semantic Web Approach to Ease Regulation Compliance Checking in Construction Industry

Directory of Open Access Journals (Sweden)

Bruno Fies

2012-09-01

Full Text Available Regulations in the Building Industry are becoming increasingly complex and involve more than one technical area, covering products, components and project implementations. They also play an important role in ensuring the quality of a building, and to minimize its environmental impact. Control or conformance checking are becoming more complex every day, not only for industrials, but also for organizations charged with assessing the conformity of new products or processes. This paper will detail the approach taken by the CSTB (Centre Scientifique et Technique du Bâtiment in order to simplify this conformance control task. The approach and the proposed solutions are based on semantic web technologies. For this purpose, we first establish a domain-ontology, which defines the main concepts involved and the relationships, including one based on OWL (Web Ontology Language [1]. We rely on SBVR (Semantics of Business Vocabulary and Business Rules [2] and SPARQL (SPARQL Protocol and RDF Query Language [3] to reformulate the regulatory requirements written in natural language, respectively, in a controlled and formal language. We then structure our control process based on expert practices. Each elementary control step is defined as a SPARQL query and assembled into complex control processes “on demand”, according to the component tested and its semantic definition. Finally, we represent in RDF (Resource Description Framework [4] the association between the SBVR rules and SPARQL queries representing the same regulatory constraints.

Semantic similarity measure in biomedical domain leverage web search engine.

Science.gov (United States)

Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

Semantic Models for Scalable Search in the Internet of Things

Directory of Open Access Journals (Sweden)

Dennis Pfisterer

2013-03-01

Full Text Available The Internet of Things is anticipated to connect billions of embedded devices equipped with sensors to perceive their surroundings. Thereby, the state of the real world will be available online and in real-time and can be combined with other data and services in the Internet to realize novel applications such as Smart Cities, Smart Grids, or Smart Healthcare. This requires an open representation of sensor data and scalable search over data from diverse sources including sensors. In this paper we show how the Semantic Web technologies RDF (an open semantic data format and SPARQL (a query language for RDF-encoded data can be used to address those challenges. In particular, we describe how prediction models can be employed for scalable sensor search, how these prediction models can be encoded as RDF, and how the models can be queried by means of SPARQL.

Matching health information seekers' queries to medical terms.

Science.gov (United States)

Soualmia, Lina F; Prieur-Gaston, Elise; Moalla, Zied; Lecroq, Thierry; Darmoni, Stéfan J

2012-01-01

The Internet is a major source of health information but most seekers are not familiar with medical vocabularies. Hence, their searches fail due to bad query formulation. Several methods have been proposed to improve information retrieval: query expansion, syntactic and semantic techniques or knowledge-based methods. However, it would be useful to clean those queries which are misspelled. In this paper, we propose a simple yet efficient method in order to correct misspellings of queries submitted by health information seekers to a medical online search tool. In addition to query normalizations and exact phonetic term matching, we tested two approximate string comparators: the similarity score function of Stoilos and the normalized Levenshtein edit distance. We propose here to combine them to increase the number of matched medical terms in French. We first took a sample of query logs to determine the thresholds and processing times. In the second run, at a greater scale we tested different combinations of query normalizations before or after misspelling correction with the retained thresholds in the first run. According to the total number of suggestions (around 163, the number of the first sample of queries), at a threshold comparator score of 0.3, the normalized Levenshtein edit distance gave the highest F-Measure (88.15%) and at a threshold comparator score of 0.7, the Stoilos function gave the highest F-Measure (84.31%). By combining Levenshtein and Stoilos, the highest F-Measure (80.28%) is obtained with 0.2 and 0.7 thresholds respectively. However, queries are composed by several terms that may be combination of medical terms. The process of query normalization and segmentation is thus required. The highest F-Measure (64.18%) is obtained when this process is realized before spelling-correction. Despite the widely known high performance of the normalized edit distance of Levenshtein, we show in this paper that its combination with the Stoilos algorithm improved

Accelerating SPARQL Queries and Analytics on RDF Data

KAUST Repository

Al-Harbi, Razen

2016-11-09

The complexity of SPARQL queries and RDF applications poses great challenges on distributed RDF management systems. SPARQL workloads are dynamic and con- sist of queries with variable complexities. Hence, systems that use static partitioning su↵er from communication overhead for workloads that generate excessive communi- cation. Concurrently, RDF applications are becoming more sophisticated, mandating analytical operations that extend beyond SPARQL queries. Being primarily designed and optimized to execute SPARQL queries, which lack procedural capabilities, exist- ing systems are not suitable for rich RDF analytics. This dissertation tackles the problem of accelerating SPARQL queries and RDF analytics on distributed shared-nothing RDF systems. First, a distributed RDF en- gine, coined AdPart, is introduced. AdPart uses lightweight hash partitioning for sharding triples using their subject values; rendering its startup overhead very low. The locality-aware query optimizer of AdPart takes full advantage of the partition- ing to (i) support the fully parallel processing of join patterns on subjects and (ii) minimize data communication for general queries by applying hash distribution of intermediate results instead of broadcasting, wherever possible. By exploiting hash- based locality, AdPart achieves better or comparable performance to systems that employ sophisticated partitioning schemes. To cope with workloads dynamism, AdPart is extended to dynamically adapt to workload changes. AdPart monitors the data access patterns and dynamically redis- tributes and replicates the instances of the most frequent patterns among workers.Consequently, the communication cost for future queries is drastically reduced or even eliminated. Experiments with synthetic and real data verify that AdPart starts faster than all existing systems and gracefully adapts to the query load. Finally, to support and accelerate rich RDF analytical tasks, a vertex-centric RDF analytics framework is

A contribution to semantic indexing and retrieval based on FCA - An application to song datasets

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

International audience; Semantic indexing and retrieval is an important research area, as the available amount of information on the Web is growing more and more. In this paper, we introduce an original approach to semantic indexing and retrieval based on Formal Concept Analysis. The concept lattice is used as a semantic index and we propose an original algorithm for traversing the lattice and answering user queries. This framework has been used and evaluated on a song dataset.

Efficient Approximate OLAP Querying Over Time Series

DEFF Research Database (Denmark)

Perera, Kasun Baruhupolage Don Kasun Sanjeewa; Hahmann, Martin; Lehner, Wolfgang

2016-01-01

The ongoing trend for data gathering not only produces larger volumes of data, but also increases the variety of recorded data types. Out of these, especially time series, e.g. various sensor readings, have attracted attention in the domains of business intelligence and decision making. As OLAP...... queries play a major role in these domains, it is desirable to also execute them on time series data. While this is not a problem on the conceptual level, it can become a bottleneck with regards to query run-time. In general, processing OLAP queries gets more computationally intensive as the volume...... of data grows. This is a particular problem when querying time series data, which generally contains multiple measures recorded at fine time granularities. Usually, this issue is addressed either by scaling up hardware or by employing workload based query optimization techniques. However, these solutions...

Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

Directory of Open Access Journals (Sweden)

Sohail Jabbar

2017-01-01

Full Text Available Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.

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/

Query Processing for Probabilistic State Diagrams Describing Multiple Robot Navigation in an Indoor Environment

Energy Technology Data Exchange (ETDEWEB)

Czejdo, Bogdan [ORNL; Bhattacharya, Sambit [North Carolina Fayetteville State University; Ferragut, Erik M [ORNL

2012-01-01

This paper describes the syntax and semantics of multi-level state diagrams to support probabilistic behavior of cooperating robots. The techniques are presented to analyze these diagrams by querying combined robots behaviors. It is shown how to use state abstraction and transition abstraction to create, verify and process large probabilistic state diagrams.

Semantic Enhancement for Enterprise Data Management

Science.gov (United States)

Ma, Li; Sun, Xingzhi; Cao, Feng; Wang, Chen; Wang, Xiaoyuan; Kanellos, Nick; Wolfson, Dan; Pan, Yue

Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.

Science.gov (United States)

Alirezaie, Marjan; Kiselev, Andrey; Längkvist, Martin; Klügl, Franziska; Loutfi, Amy

2017-11-05

This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment-central Stockholm-in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as "find all regions close to schools and far from the flooded area". The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring

Directory of Open Access Journals (Sweden)

Marjan Alirezaie

2017-11-01

Full Text Available This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

KoralQuery -- A General Corpus Query Protocol

DEFF Research Database (Denmark)

Bingel, Joachim; Diewald, Nils

2015-01-01

. In this paper, we present KoralQuery, a JSON-LD based general corpus query protocol, aiming to be independent of particular QLs, tasks and corpus formats. In addition to describing the system of types and operations that KoralQuery is built on, we exemplify the representation of corpus queries in the serialized...

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

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.

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.

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).

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.

On (dynamic) range minimum queries in external memory

DEFF Research Database (Denmark)

Arge, L.; Fischer, Johannes; Sanders, Peter

2013-01-01

We study the one-dimensional range minimum query (RMQ) problem in the external memory model. We provide the first space-optimal solution to the batched static version of the problem. On an instance with N elements and Q queries, our solution takes Θ(sort(N + Q)) = Θ( N+QB log M /B N+QB ) I...

Designing a federated multimedia information system on the semantic web

NARCIS (Netherlands)

Vdovják, R.; Barna, P.; Houben, G.J.P.M.; Eder, J.; Missikoff, M.

2003-01-01

A federated Web-based multimedia information system on one hand gathers its data from various Web sources, on the other hand offers the end-user a rich semantics describing its content and a user-friendly environment for expressing queries over its data. There are three essential ingredients to

Semantic Legal Policies for Data Exchange and Protection across Super-Peer Domains in the Cloud

Directory of Open Access Journals (Sweden)

Kua-Ping Cheng

2012-10-01

Full Text Available In semantic policy infrastructure, a Trusted Legal Domain (TLD, designated as a Super-Peer Domain (SPD, is a legal cage model used to circumscribe the legal virtual boundary of data disclosure and usage in the cloud. Semantic legal policies in compliance with the law are enforced at the super-peer within an SPD to enable Law-as-a-Service (LaaS for cloud service providers. In addition, cloud users could query fragmented but protected outsourcing cloud data from a law-aware super-peer, where each query is also compliant with the law. Semantic legal policies are logic-based formal policies, which are shown to be a combination of OWL-DL ontologies and stratified Datalog rules with negation, i.e., so-called non-monotonic cq-programs, for policy representation and enforcement. An agent at the super-peer is a unique law-aware guardian that provides protected data integration services for its peers within an SPD. Furthermore, agents at the super-peers specify how law-compliant legal policies are unified with each other to provide protected data exchange services across SPDs in the semantic data cloud.

Dataflow Query Execution in a Parallel Main-Memory Environment

NARCIS (Netherlands)

Wilschut, A.N.; Apers, Peter M.G.

1991-01-01

The performance and characteristics of the execution of various join-trees on a parallel DBMS are studied. The results are a step in the direction of the design of a query optimization strategy that is fit for parallel execution of complex queries. Among others, synchronization issues are identified

Optimizing Aggregate SPARQL Queries Using Materialized RDF Views

DEFF Research Database (Denmark)

Ibragimov, Dilshod; Hose, Katja; Pedersen, Torben Bach

2016-01-01

, this paper proposes MARVEL (MAterialized Rdf Views with Entailment and incompLetness). The approach consists of a view selection algorithm based on an associated RDF-specific cost model, a view definition syntax, and an algorithm for rewriting SPARQL queries using materialized RDF views. The experimental...

An Approach to Measuring Semantic Relatedness of Geographic Terminologies Using a Thesaurus and Lexical Database Sources

Directory of Open Access Journals (Sweden)

Zugang Chen

2018-03-01

Full Text Available In geographic information science, semantic relatedness is important for Geographic Information Retrieval (GIR, Linked Geospatial Data, geoparsing, and geo-semantics. But computing the semantic similarity/relatedness of geographic terminology is still an urgent issue to tackle. The thesaurus is a ubiquitous and sophisticated knowledge representation tool existing in various domains. In this article, we combined the generic lexical database (WordNet or HowNet with the Thesaurus for Geographic Science and proposed a thesaurus–lexical relatedness measure (TLRM to compute the semantic relatedness of geographic terminology. This measure quantified the relationship between terminologies, interlinked the discrete term trees by using the generic lexical database, and realized the semantic relatedness computation of any two terminologies in the thesaurus. The TLRM was evaluated on a new relatedness baseline, namely, the Geo-Terminology Relatedness Dataset (GTRD which was built by us, and the TLRM obtained a relatively high cognitive plausibility. Finally, we applied the TLRM on a geospatial data sharing portal to support data retrieval. The application results of the 30 most frequently used queries of the portal demonstrated that using TLRM could improve the recall of geospatial data retrieval in most situations and rank the retrieval results by the matching scores between the query of users and the geospatial dataset.

Towards Automatic Improvement of Patient Queries in Health Retrieval Systems

Directory of Open Access Journals (Sweden)

Nesrine KSENTINI

2016-07-01

Full Text Available With the adoption of health information technology for clinical health, e-health is becoming usual practice today. Users of this technology find it difficult to seek information relevant to their needs due to the increasing amount of the clinical and medical data on the web, and the lack of knowledge of medical jargon. In this regards, a method is described to improve user's needs by automatically adding new related terms to their queries which appear in the same context of the original query in order to improve final search results. This method is based on the assessment of semantic relationships defined by a proposed statistical method between a set of terms or keywords. Experiments were performed on CLEF-eHealth-2015 database and the obtained results show the effectiveness of our proposed method.

Memory-Aware Query Routing in Interactive Web-based Information Systems

NARCIS (Netherlands)

F. Waas; M.L. Kersten (Martin)

2001-01-01

textabstractQuery throughput is one of the primary optimization goals in interactive web-based information systems in order to achieve the performance necessary to serve large user communities. Queries in this application domain differ significantly from those in traditional database applications:

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

Science.gov (United States)

Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

2017-04-01

In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

Enhancing biomedical text summarization using semantic relation extraction.

Directory of Open Access Journals (Sweden)

Yue Shang

Full Text Available Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1 We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2 We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3 For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

Enhancing biomedical text summarization using semantic relation extraction.

Science.gov (United States)

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

Digital Investigations of AN Archaeological Smart Point Cloud: a Real Time Web-Based Platform to Manage the Visualisation of Semantical Queries

Science.gov (United States)

Poux, F.; Neuville, R.; Hallot, P.; Van Wersch, L.; Luczfalvy Jancsó, A.; Billen, R.

2017-05-01

While virtual copies of the real world tend to be created faster than ever through point clouds and derivatives, their working proficiency by all professionals' demands adapted tools to facilitate knowledge dissemination. Digital investigations are changing the way cultural heritage researchers, archaeologists, and curators work and collaborate to progressively aggregate expertise through one common platform. In this paper, we present a web application in a WebGL framework accessible on any HTML5-compatible browser. It allows real time point cloud exploration of the mosaics in the Oratory of Germigny-des-Prés, and emphasises the ease of use as well as performances. Our reasoning engine is constructed over a semantically rich point cloud data structure, where metadata has been injected a priori. We developed a tool that directly allows semantic extraction and visualisation of pertinent information for the end users. It leads to efficient communication between actors by proposing optimal 3D viewpoints as a basis on which interactions can grow.

The Odyssey Approach for Optimizing Federated SPARQL Queries

DEFF Research Database (Denmark)

Montoya, Gabriela; Skaf-Molli, Hala; Hose, Katja

2017-01-01

. Nevertheless, these plans may still exhibit a high number of intermediate results or high execution times because of heuristics and inaccurate cost estimations. In this paper, we present Odyssey, an approach that uses statistics that allow for a more accurate cost estimation for federated queries and therefore...

Dataflow Query Execution in a Parallel, Main-memory Environment

NARCIS (Netherlands)

Wilschut, A.N.; Apers, Peter M.G.

In this paper, the performance and characteristics of the execution of various join-trees on a parallel DBMS are studied. The results of this study are a step into the direction of the design of a query optimization strategy that is fit for parallel execution of complex queries. Among others,

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases.

Science.gov (United States)

Kobayashi, Norio; Ishii, Manabu; Takahashi, Satoshi; Mochizuki, Yoshiki; Matsushima, Akihiro; Toyoda, Tetsuro

2011-07-01

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org.

Learning via Query Synthesis

KAUST Repository

Alabdulmohsin, Ibrahim Mansour

2017-05-07

Active learning is a subfield of machine learning that has been successfully used in many applications. One of the main branches of active learning is query synthe- sis, where the learning agent constructs artificial queries from scratch in order to reveal sensitive information about the underlying decision boundary. It has found applications in areas, such as adversarial reverse engineering, automated science, and computational chemistry. Nevertheless, the existing literature on membership query synthesis has, generally, focused on finite concept classes or toy problems, with a limited extension to real-world applications. In this thesis, I develop two spectral algorithms for learning halfspaces via query synthesis. The first algorithm is a maximum-determinant convex optimization method while the second algorithm is a Markovian method that relies on Khachiyan’s classical update formulas for solving linear programs. The general theme of these methods is to construct an ellipsoidal approximation of the version space and to synthesize queries, afterward, via spectral decomposition. Moreover, I also describe how these algorithms can be extended to other settings as well, such as pool-based active learning. Having demonstrated that halfspaces can be learned quite efficiently via query synthesis, the second part of this thesis proposes strategies for mitigating the risk of reverse engineering in adversarial environments. One approach that can be used to render query synthesis algorithms ineffective is to implement a randomized response. In this thesis, I propose a semidefinite program (SDP) for learning a distribution of classifiers, subject to the constraint that any individual classifier picked at random from this distributions provides reliable predictions with a high probability. This algorithm is, then, justified both theoretically and empirically. A second approach is to use a non-parametric classification method, such as similarity-based classification. In this

Algebra-Based Optimization of XML-Extended OLAP Queries

DEFF Research Database (Denmark)

Yin, Xuepeng; Pedersen, Torben Bach

2006-01-01

In today’s OLAP systems, integrating fast changing data physically into a cube is complex and time-consuming. Our solution, the “OLAP-XML Federation System,” makes it possible to reference the fast changing data in XML format in OLAP queries without physical integration. In this paper, we introduce...

Persistent Identifiers for Improved Accessibility for Linked Data Querying

Science.gov (United States)

Shepherd, A.; Chandler, C. L.; Arko, R. A.; Fils, D.; Jones, M. B.; Krisnadhi, A.; Mecum, B.

2016-12-01

The adoption of linked open data principles within the geosciences has increased the amount of accessible information available on the Web. However, this data is difficult to consume for those who are unfamiliar with Semantic Web technologies such as Web Ontology Language (OWL), Resource Description Framework (RDF) and SPARQL - the RDF query language. Consumers would need to understand the structure of the data and how to efficiently query it. Furthermore, understanding how to query doesn't solve problems of poor precision and recall in search results. For consumers unfamiliar with the data, full-text searches are most accessible, but not ideal as they arrest the advantages of data disambiguation and co-reference resolution efforts. Conversely, URI searches across linked data can deliver improved search results, but knowledge of these exact URIs may remain difficult to obtain. The increased adoption of Persistent Identifiers (PIDs) can lead to improved linked data querying by a wide variety of consumers. Because PIDs resolve to a single entity, they are an excellent data point for disambiguating content. At the same time, PIDs are more accessible and prominent than a single data provider's linked data URI. When present in linked open datasets, PIDs provide balance between the technical and social hurdles of linked data querying as evidenced by the NSF EarthCube GeoLink project. The GeoLink project, funded by NSF's EarthCube initiative, have brought together data 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 ecosystems and biogeochemistry to paleoclimatology.

Graphical modeling and query language for hospitals.

Science.gov (United States)

Barzdins, Janis; Barzdins, Juris; Rencis, Edgars; Sostaks, Agris

2013-01-01

So far there has been little evidence that implementation of the health information technologies (HIT) is leading to health care cost savings. One of the reasons for this lack of impact by the HIT likely lies in the complexity of the business process ownership in the hospitals. The goal of our research is to develop a business model-based method for hospital use which would allow doctors to retrieve directly the ad-hoc information from various hospital databases. We have developed a special domain-specific process modelling language called the MedMod. Formally, we define the MedMod language as a profile on UML Class diagrams, but we also demonstrate it on examples, where we explain the semantics of all its elements informally. Moreover, we have developed the Process Query Language (PQL) that is based on MedMod process definition language. The purpose of PQL is to allow a doctor querying (filtering) runtime data of hospital's processes described using MedMod. The MedMod language tries to overcome deficiencies in existing process modeling languages, allowing to specify the loosely-defined sequence of the steps to be performed in the clinical process. The main advantages of PQL are in two main areas - usability and efficiency. They are: 1) the view on data through "glasses" of familiar process, 2) the simple and easy-to-perceive means of setting filtering conditions require no more expertise than using spreadsheet applications, 3) the dynamic response to each step in construction of the complete query that shortens the learning curve greatly and reduces the error rate, and 4) the selected means of filtering and data retrieving allows to execute queries in O(n) time regarding the size of the dataset. We are about to continue developing this project with three further steps. First, we are planning to develop user-friendly graphical editors for the MedMod process modeling and query languages. The second step is to do evaluation of usability the proposed language and tool

A semantically-aided architecture for a web-based monitoring system for carotid atherosclerosis.

Science.gov (United States)

Kolias, Vassileios D; Stamou, Giorgos; Golemati, Spyretta; Stoitsis, Giannis; Gkekas, Christos D; Liapis, Christos D; Nikita, Konstantina S

2015-08-01

Carotid atherosclerosis is a multifactorial disease and its clinical diagnosis depends on the evaluation of heterogeneous clinical data, such as imaging exams, biochemical tests and the patient's clinical history. The lack of interoperability between Health Information Systems (HIS) does not allow the physicians to acquire all the necessary data for the diagnostic process. In this paper, a semantically-aided architecture is proposed for a web-based monitoring system for carotid atherosclerosis that is able to gather and unify heterogeneous data with the use of an ontology and to create a common interface for data access enhancing the interoperability of HIS. The architecture is based on an application ontology of carotid atherosclerosis that is used to (a) integrate heterogeneous data sources on the basis of semantic representation and ontological reasoning and (b) access the critical information using SPARQL query rewriting and ontology-based data access services. The architecture was tested over a carotid atherosclerosis dataset consisting of the imaging exams and the clinical profile of 233 patients, using a set of complex queries, constructed by the physicians. The proposed architecture was evaluated with respect to the complexity of the queries that the physicians could make and the retrieval speed. The proposed architecture gave promising results in terms of interoperability, data integration of heterogeneous sources with an ontological way and expanded capabilities of query and retrieval in HIS.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

Science.gov (United States)

Waagmeester, Andra; Kutmon, Martina; Riutta, Anders; Miller, Ryan; Willighagen, Egon L; Evelo, Chris T; Pico, Alexander R

2016-06-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

Directory of Open Access Journals (Sweden)

Andra Waagmeester

2016-06-01

Full Text Available The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources

Science.gov (United States)

Waagmeester, Andra; Pico, Alexander R.

2016-01-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. PMID:27336457

An Efficient Algorithm for Maximizing Range Sum Queries in a Road Network

Directory of Open Access Journals (Sweden)

Tien-Khoi Phan

2014-01-01

Full Text Available Given a set of positive-weighted points and a query rectangle r (specified by a client of given extents, the goal of a maximizing range sum (MaxRS query is to find the optimal location of r such that the total weights of all the points covered by r are maximized. All existing methods for processing MaxRS queries assume the Euclidean distance metric. In many location-based applications, however, the motion of a client may be constrained by an underlying (spatial road network; that is, the client cannot move freely in space. This paper addresses the problem of processing MaxRS queries in a road network. We propose the external-memory algorithm that is suited for a large road network database. In addition, in contrast to the existing methods, which retrieve only one optimal location, our proposed algorithm retrieves all the possible optimal locations. Through simulations, we evaluate the performance of the proposed algorithm.

Parasol: An Architecture for Cross-Cloud Federated Graph Querying

Energy Technology Data Exchange (ETDEWEB)

Lieberman, Michael; Choudhury, Sutanay; Hughes, Marisa; Patrone, Dennis; Hider, Sandy; Piatko, Christine; Chapman, Matthew; Marple, JP; Silberberg, David

2014-06-22

Large scale data fusion of multiple datasets can often provide in- sights that examining datasets individually cannot. However, when these datasets reside in different data centers and cannot be collocated due to technical, administrative, or policy barriers, a unique set of problems arise that hamper querying and data fusion. To ad- dress these problems, a system and architecture named Parasol is presented that enables federated queries over graph databases residing in multiple clouds. Parasol’s design is flexible and requires only minimal assumptions for participant clouds. Query optimization techniques are also described that are compatible with Parasol’s lightweight architecture. Experiments on a prototype implementation of Parasol indicate its suitability for cross-cloud federated graph queries.

Hierarchical Matching of Traffic Information Services Using Semantic Similarity

Directory of Open Access Journals (Sweden)

Zongtao Duan

2018-01-01

Full Text Available Service matching aims to find the information similar to a given query, which has numerous applications in web search. Although existing methods yield promising results, they are not applicable for transportation. In this paper, we propose a multilevel matching method based on semantic technology, towards efficiently searching the traffic information requested. Our approach is divided into two stages: service clustering, which prunes candidate services that are not promising, and functional matching. The similarity at function level between services is computed by grouping the connections between the services into inheritance and noninheritance relationships. We also developed a three-layer framework with a semantic similarity measure that requires less time and space cost than existing method since the scale of candidate services is significantly smaller than the whole transportation network. The OWL_TC4 based service set was used to verify the proposed approach. The accuracy of offline service clustering reached 93.80%, and it reduced the response time to 651 ms when the total number of candidate services was 1000. Moreover, given the different thresholds for the semantic similarity measure, the proposed mixed matching model did better in terms of recall and precision (i.e., up to 72.7% and 80%, respectively, for more than 1000 services compared to the compared models based on information theory and taxonomic distance. These experimental results confirmed the effectiveness and validity of service matching for responding quickly and accurately to user queries.

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.

Minimizing I/O Costs of Multi-Dimensional Queries with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2006-03-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex,multi-dimensional queries where traditional tree-based indices would not work efficiently. A common approach for reducing the size of a bitmap index for high cardinality attributes is to group ranges of values of an attribute into bins and then build a bitmap for each bin rather than a bitmap for each value of the attribute. Binning reduces storage costs,however, results of queries based on bins often require additional filtering for discarding it false positives, i.e., records in the result that do not satisfy the query constraints. This additional filtering,also known as ''candidate checking,'' requires access to the base data on disk and involves significant I/O costs. This paper studies strategies for minimizing the I/O costs for ''candidate checking'' for multi-dimensional queries. This is done by determining the number of bins allocated for each dimension and then placing bin boundaries in optimal locations. Our algorithms use knowledge of data distribution and query workload. We derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

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.

A JBI Information Object Engineering Environment Utilizing Metadata Fragments for Refining Searches on Semantically-Related Object Types

National Research Council Canada - National Science Library

Harlow, Felicia N

2005-01-01

.... This enhancement will improve the ability of JBI users to create and store IO type schemas, and query and subscribe to information objects, which may be semantically related by their inclusion...

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

Navigation as a New Form of Search for Agricultural Learning Resources in Semantic Repositories

Science.gov (United States)

Cano, Ramiro; Abián, Alberto; Mena, Elena

Education is essential when it comes to raise public awareness on the environmental and economic benefits of organic agriculture and agroecology (OA & AE). Organic.Edunet, an EU funded project, aims at providing a freely-available portal where learning contents on OA & AE can be published and accessed through specialized technologies. This paper describes a novel mechanism for providing semantic capabilities (such as semantic navigational queries) to an arbitrary set of agricultural learning resources, in the context of the Organic.Edunet initiative.

Semantic Web repositories for genomics data using the eXframe platform.

Science.gov (United States)

Merrill, Emily; Corlosquet, Stéphane; Ciccarese, Paolo; Clark, Tim; Das, Sudeshna

2014-01-01

With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge.

A semantically rich and standardised approach enhancing discovery of sensor data and metadata

Science.gov (United States)

Kokkinaki, Alexandra; Buck, Justin; Darroch, Louise

2016-04-01

The marine environment plays an essential role in the earth's climate. To enhance the ability to monitor the health of this important system, innovative sensors are being produced and combined with state of the art sensor technology. As the number of sensors deployed is continually increasing,, it is a challenge for data users to find the data that meet their specific needs. Furthermore, users need to integrate diverse ocean datasets originating from the same or even different systems. Standards provide a solution to the above mentioned challenges. The Open Geospatial Consortium (OGC) has created Sensor Web Enablement (SWE) standards that enable different sensor networks to establish syntactic interoperability. When combined with widely accepted controlled vocabularies, they become semantically rich and semantic interoperability is achievable. In addition, Linked Data is the recommended best practice for exposing, sharing and connecting information on the Semantic Web using Uniform Resource Identifiers (URIs), Resource Description Framework (RDF) and RDF Query Language (SPARQL). As part of the EU-funded SenseOCEAN project, the British Oceanographic Data Centre (BODC) is working on the standardisation of sensor metadata enabling 'plug and play' sensor integration. Our approach combines standards, controlled vocabularies and persistent URIs to publish sensor descriptions, their data and associated metadata as 5 star Linked Data and OGC SWE (SensorML, Observations & Measurements) standard. Thus sensors become readily discoverable, accessible and useable via the web. Content and context based searching is also enabled since sensors descriptions are understood by machines. Additionally, sensor data can be combined with other sensor or Linked Data datasets to form knowledge. This presentation will describe the work done in BODC to achieve syntactic and semantic interoperability in the sensor domain. It will illustrate the reuse and extension of the Semantic Sensor

Linked data querying through FCA-based schema indexing

OpenAIRE

Brosius, Dominik; Staab, Steffen

2016-01-01

The effciency of SPARQL query evaluation against Linked Open Data may benefit from schema-based indexing. However, many data items come with incomplete schema information or lack schema descriptions entirely. In this position paper, we outline an approach to an indexing of linked data graphs based on schemata induced through Formal Concept Analysis. We show how to map queries onto RDF graphs based on such derived schema information. We sketch next steps for realizing and optimizing the sugges...

COEUS: "semantic web in a box" for biomedical applications.

Science.gov (United States)

Lopes, Pedro; Oliveira, José Luís

2012-12-17

As the "omics" revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter's complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a "semantic web in a box" approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/.

Semantic Web and Inferencing Technologies for Department of Defense Systems

Science.gov (United States)

2014-10-01

components: data model, semantics, serialization, and query language. The data model defines a collection of datatypes suitable for composing abstract...views of web content. Available datatypes might include strings, integers, single- and double-precision floating point numbers, URLs, and hyperlinks...In addition to atomic datatypes , data models typically provide rules and mechanisms for defining complex data types or restrictions on existing

Query deforestation

OpenAIRE

Grust, Torsten; Scholl, Marc H.

1998-01-01

The construction of a declarative query engine for a DBMS includes the challenge of compiling algebraic queries into efficient execution plans that can be run on top of the persistent storage. This work pursues the goal of employing foldr-build deforestation for the derivation of efficient streaming programs - programs that do not allocate intermediate data structures to perform their task - from algebraic (combinator) query plans. The query engine is based on the insertion representation of ...

External Data Structures for Shortest Path Queries on Planar Digraphs

DEFF Research Database (Denmark)

Arge, Lars; Toma, Laura

2005-01-01

In this paper we present space-query trade-offs for external memory data structures that answer shortest path queries on planar directed graphs. For any S = Ω(N 1 + ε) and S = O(N2/B), our main result is a family of structures that use S space and answer queries in O(N2/ S B) I/Os, thus obtaining...... optimal space-query product O(N2/B). An S space structure can be constructed in O(√S · sort(N)) I/Os, where sort(N) is the number of I/Os needed to sort N elements, B is the disk block size, and N is the size of the graph....

Robust Runtime Optimization and Skew-Resistant Execution of Analytical SPARQL Queries on Pig

NARCIS (Netherlands)

S Kotoulas; J. Urbani; P.A. Boncz (Peter); P. Mika

2012-01-01

textabstractWe describe a system that incrementally translates SPARQL queries to Pig Latin and executes them on a Hadoop cluster. This system is designed to work eciently on complex queries with many self-joins over huge datasets, avoiding job failures even in the case of joins with unexpected

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration

Science.gov (United States)

2011-01-01

Background Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Results Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. Conclusions By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full

Agricultural Library Information Retrieval Based on Improved Semantic Algorithm

OpenAIRE

Meiling , Xie

2014-01-01

International audience; To support users to quickly access information they need from the agricultural library’s vast information and to improve the low intelligence query service, a model for intelligent library information retrieval was constructed. The semantic web mode was introduced and the information retrieval framework was designed. The model structure consisted of three parts: Information data integration, user interface and information retrieval match. The key method supporting retr...

Design and evaluation of a NoSQL database for storing and querying RDF data

Directory of Open Access Journals (Sweden)

Kanda Runapongsa Saikaew

2014-12-01

Full Text Available Currently the amount of web data has increased excessively. Its metadata is widely used in order to fully exploit web information resources. This causes the need for Semantic Web technology to quickly analyze such big data. Resource Description Framework (RDF is a standard for describing web resources. In this paper, we propose a method to exploit a NoSQL database, specifically MongoDB, to store and query RDF data. We choose MongoDB to represent a NoSQL database because it is one of the most popular high-performance NoSQL databases. We evaluate the proposed design and implementation by using the Berlin SPARQL Benchmark, which is one of the most widely accepted benchmarks for comparing the performance of RDF storage systems. We compare three database systems, which are Apache Jena TDB (native RDF store, MySQL (relational database, and our proposed system with MongoDB (NoSQL database. Based on the experimental results analysis, our proposed system outperforms other database systems for most queries when the data set size is small. However, for a larger data set, MongoDB performs well for queries with simple operators while MySQL offers an efficient solution for complex queries. The result of this work can provide some guideline for choosing an appropriate RDF database system and applying a NoSQL database in storing and querying RDF data.

Semantically Enriching the Search System of a Music Digital Library

Science.gov (United States)

de Juan, Paloma; Iglesias, Carlos

Traditional search systems are usually based on keywords, a very simple and convenient mechanism to express a need for information. This is the most popular way of searching the Web, although it is not always an easy task to accurately summarize a natural language query in a few keywords. Working with keywords means losing the context, which is the only thing that can help us deal with ambiguity. This is the biggest problem of keyword-based systems. Semantic Web technologies seem a perfect solution to this problem, since they make it possible to represent the semantics of a given domain. In this chapter, we present three projects, Harmos, Semusici and Cantiga, whose aim is to provide access to a music digital library. We will describe two search systems, a traditional one and a semantic one, developed in the context of these projects and compare them in terms of usability and effectiveness.

Time-dependent Networks as Models to Achieve Fast Exact Time-table Queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Jacob, Rico

2001-01-01

We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models.......We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models....

Semantic integration of medication data into the EHOP Clinical Data Warehouse.

Science.gov (United States)

Delamarre, Denis; Bouzille, Guillaume; Dalleau, Kevin; Courtel, Denis; Cuggia, Marc

2015-01-01

Reusing medication data is crucial for many medical research domains. Semantic integration of such data in clinical data warehouse (CDW) is quite challenging. Our objective was to develop a reliable and scalable method for integrating prescription data into EHOP (a French CDW). PN13/PHAST was used as the semantic interoperability standard during the ETL process, and to store the prescriptions as documents in the CDW. Theriaque was used as a drug knowledge database (DKDB), to annotate the prescription dataset with the finest granularity, and to provide semantic capabilities to the EHOP query workbench. the system was evaluated on a clinical data set. Depending on the use case, the precision ranged from 52% to 100%, Recall was always 100%. interoperability standards and DKDB, document approach, and the finest granularity approach are the key factors for successful drug data integration in CDW.

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.

BioFed: federated query processing over life sciences linked open data.

Science.gov (United States)

Hasnain, Ali; Mehmood, Qaiser; Sana E Zainab, Syeda; Saleem, Muhammad; Warren, Claude; Zehra, Durre; Decker, Stefan; Rebholz-Schuhmann, Dietrich

2017-03-15

Biomedical data, e.g. from knowledge bases and ontologies, is increasingly made available following open linked data principles, at best as RDF triple data. This is a necessary step towards unified access to biological data sets, but this still requires solutions to query multiple endpoints for their heterogeneous data to eventually retrieve all the meaningful information. Suggested solutions are based on query federation approaches, which require the submission of SPARQL queries to endpoints. Due to the size and complexity of available data, these solutions have to be optimised for efficient retrieval times and for users in life sciences research. Last but not least, over time, the reliability of data resources in terms of access and quality have to be monitored. Our solution (BioFed) federates data over 130 SPARQL endpoints in life sciences and tailors query submission according to the provenance information. BioFed has been evaluated against the state of the art solution FedX and forms an important benchmark for the life science domain. The efficient cataloguing approach of the federated query processing system 'BioFed', the triple pattern wise source selection and the semantic source normalisation forms the core to our solution. It gathers and integrates data from newly identified public endpoints for federated access. Basic provenance information is linked to the retrieved data. Last but not least, BioFed makes use of the latest SPARQL standard (i.e., 1.1) to leverage the full benefits for query federation. The evaluation is based on 10 simple and 10 complex queries, which address data in 10 major and very popular data sources (e.g., Dugbank, Sider). BioFed is a solution for a single-point-of-access for a large number of SPARQL endpoints providing life science data. It facilitates efficient query generation for data access and provides basic provenance information in combination with the retrieved data. BioFed fully supports SPARQL 1.1 and gives access to the

Optimization of Extended Relational Database Systems

Science.gov (United States)

1986-07-23

control functions are integrated into a single system in a homogeneoua way. As a first exam - ple, consider previous work in supporting various semantic...sizes are reduced and, wnk? quently, the number of materializations that will be needed is aba lower. For exam - pie, in the above query tuple...retrieve (EMP.name) where EMP hobbies instrument = ’ violin ’ When the various entries in the hobbies field are materialized, only those queries that

A data base processor semantics specification package

Science.gov (United States)

Fishwick, P. A.

1983-01-01

A Semantics Specification Package (DBPSSP) for the Intel Data Base Processor (DBP) is defined. DBPSSP serves as a collection of cross assembly tools that allow the analyst to assemble request blocks on the host computer for passage to the DBP. The assembly tools discussed in this report may be effectively used in conjunction with a DBP compatible data communications protocol to form a query processor, precompiler, or file management system for the database processor. The source modules representing the components of DBPSSP are fully commented and included.

Using Query Languages and Mobile Code to Reduce Service Invocation Costs

National Research Council Canada - National Science Library

Szymanski, R; Palmer, N; Chase, T

2006-01-01

.... As a concrete example, this paper describes work being performed by CERDEC C2D (Communications Electronics Research, Development, and Engineering Center - Command and Control Directorate) at Fort Monmouth, NJ to expose a military mission plan as a web service through the use of simple SQL-like (Structured Query Language) statements optimized for mission data query.

QuerySpaces on Hadoop for the ATLAS EventIndex

CERN Document Server

Hrivnac, Julius; The ATLAS collaboration; Cranshaw, Jack; Favareto, Andrea; Prokoshin, Fedor; Glasman, Claudia; Toebbicke, Rainer

2015-01-01

A Hadoop-based implementation of the adaptive query engine serving as the back-end for the ATLAS EventIndex. The QuerySpaces implementation handles both original data and search results providing fast and efficient mechanisms for new user queries using already accumulated knowledge for optimization. Detailed descriptions and statistics about user requests are collected in HBase tables and HDFS files. Requests are associated to their results and a graph of relations between them is created to be used to find the most efficient way of providing answers to new requests The environment is completely transparent to users and is accessible over several command-line interfaces, a Web Service and a programming API.

Learning from the History of Distributed Query Processing

DEFF Research Database (Denmark)

Betz, Heiko; Gropengießer, Francis; Hose, Katja

2012-01-01

The vision of the Semantic Web has triggered the development of various new applications and opened up new directions in research. Recently, much effort has been put into the development of techniques for query processing over Linked Data. Being based upon techniques originally developed...... for distributed and federated databases, some of them inherit the same or similar problems. Thus, the goal of this paper is to point out pitfalls that the previous generation of researchers has already encountered and to introduce the Linked Data as a Service as an idea that has the potential to solve the problem...... in some scenarios. Hence, this paper discusses nine theses about Linked Data processing and sketches a research agenda for future endeavors in the area of Linked Data processing....

Processing SPARQL queries with regular expressions in RDF databases

Science.gov (United States)

2011-01-01

Background As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users’ requests for extracting information from the RDF data as well as the lack of users’ knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns. PMID:21489225

Processing SPARQL queries with regular expressions in RDF databases.

Science.gov (United States)

Lee, Jinsoo; Pham, Minh-Duc; Lee, Jihwan; Han, Wook-Shin; Cho, Hune; Yu, Hwanjo; Lee, Jeong-Hoon

2011-03-29

As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

Learning semantic and visual similarity for endomicroscopy video retrieval.

Science.gov (United States)

Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them

Approximate dictionary queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Gasieniec, Leszek

1996-01-01

Given a set of n binary strings of length m each. We consider the problem of answering d-queries. Given a binary query string of length m, a d-query is to report if there exists a string in the set within Hamming distance d of . We present a data structure of size O(nm) supporting 1-queries in ti...

Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety.

Science.gov (United States)

Saeb, Sohrab; Lattie, Emily G; Kording, Konrad P; Mohr, David C

2017-08-10

Is someone at home, at their friend's place, at a restaurant, or enjoying the outdoors? Knowing the semantic location of an individual matters for delivering medical interventions, recommendations, and other context-aware services. This knowledge is particularly useful in mental health care for monitoring relevant behavioral indicators to improve treatment delivery. Local search-and-discovery services such as Foursquare can be used to detect semantic locations based on the global positioning system (GPS) coordinates, but GPS alone is often inaccurate. Mobile phones can also sense other signals (such as movement, light, and sound), and the use of these signals promises to lead to a better estimation of an individual's semantic location. We aimed to examine the ability of mobile phone sensors to estimate semantic locations, and to evaluate the relationship between semantic location visit patterns and depression and anxiety. A total of 208 participants across the United States were asked to log the type of locations they visited daily, using their mobile phones for a period of 6 weeks, while their phone sensor data was recorded. Using the sensor data and Foursquare queries based on GPS coordinates, we trained models to predict these logged locations, and evaluated their prediction accuracy on participants that models had not seen during training. We also evaluated the relationship between the amount of time spent in each semantic location and depression and anxiety assessed at baseline, in the middle, and at the end of the study. While Foursquare queries detected true semantic locations with an average area under the curve (AUC) of 0.62, using phone sensor data alone increased the AUC to 0.84. When we used Foursquare and sensor data together, the AUC further increased to 0.88. We found some significant relationships between the time spent in certain locations and depression and anxiety, although these relationships were not consistent. The accuracy of location

Protecting count queries in study design.

Science.gov (United States)

Vinterbo, Staal A; Sarwate, Anand D; Boxwala, Aziz A

2012-01-01

Today's clinical research institutions provide tools for researchers to query their data warehouses for counts of patients. To protect patient privacy, counts are perturbed before reporting; this compromises their utility for increased privacy. The goal of this study is to extend current query answer systems to guarantee a quantifiable level of privacy and allow users to tailor perturbations to maximize the usefulness according to their needs. A perturbation mechanism was designed in which users are given options with respect to scale and direction of the perturbation. The mechanism translates the true count, user preferences, and a privacy level within administrator-specified bounds into a probability distribution from which the perturbed count is drawn. Users can significantly impact the scale and direction of the count perturbation and can receive more accurate final cohort estimates. Strong and semantically meaningful differential privacy is guaranteed, providing for a unified privacy accounting system that can support role-based trust levels. This study provides an open source web-enabled tool to investigate visually and numerically the interaction between system parameters, including required privacy level and user preference settings. Quantifying privacy allows system administrators to provide users with a privacy budget and to monitor its expenditure, enabling users to control the inevitable loss of utility. While current measures of privacy are conservative, this system can take advantage of future advances in privacy measurement. The system provides new ways of trading off privacy and utility that are not provided in current study design systems.

Spatial Search Techniques for Mobile 3D Queries in Sensor Web Environments

Directory of Open Access Journals (Sweden)

James D. Carswell

2013-03-01

Full Text Available Developing mobile geo-information systems for sensor web applications involves technologies that can access linked geographical and semantically related Internet information. Additionally, in tomorrow’s Web 4.0 world, it is envisioned that trillions of inexpensive micro-sensors placed throughout the environment will also become available for discovery based on their unique geo-referenced IP address. Exploring these enormous volumes of disparate heterogeneous data on today’s location and orientation aware smartphones requires context-aware smart applications and services that can deal with “information overload”. 3DQ (Three Dimensional Query is our novel mobile spatial interaction (MSI prototype that acts as a next-generation base for human interaction within such geospatial sensor web environments/urban landscapes. It filters information using “Hidden Query Removal” functionality that intelligently refines the search space by calculating the geometry of a three dimensional visibility shape (Vista space at a user’s current location. This 3D shape then becomes the query “window” in a spatial database for retrieving information on only those objects visible within a user’s actual 3D field-of-view. 3DQ reduces information overload and serves to heighten situation awareness on constrained commercial off-the-shelf devices by providing visibility space searching as a mobile web service. The effects of variations in mobile spatial search techniques in terms of query speed vs. accuracy are evaluated and presented in this paper.

TopFed: TCGA tailored federated query processing and linking to LOD.

Science.gov (United States)

Saleem, Muhammad; Padmanabhuni, Shanmukha S; Ngomo, Axel-Cyrille Ngonga; Iqbal, Aftab; Almeida, Jonas S; Decker, Stefan; Deus, Helena F

2014-01-01

The Cancer Genome Atlas (TCGA) is a multidisciplinary, multi-institutional effort to catalogue genetic mutations responsible for cancer using genome analysis techniques. One of the aims of this project is to create a comprehensive and open repository of cancer related molecular analysis, to be exploited by bioinformaticians towards advancing cancer knowledge. However, devising bioinformatics applications to analyse such large dataset is still challenging, as it often requires downloading large archives and parsing the relevant text files. Therefore, it is making it difficult to enable virtual data integration in order to collect the critical co-variates necessary for analysis. We address these issues by transforming the TCGA data into the Semantic Web standard Resource Description Format (RDF), link it to relevant datasets in the Linked Open Data (LOD) cloud and further propose an efficient data distribution strategy to host the resulting 20.4 billion triples data via several SPARQL endpoints. Having the TCGA data distributed across multiple SPARQL endpoints, we enable biomedical scientists to query and retrieve information from these SPARQL endpoints by proposing a TCGA tailored federated SPARQL query processing engine named TopFed. We compare TopFed with a well established federation engine FedX in terms of source selection and query execution time by using 10 different federated SPARQL queries with varying requirements. Our evaluation results show that TopFed selects on average less than half of the sources (with 100% recall) with query execution time equal to one third to that of FedX. With TopFed, we aim to offer biomedical scientists a single-point-of-access through which distributed TCGA data can be accessed in unison. We believe the proposed system can greatly help researchers in the biomedical domain to carry out their research effectively with TCGA as the amount and diversity of data exceeds the ability of local resources to handle its retrieval and

Topics in Semantics-based Program Manipulation

DEFF Research Database (Denmark)

Grobauer, Bernt

four articles in the field of semantics-based techniques for program manipulation: three articles are about partial evaluation, a method for program specialization; the fourth article treats an approach to automatic cost analysis. Partial evaluation optimizes programs by specializing them with respect...... article in this dissertation describes how the second Futamura projection can be achieved for type-directed partial evaluation (TDPE), a relatively recent approach to partial evaluation: We derive an ML implementation of the second Futamura projection for TDPE. Due to the differences between ‘traditional...... denotational semantics—allows us to relate various possible semantics to each other both conceptually and formally. We thus are able to explain goal-directed evaluation using an intuitive list-based semantics, while using a continuation semantics for semantics-based compilation through partial evaluation...

Time-Dependent Networks as Models to Achieve Fast Exact Time-Table Queries

DEFF Research Database (Denmark)

Brodal, Gert Stølting; Jacob, Rico

2003-01-01

We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries for travelers using a train system. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models.......We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries for travelers using a train system. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models....

Query responses

Directory of Open Access Journals (Sweden)

Paweł Łupkowski

2017-05-01

Full Text Available In this article we consider the phenomenon of answering a query with a query. Although such answers are common, no large scale, corpus-based characterization exists, with the exception of clarification requests. After briefly reviewing different theoretical approaches on this subject, we present a corpus study of query responses in the British National Corpus and develop a taxonomy for query responses. We point at a variety of response categories that have not been formalized in previous dialogue work, particularly those relevant to adversarial interaction. We show that different response categories have significantly different rates of subsequent answer provision. We provide a formal analysis of the response categories in the framework of KoS.

Recommending Multidimensional Queries

Science.gov (United States)

Giacometti, Arnaud; Marcel, Patrick; Negre, Elsa

Interactive analysis of datacube, in which a user navigates a cube by launching a sequence of queries is often tedious since the user may have no idea of what the forthcoming query should be in his current analysis. To better support this process we propose in this paper to apply a Collaborative Work approach that leverages former explorations of the cube to recommend OLAP queries. The system that we have developed adapts Approximate String Matching, a technique popular in Information Retrieval, to match the current analysis with the former explorations and help suggesting a query to the user. Our approach has been implemented with the open source Mondrian OLAP server to recommend MDX queries and we have carried out some preliminary experiments that show its efficiency for generating effective query recommendations.

Answering PICO Clinical Questions: a Semantic Graph-Based Approach

OpenAIRE

Znaidi , Eya; Tamine , Lynda; Latiri , Chiraz

2015-01-01

International audience; In this paper, we tackle the issue related to the retrieval of the best evidence that fits with a PICO (Population, Intervention, Comparison and Outcome) question. We propose a new document ranking algorithm that relies on semantic based query expansion bounded by the local search context to better discard irrelevant documents. Experiments using a standard dataset including 423 PICO questions and more than 1,2 million of documents, show that our aproach is promising.

Scaling the walls of discovery: using semantic metadata for integrative problem solving.

Science.gov (United States)

Manning, Maurice; Aggarwal, Amit; Gao, Kevin; Tucker-Kellogg, Greg

2009-03-01

Current data integration approaches by bioinformaticians frequently involve extracting data from a wide variety of public and private data repositories, each with a unique vocabulary and schema, via scripts. These separate data sets must then be normalized through the tedious and lengthy process of resolving naming differences and collecting information into a single view. Attempts to consolidate such diverse data using data warehouses or federated queries add significant complexity and have shown limitations in flexibility. The alternative of complete semantic integration of data requires a massive, sustained effort in mapping data types and maintaining ontologies. We focused instead on creating a data architecture that leverages semantic mapping of experimental metadata, to support the rapid prototyping of scientific discovery applications with the twin goals of reducing architectural complexity while still leveraging semantic technologies to provide flexibility, efficiency and more fully characterized data relationships. A metadata ontology was developed to describe our discovery process. A metadata repository was then created by mapping metadata from existing data sources into this ontology, generating RDF triples to describe the entities. Finally an interface to the repository was designed which provided not only search and browse capabilities but complex query templates that aggregate data from both RDF and RDBMS sources. We describe how this approach (i) allows scientists to discover and link relevant data across diverse data sources and (ii) provides a platform for development of integrative informatics applications.

A Semantic Sensor Web for Environmental Decision Support Applications

Science.gov (United States)

Gray, Alasdair J. G.; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A. A.; Paton, Norman W.; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

2011-01-01

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England. PMID:22164110

Processing SPARQL queries with regular expressions in RDF databases

Directory of Open Access Journals (Sweden)

Cho Hune

2011-03-01

Full Text Available Abstract Background As the Resource Description Framework (RDF data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf or Bio2RDF (bio2rdf.org, SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users’ requests for extracting information from the RDF data as well as the lack of users’ knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1 We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2 We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3 We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

A novel architecture for information retrieval system based on semantic web

Science.gov (United States)

Zhang, Hui

2011-12-01

Nowadays, the web has enabled an explosive growth of information sharing (there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. The challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document. To address this issue, Berners-Lee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.

An hybrid method for the Arabic queries disambiguation to improve the relevance calculation in the IRS

OpenAIRE

Adil ENAANAI, Aziz SDIGUI DOUKKALI, El habib BENLAHMER

2012-01-01

In the information systems, the query’s expansion brings more benefices in the relevant documents extraction. However, the current expansion types are focused on the retrieve of the maximum of documents (reduce the silence). In Arabic, the queries are derived in many morphosemantical variants. Hence the diversity of the semantic interpretations that often creates a problem of ambiguity. Our objective is to prepare the Arabic request before its introduction to the document retrieval system. Th...

GeoSpark SQL: An Effective Framework Enabling Spatial Queries on Spark

Directory of Open Access Journals (Sweden)

Zhou Huang

2017-09-01

Full Text Available In the era of big data, Internet-based geospatial information services such as various LBS apps are deployed everywhere, followed by an increasing number of queries against the massive spatial data. As a result, the traditional relational spatial database (e.g., PostgreSQL with PostGIS and Oracle Spatial cannot adapt well to the needs of large-scale spatial query processing. Spark is an emerging outstanding distributed computing framework in the Hadoop ecosystem. This paper aims to address the increasingly large-scale spatial query-processing requirement in the era of big data, and proposes an effective framework GeoSpark SQL, which enables spatial queries on Spark. On the one hand, GeoSpark SQL provides a convenient SQL interface; on the other hand, GeoSpark SQL achieves both efficient storage management and high-performance parallel computing through integrating Hive and Spark. In this study, the following key issues are discussed and addressed: (1 storage management methods under the GeoSpark SQL framework, (2 the spatial operator implementation approach in the Spark environment, and (3 spatial query optimization methods under Spark. Experimental evaluation is also performed and the results show that GeoSpark SQL is able to achieve real-time query processing. It should be noted that Spark is not a panacea. It is observed that the traditional spatial database PostGIS/PostgreSQL performs better than GeoSpark SQL in some query scenarios, especially for the spatial queries with high selectivity, such as the point query and the window query. In general, GeoSpark SQL performs better when dealing with compute-intensive spatial queries such as the kNN query and the spatial join query.

Estimating Influenza Outbreaks Using Both Search Engine Query Data and Social Media Data in South Korea.

Science.gov (United States)

Woo, Hyekyung; Cho, Youngtae; Shim, Eunyoung; Lee, Jong-Koo; Lee, Chang-Gun; Kim, Seong Hwan

2016-07-04

As suggested as early as in 2006, logs of queries submitted to search engines seeking information could be a source for detection of emerging influenza epidemics if changes in the volume of search queries are monitored (infodemiology). However, selecting queries that are most likely to be associated with influenza epidemics is a particular challenge when it comes to generating better predictions. In this study, we describe a methodological extension for detecting influenza outbreaks using search query data; we provide a new approach for query selection through the exploration of contextual information gleaned from social media data. Additionally, we evaluate whether it is possible to use these queries for monitoring and predicting influenza epidemics in South Korea. Our study was based on freely available weekly influenza incidence data and query data originating from the search engine on the Korean website Daum between April 3, 2011 and April 5, 2014. To select queries related to influenza epidemics, several approaches were applied: (1) exploring influenza-related words in social media data, (2) identifying the chief concerns related to influenza, and (3) using Web query recommendations. Optimal feature selection by least absolute shrinkage and selection operator (Lasso) and support vector machine for regression (SVR) were used to construct a model predicting influenza epidemics. In total, 146 queries related to influenza were generated through our initial query selection approach. A considerable proportion of optimal features for final models were derived from queries with reference to the social media data. The SVR model performed well: the prediction values were highly correlated with the recent observed influenza-like illness (r=.956; Psearch queries to enhance influenza surveillance in South Korea. In addition, an approach for query selection using social media data seems ideal for supporting influenza surveillance based on search query data.

A semantic web framework to integrate cancer omics data with biological knowledge.

Science.gov (United States)

Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

2012-01-25

The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

In-context query reformulation for failing SPARQL queries

Science.gov (United States)

Viswanathan, Amar; Michaelis, James R.; Cassidy, Taylor; de Mel, Geeth; Hendler, James

2017-05-01

Knowledge bases for decision support systems are growing increasingly complex, through continued advances in data ingest and management approaches. However, humans do not possess the cognitive capabilities to retain a bird's-eyeview of such knowledge bases, and may end up issuing unsatisfiable queries to such systems. This work focuses on the implementation of a query reformulation approach for graph-based knowledge bases, specifically designed to support the Resource Description Framework (RDF). The reformulation approach presented is instance-and schema-aware. Thus, in contrast to relaxation techniques found in the state-of-the-art, the presented approach produces in-context query reformulation.

Google BigQuery analytics

CERN Document Server

Tigani, Jordan

2014-01-01

How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addit

Semantic distance-based creation of clusters of pharmacovigilance terms and their evaluation.

Science.gov (United States)

Dupuch, Marie; Grabar, Natalia

2015-04-01

Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs or biologics. The detection of adverse drug reactions is performed using statistical algorithms and groupings of ADR terms from the MedDRA (Medical Dictionary for Drug Regulatory Activities) terminology. Standardized MedDRA Queries (SMQs) are the groupings which become a standard for assisting the retrieval and evaluation of MedDRA-coded ADR reports worldwide. Currently 84 SMQs have been created, while several important safety topics are not yet covered. Creation of SMQs is a long and tedious process performed by the experts. It relies on manual analysis of MedDRA in order to find out all the relevant terms to be included in a SMQ. Our objective is to propose an automatic method for assisting the creation of SMQs using the clustering of terms which are semantically similar. The experimental method relies on a specific semantic resource, and also on the semantic distance algorithms and clustering approaches. We perform several experiments in order to define the optimal parameters. Our results show that the proposed method can assist the creation of SMQs and make this process faster and systematic. The average performance of the method is precision 59% and recall 26%. The correlation of the results obtained is 0.72 against the medical doctors judgments and 0.78 against the medical coders judgments. These results and additional evaluation indicate that the generated clusters can be efficiently used for the detection of pharmacovigilance signals, as they provide better signal detection than the existing SMQs. Copyright © 2014. Published by Elsevier Inc.

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.

SEMANTIC INDEXING OF TERRASAR-X AND IN SITU DATA FOR URBAN ANALYTICS

Directory of Open Access Journals (Sweden)

D. Espinoza Molina

2015-12-01

Full Text Available This paper presents the semantic indexing of TerraSAR-X images and in situ data. Image processing together with machine learning methods, relevance feedback techniques, and human expertise are used to annotate the image content into a land use land cover catalogue. All the generated information is stored into a geo-database supporting the link between different types of information and the computation of queries and analytics. We used 11 TerraSAR-X scenes over Germany and LUCAS as in situ data. The semantic index is composed of about 73 land use land cover categories found in TerraSAR-X test dataset and 84 categories found in LUCAS dataset.

Digital Workflows for a 3d Semantic Representation of AN Ancient Mining Landscape

Science.gov (United States)

Hiebel, G.; Hanke, K.

2017-08-01

The ancient mining landscape of Schwaz/Brixlegg in the Tyrol, Austria witnessed mining from prehistoric times to modern times creating a first order cultural landscape when it comes to one of the most important inventions in human history: the production of metal. In 1991 a part of this landscape was lost due to an enormous landslide that reshaped part of the mountain. With our work we want to propose a digital workflow to create a 3D semantic representation of this ancient mining landscape with its mining structures to preserve it for posterity. First, we define a conceptual model to integrate the data. It is based on the CIDOC CRM ontology and CRMgeo for geometric data. To transform our information sources to a formal representation of the classes and properties of the ontology we applied semantic web technologies and created a knowledge graph in RDF (Resource Description Framework). Through the CRMgeo extension coordinate information of mining features can be integrated into the RDF graph and thus related to the detailed digital elevation model that may be visualized together with the mining structures using Geoinformation systems or 3D visualization tools. The RDF network of the triple store can be queried using the SPARQL query language. We created a snapshot of mining, settlement and burial sites in the Bronze Age. The results of the query were loaded into a Geoinformation system and a visualization of known bronze age sites related to mining, settlement and burial activities was created.

DISPAQ: Distributed Profitable-Area Query from Big Taxi Trip Data.

Science.gov (United States)

Putri, Fadhilah Kurnia; Song, Giltae; Kwon, Joonho; Rao, Praveen

2017-09-25

One of the crucial problems for taxi drivers is to efficiently locate passengers in order to increase profits. The rapid advancement and ubiquitous penetration of Internet of Things (IoT) technology into transportation industries enables us to provide taxi drivers with locations that have more potential passengers (more profitable areas) by analyzing and querying taxi trip data. In this paper, we propose a query processing system, called Distributed Profitable-Area Query ( DISPAQ ) which efficiently identifies profitable areas by exploiting the Apache Software Foundation's Spark framework and a MongoDB database. DISPAQ first maintains a profitable-area query index (PQ-index) by extracting area summaries and route summaries from raw taxi trip data. It then identifies candidate profitable areas by searching the PQ-index during query processing. Then, it exploits a Z-Skyline algorithm, which is an extension of skyline processing with a Z-order space filling curve, to quickly refine the candidate profitable areas. To improve the performance of distributed query processing, we also propose local Z-Skyline optimization, which reduces the number of dominant tests by distributing killer profitable areas to each cluster node. Through extensive evaluation with real datasets, we demonstrate that our DISPAQ system provides a scalable and efficient solution for processing profitable-area queries from huge amounts of big taxi trip data.

Adaptive query parallelization in multi-core column stores

NARCIS (Netherlands)

M.M. Gawade (Mrunal); M.L. Kersten (Martin); M.M. Gawade (Mrunal); M.L. Kersten (Martin)

2016-01-01

htmlabstractWith the rise of multi-core CPU platforms, their optimal utilization for in-memory OLAP workloads using column store databases has become one of the biggest challenges. Some of the inherent limi- tations in the achievable query parallelism are due to the degree of parallelism

A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

Science.gov (United States)

Sinaci, A Anil; Laleci Erturkmen, Gokce B

2013-10-01

In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

ADEpedia: a scalable and standardized knowledge base of Adverse Drug Events using semantic web technology.

Science.gov (United States)

Jiang, Guoqian; Solbrig, Harold R; Chute, Christopher G

2011-01-01

A source of semantically coded Adverse Drug Event (ADE) data can be useful for identifying common phenotypes related to ADEs. We proposed a comprehensive framework for building a standardized ADE knowledge base (called ADEpedia) through combining ontology-based approach with semantic web technology. The framework comprises four primary modules: 1) an XML2RDF transformation module; 2) a data normalization module based on NCBO Open Biomedical Annotator; 3) a RDF store based persistence module; and 4) a front-end module based on a Semantic Wiki for the review and curation. A prototype is successfully implemented to demonstrate the capability of the system to integrate multiple drug data and ontology resources and open web services for the ADE data standardization. A preliminary evaluation is performed to demonstrate the usefulness of the system, including the performance of the NCBO annotator. In conclusion, the semantic web technology provides a highly scalable framework for ADE data source integration and standard query service.

Analysis of Semantic Networks using Complex Networks Concepts

DEFF Research Database (Denmark)

Ortiz-Arroyo, Daniel

2013-01-01

In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...

Semantic Web applications and tools for the life sciences: SWAT4LS 2010.

Science.gov (United States)

Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott; Splendiani, Andrea

2012-01-25

As Semantic Web technologies mature and new releases of key elements, such as SPARQL 1.1 and OWL 2.0, become available, the Life Sciences continue to push the boundaries of these technologies with ever more sophisticated tools and applications. Unsurprisingly, therefore, interest in the SWAT4LS (Semantic Web Applications and Tools for the Life Sciences) activities have remained high, as was evident during the third international SWAT4LS workshop held in Berlin in December 2010. Contributors to this workshop were invited to submit extended versions of their papers, the best of which are now made available in the special supplement of BMC Bioinformatics. The papers reflect the wide range of work in this area, covering the storage and querying of Life Sciences data in RDF triple stores, tools for the development of biomedical ontologies and the semantics-based integration of Life Sciences as well as clinicial data.

Querying on Federated Sensor Networks

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Zuhal Can

2016-09-01

Full Text Available A Federated Sensor Network (FSN is a network of geographically distributed Wireless Sensor Networks (WSNs called islands. For querying on an FSN, we introduce the Layered Federated Sensor Network (L-FSN Protocol. For layered management, L-FSN provides communication among islands by its inter-island querying protocol by which a query packet routing path is determined according to some path selection policies. L-FSN allows autonomous management of each island by island-specific intra-island querying protocols that can be selected according to island properties. We evaluate the applicability of L-FSN and compare the L-FSN protocol with various querying protocols running on the flat federation model. Flat federation is a method to federate islands by running a single querying protocol on an entire FSN without distinguishing communication among and within islands. For flat federation, we select a querying protocol from geometrical, hierarchical cluster-based, hash-based, and tree-based WSN querying protocol categories. We found that a layered federation of islands by L-FSN increases the querying performance with respect to energy-efficiency, query resolving distance, and query resolving latency. Moreover, L-FSN’s flexibility of choosing intra-island querying protocols regarding the island size brings advantages on energy-efficiency and query resolving latency.

Application of Clustering Algorithm CLOPE to the Query Grouping Problem in the Field of Materialized View Maintenance

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Kateryna Novokhatska

2016-03-01

Full Text Available In recent years, materialized views (MVs are widely used to enhance the database performance by storing pre-calculated results of resource-intensive queries in the physical memory. In order to identify which queries may be potentially materialized, database transaction log for a long period of time should be analyzed. The goal of analysis is to distinguish resource-intensive and frequently used queries collected from database log, and optimize these queries by implementation of MVs. In order to achieve greater efficiency of MVs, they were used not only for the optimization of single queries, but also for entire groups of queries that are similar in syntax and execution results. Thus, the problem stated in this article is the development of approach that will allow forming groups of queries with similar syntax around the most resource-intensive queries in order to identify the list of potential candidates for materialization. For solving this problem, we have applied the algorithm of categorical data clustering to the query grouping problem on the step of database log analysis and searching candidates for materialization. In the current work CLOPE algorithm was modified to cover the introduced problem. Statistical and timing indicators were taken into account in order to form the clusters around the most resource intensive queries. Application of modified algorithm CLOPE allowed to decrease calculable complexity of clustering and to enhance the quality of formed groups.

A Distributed Approach to Continuous Monitoring of Constrained k-Nearest Neighbor Queries in Road Networks

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Hyung-Ju Cho

2012-01-01

Full Text Available Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.

Application of Machine Learning Algorithms for the Query Performance Prediction

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MILICEVIC, M.

2015-08-01

Full Text Available This paper analyzes the relationship between the system load/throughput and the query response time in a real Online transaction processing (OLTP system environment. Although OLTP systems are characterized by short transactions, which normally entail high availability and consistent short response times, the need for operational reporting may jeopardize these objectives. We suggest a new approach to performance prediction for concurrent database workloads, based on the system state vector which consists of 36 attributes. There is no bias to the importance of certain attributes, but the machine learning methods are used to determine which attributes better describe the behavior of the particular database server and how to model that system. During the learning phase, the system's profile is created using multiple reference queries, which are selected to represent frequent business processes. The possibility of the accurate response time prediction may be a foundation for automated decision-making for database (DB query scheduling. Possible applications of the proposed method include adaptive resource allocation, quality of service (QoS management or real-time dynamic query scheduling (e.g. estimation of the optimal moment for a complex query execution.

Collective spatial keyword querying

DEFF Research Database (Denmark)

Cao, Xin; Cong, Gao; Jensen, Christian S.

2011-01-01

With the proliferation of geo-positioning and geo-tagging, spatial web objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However, the quer......With the proliferation of geo-positioning and geo-tagging, spatial web objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However......, the queries studied so far generally focus on finding individual objects that each satisfy a query rather than finding groups of objects where the objects in a group collectively satisfy a query. We define the problem of retrieving a group of spatial web objects such that the group's keywords cover the query......'s keywords and such that objects are nearest to the query location and have the lowest inter-object distances. Specifically, we study two variants of this problem, both of which are NP-complete. We devise exact solutions as well as approximate solutions with provable approximation bounds to the problems. We...

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

Science.gov (United States)

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

Directory of Open Access Journals (Sweden)

Xi Chen

2014-01-01

Full Text Available Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM, essentially different from Western Medicine (WM, is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

Context-rich semantic framework for effective data-to-decisions in coalition networks

Science.gov (United States)

Grueneberg, Keith; de Mel, Geeth; Braines, Dave; Wang, Xiping; Calo, Seraphin; Pham, Tien

2013-05-01

In a coalition context, data fusion involves combining of soft (e.g., field reports, intelligence reports) and hard (e.g., acoustic, imagery) sensory data such that the resulting output is better than what it would have been if the data are taken individually. However, due to the lack of explicit semantics attached with such data, it is difficult to automatically disseminate and put the right contextual data in the hands of the decision makers. In order to understand the data, explicit meaning needs to be added by means of categorizing and/or classifying the data in relationship to each other from base reference sources. In this paper, we present a semantic framework that provides automated mechanisms to expose real-time raw data effectively by presenting appropriate information needed for a given situation so that an informed decision could be made effectively. The system utilizes controlled natural language capabilities provided by the ITA (International Technology Alliance) Controlled English (CE) toolkit to provide a human-friendly semantic representation of messages so that the messages can be directly processed in human/machine hybrid environments. The Real-time Semantic Enrichment (RTSE) service adds relevant contextual information to raw data streams from domain knowledge bases using declarative rules. The rules define how the added semantics and context information are derived and stored in a semantic knowledge base. The software framework exposes contextual information from a variety of hard and soft data sources in a fast, reliable manner so that an informed decision can be made using semantic queries in intelligent software systems.

SAS- Semantic Annotation Service for Geoscience resources on the web

Science.gov (United States)

Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

2015-12-01

There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

DIGITAL WORKFLOWS FOR A 3D SEMANTIC REPRESENTATION OF AN ANCIENT MINING LANDSCAPE

Directory of Open Access Journals (Sweden)

G. Hiebel

2017-08-01

Full Text Available The ancient mining landscape of Schwaz/Brixlegg in the Tyrol, Austria witnessed mining from prehistoric times to modern times creating a first order cultural landscape when it comes to one of the most important inventions in human history: the production of metal. In 1991 a part of this landscape was lost due to an enormous landslide that reshaped part of the mountain. With our work we want to propose a digital workflow to create a 3D semantic representation of this ancient mining landscape with its mining structures to preserve it for posterity. First, we define a conceptual model to integrate the data. It is based on the CIDOC CRM ontology and CRMgeo for geometric data. To transform our information sources to a formal representation of the classes and properties of the ontology we applied semantic web technologies and created a knowledge graph in RDF (Resource Description Framework. Through the CRMgeo extension coordinate information of mining features can be integrated into the RDF graph and thus related to the detailed digital elevation model that may be visualized together with the mining structures using Geoinformation systems or 3D visualization tools. The RDF network of the triple store can be queried using the SPARQL query language. We created a snapshot of mining, settlement and burial sites in the Bronze Age. The results of the query were loaded into a Geoinformation system and a visualization of known bronze age sites related to mining, settlement and burial activities was created.

DISPAQ: Distributed Profitable-Area Query from Big Taxi Trip Data †

Science.gov (United States)

Putri, Fadhilah Kurnia; Song, Giltae; Rao, Praveen

2017-01-01

One of the crucial problems for taxi drivers is to efficiently locate passengers in order to increase profits. The rapid advancement and ubiquitous penetration of Internet of Things (IoT) technology into transportation industries enables us to provide taxi drivers with locations that have more potential passengers (more profitable areas) by analyzing and querying taxi trip data. In this paper, we propose a query processing system, called Distributed Profitable-Area Query (DISPAQ) which efficiently identifies profitable areas by exploiting the Apache Software Foundation’s Spark framework and a MongoDB database. DISPAQ first maintains a profitable-area query index (PQ-index) by extracting area summaries and route summaries from raw taxi trip data. It then identifies candidate profitable areas by searching the PQ-index during query processing. Then, it exploits a Z-Skyline algorithm, which is an extension of skyline processing with a Z-order space filling curve, to quickly refine the candidate profitable areas. To improve the performance of distributed query processing, we also propose local Z-Skyline optimization, which reduces the number of dominant tests by distributing killer profitable areas to each cluster node. Through extensive evaluation with real datasets, we demonstrate that our DISPAQ system provides a scalable and efficient solution for processing profitable-area queries from huge amounts of big taxi trip data. PMID:28946679

Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

Science.gov (United States)

Liu, Dong; Wang, Dandan; Li, Houqiang

2017-12-01

Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

Semantic Document Library: A Virtual Research Environment for Documents, Data and Workflows Sharing

Science.gov (United States)

Kotwani, K.; Liu, Y.; Myers, J.; Futrelle, J.

2008-12-01

The Semantic Document Library (SDL) was driven by use cases from the environmental observatory communities and is designed to provide conventional document repository features of uploading, downloading, editing and versioning of documents as well as value adding features of tagging, querying, sharing, annotating, ranking, provenance, social networking and geo-spatial mapping services. It allows users to organize a catalogue of watershed observation data, model output, workflows, as well publications and documents related to the same watershed study through the tagging capability. Users can tag all relevant materials using the same watershed name and find all of them easily later using this tag. The underpinning semantic content repository can store materials from other cyberenvironments such as workflow or simulation tools and SDL provides an effective interface to query and organize materials from various sources. Advanced features of the SDL allow users to visualize the provenance of the materials such as the source and how the output data is derived. Other novel features include visualizing all geo-referenced materials on a geospatial map. SDL as a component of a cyberenvironment portal (the NCSA Cybercollaboratory) has goal of efficient management of information and relationships between published artifacts (Validated models, vetted data, workflows, annotations, best practices, reviews and papers) produced from raw research artifacts (data, notes, plans etc.) through agents (people, sensors etc.). Tremendous scientific potential of artifacts is achieved through mechanisms of sharing, reuse and collaboration - empowering scientists to spread their knowledge and protocols and to benefit from the knowledge of others. SDL successfully implements web 2.0 technologies and design patterns along with semantic content management approach that enables use of multiple ontologies and dynamic evolution (e.g. folksonomies) of terminology. Scientific documents involved with

jQuery Pocket Reference

CERN Document Server

Flanagan, David

2010-01-01

"As someone who uses jQuery on a regular basis, it was surprising to discover how much of the library I'm not using. This book is indispensable for anyone who is serious about using jQuery for non-trivial applications."-- Raffaele Cecco, longtime developer of video games, including Cybernoid, Exolon, and Stormlord jQuery is the "write less, do more" JavaScript library. Its powerful features and ease of use have made it the most popular client-side JavaScript framework for the Web. This book is jQuery's trusty companion: the definitive "read less, learn more" guide to the library. jQuery P

jQuery UI cookbook

CERN Document Server

Boduch, Adam

2013-01-01

Filled with a practical collection of recipes, jQuery UI Cookbook is full of clear, step-by-step instructions that will help you harness the powerful UI framework in jQuery. Depending on your needs, you can dip in and out of the Cookbook and its recipes, or follow the book from start to finish.If you are a jQuery UI developer looking to improve your existing applications, extract ideas for your new application, or to better understand the overall widget architecture, then jQuery UI Cookbook is a must-have for you. The reader should at least have a rudimentary understanding of what jQuery UI is

Instant jQuery selectors

CERN Document Server

De Rosa, Aurelio

2013-01-01

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Instant jQuery Selectors follows a simple how-to format with recipes aimed at making you well versed with the wide range of selectors that jQuery has to offer through a myriad of examples.Instant jQuery Selectors is for web developers who want to delve into jQuery from its very starting point: selectors. Even if you're already familiar with the framework and its selectors, you could find several tips and tricks that you aren't aware of, especially about performance and how jQuery ac

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.

Dynamic Planar Convex Hull with Optimal Query Time and O(log n · log log n ) Update Time

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Jakob, Riko

2000-01-01

The dynamic maintenance of the convex hull of a set of points in the plane is one of the most important problems in computational geometry. We present a data structure supporting point insertions in amortized O(log n · log log log n) time, point deletions in amortized O(log n · log log n) time......, and various queries about the convex hull in optimal O(log n) worst-case time. The data structure requires O(n) space. Applications of the new dynamic convex hull data structure are improved deterministic algorithms for the k-level problem and the red-blue segment intersection problem where all red and all...

SkyQuery - A Prototype Distributed Query and Cross-Matching Web Service for the Virtual Observatory

Science.gov (United States)

Thakar, A. R.; Budavari, T.; Malik, T.; Szalay, A. S.; Fekete, G.; Nieto-Santisteban, M.; Haridas, V.; Gray, J.

2002-12-01

We have developed a prototype distributed query and cross-matching service for the VO community, called SkyQuery, which is implemented with hierarchichal Web Services. SkyQuery enables astronomers to run combined queries on existing distributed heterogeneous astronomy archives. SkyQuery provides a simple, user-friendly interface to run distributed queries over the federation of registered astronomical archives in the VO. The SkyQuery client connects to the portal Web Service, which farms the query out to the individual archives, which are also Web Services called SkyNodes. The cross-matching algorithm is run recursively on each SkyNode. Each archive is a relational DBMS with a HTM index for fast spatial lookups. The results of the distributed query are returned as an XML DataSet that is automatically rendered by the client. SkyQuery also returns the image cutout corresponding to the query result. SkyQuery finds not only matches between the various catalogs, but also dropouts - objects that exist in some of the catalogs but not in others. This is often as important as finding matches. We demonstrate the utility of SkyQuery with a brown-dwarf search between SDSS and 2MASS, and a search for radio-quiet quasars in SDSS, 2MASS and FIRST. The importance of a service like SkyQuery for the worldwide astronomical community cannot be overstated: data on the same objects in various archives is mapped in different wavelength ranges and looks very different due to different errors, instrument sensitivities and other peculiarities of each archive. Our cross-matching algorithm preforms a fuzzy spatial join across multiple catalogs. This type of cross-matching is currently often done by eye, one object at a time. A static cross-identification table for a set of archives would become obsolete by the time it was built - the exponential growth of astronomical data means that a dynamic cross-identification mechanism like SkyQuery is the only viable option. SkyQuery was funded by a

Sharing and executing linked data queries in a collaborative environment.

Science.gov (United States)

García Godoy, María Jesús; López-Camacho, Esteban; Navas-Delgado, Ismael; Aldana-Montes, José F

2013-07-01

Life Sciences have emerged as a key domain in the Linked Data community because of the diversity of data semantics and formats available through a great variety of databases and web technologies. Thus, it has been used as the perfect domain for applications in the web of data. Unfortunately, bioinformaticians are not exploiting the full potential of this already available technology, and experts in Life Sciences have real problems to discover, understand and devise how to take advantage of these interlinked (integrated) data. In this article, we present Bioqueries, a wiki-based portal that is aimed at community building around biological Linked Data. This tool has been designed to aid bioinformaticians in developing SPARQL queries to access biological databases exposed as Linked Data, and also to help biologists gain a deeper insight into the potential use of this technology. This public space offers several services and a collaborative infrastructure to stimulate the consumption of biological Linked Data and, therefore, contribute to implementing the benefits of the web of data in this domain. Bioqueries currently contains 215 query entries grouped by database and theme, 230 registered users and 44 end points that contain biological Resource Description Framework information. The Bioqueries portal is freely accessible at http://bioqueries.uma.es. Supplementary data are available at Bioinformatics online.

A Semantic Sensor Web for Environmental Decision Support Applications

Directory of Open Access Journals (Sweden)

Raúl García-Castro

2011-09-01

Full Text Available Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

Accelerating SPARQL queries by exploiting hash-based locality and adaptive partitioning

KAUST Repository

Al-Harbi, Razen

2016-02-08

State-of-the-art distributed RDF systems partition data across multiple computer nodes (workers). Some systems perform cheap hash partitioning, which may result in expensive query evaluation. Others try to minimize inter-node communication, which requires an expensive data preprocessing phase, leading to a high startup cost. Apriori knowledge of the query workload has also been used to create partitions, which, however, are static and do not adapt to workload changes. In this paper, we propose AdPart, a distributed RDF system, which addresses the shortcomings of previous work. First, AdPart applies lightweight partitioning on the initial data, which distributes triples by hashing on their subjects; this renders its startup overhead low. At the same time, the locality-aware query optimizer of AdPart takes full advantage of the partitioning to (1) support the fully parallel processing of join patterns on subjects and (2) minimize data communication for general queries by applying hash distribution of intermediate results instead of broadcasting, wherever possible. Second, AdPart monitors the data access patterns and dynamically redistributes and replicates the instances of the most frequent ones among workers. As a result, the communication cost for future queries is drastically reduced or even eliminated. To control replication, AdPart implements an eviction policy for the redistributed patterns. Our experiments with synthetic and real data verify that AdPart: (1) starts faster than all existing systems; (2) processes thousands of queries before other systems become online; and (3) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in subseconds.

Semantic Metadata for Heterogeneous Spatial Planning Documents

Science.gov (United States)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Semantics based approach for analyzing disease-target associations.

Science.gov (United States)

Kaalia, Rama; Ghosh, Indira

2016-08-01

A complex disease is caused by heterogeneous biological interactions between genes and their products along with the influence of environmental factors. There have been many attempts for understanding the cause of these diseases using experimental, statistical and computational methods. In the present work the objective is to address the challenge of representation and integration of information from heterogeneous biomedical aspects of a complex disease using semantics based approach. Semantic web technology is used to design Disease Association Ontology (DAO-db) for representation and integration of disease associated information with diabetes as the case study. The functional associations of disease genes are integrated using RDF graphs of DAO-db. Three semantic web based scoring algorithms (PageRank, HITS (Hyperlink Induced Topic Search) and HITS with semantic weights) are used to score the gene nodes on the basis of their functional interactions in the graph. Disease Association Ontology for Diabetes (DAO-db) provides a standard ontology-driven platform for describing genes, proteins, pathways involved in diabetes and for integrating functional associations from various interaction levels (gene-disease, gene-pathway, gene-function, gene-cellular component and protein-protein interactions). An automatic instance loader module is also developed in present work that helps in adding instances to DAO-db on a large scale. Our ontology provides a framework for querying and analyzing the disease associated information in the form of RDF graphs. The above developed methodology is used to predict novel potential targets involved in diabetes disease from the long list of loose (statistically associated) gene-disease associations. Copyright © 2016 Elsevier Inc. All rights reserved.

Web page sorting algorithm based on query keyword distance relation

Science.gov (United States)

Yang, Han; Cui, Hong Gang; Tang, Hao

2017-08-01

In order to optimize the problem of page sorting, according to the search keywords in the web page in the relationship between the characteristics of the proposed query keywords clustering ideas. And it is converted into the degree of aggregation of the search keywords in the web page. Based on the PageRank algorithm, the clustering degree factor of the query keyword is added to make it possible to participate in the quantitative calculation. This paper proposes an improved algorithm for PageRank based on the distance relation between search keywords. The experimental results show the feasibility and effectiveness of the method.

QCS: a system for querying, clustering and summarizing documents.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M.; Schlesinger, Judith D. (Center for Computing Sciences, Bowie, MD); O' Leary, Dianne P. (University of Maryland, College Park, MD); Conroy, John M. (Center for Computing Sciences, Bowie, MD)

2006-10-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence 'trimming', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of the design

QCS : a system for querying, clustering, and summarizing documents.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M.

2006-08-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence ''trimming'', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of

The BiSciCol Triplifier: bringing biodiversity data to the Semantic Web.

Science.gov (United States)

Stucky, Brian J; Deck, John; Conlin, Tom; Ziemba, Lukasz; Cellinese, Nico; Guralnick, Robert

2014-07-29

Recent years have brought great progress in efforts to digitize the world's biodiversity data, but integrating data from many different providers, and across research domains, remains challenging. Semantic Web technologies have been widely recognized by biodiversity scientists for their potential to help solve this problem, yet these technologies have so far seen little use for biodiversity data. Such slow uptake has been due, in part, to the relative complexity of Semantic Web technologies along with a lack of domain-specific software tools to help non-experts publish their data to the Semantic Web. The BiSciCol Triplifier is new software that greatly simplifies the process of converting biodiversity data in standard, tabular formats, such as Darwin Core-Archives, into Semantic Web-ready Resource Description Framework (RDF) representations. The Triplifier uses a vocabulary based on the popular Darwin Core standard, includes both Web-based and command-line interfaces, and is fully open-source software. Unlike most other RDF conversion tools, the Triplifier does not require detailed familiarity with core Semantic Web technologies, and it is tailored to a widely popular biodiversity data format and vocabulary standard. As a result, the Triplifier can often fully automate the conversion of biodiversity data to RDF, thereby making the Semantic Web much more accessible to biodiversity scientists who might otherwise have relatively little knowledge of Semantic Web technologies. Easy availability of biodiversity data as RDF will allow researchers to combine data from disparate sources and analyze them with powerful linked data querying tools. However, before software like the Triplifier, and Semantic Web technologies in general, can reach their full potential for biodiversity science, the biodiversity informatics community must address several critical challenges, such as the widespread failure to use robust, globally unique identifiers for biodiversity data.

The CMS DBS query language

International Nuclear Information System (INIS)

Kuznetsov, Valentin; Riley, Daniel; Afaq, Anzar; Sekhri, Vijay; Guo Yuyi; Lueking, Lee

2010-01-01

The CMS experiment has implemented a flexible and powerful system enabling users to find data within the CMS physics data catalog. The Dataset Bookkeeping Service (DBS) comprises a database and the services used to store and access metadata related to CMS physics data. To this, we have added a generalized query system in addition to the existing web and programmatic interfaces to the DBS. This query system is based on a query language that hides the complexity of the underlying database structure by discovering the join conditions between database tables. This provides a way of querying the system that is simple and straightforward for CMS data managers and physicists to use without requiring knowledge of the database tables or keys. The DBS Query Language uses the ANTLR tool to build the input query parser and tokenizer, followed by a query builder that uses a graph representation of the DBS schema to construct the SQL query sent to underlying database. We will describe the design of the query system, provide details of the language components and overview of how this component fits into the overall data discovery system architecture.

Knowledge, Skills and Competence Modelling in Nuclear Engineering Domain using Singular Value Decomposition (SVD) and Latent Semantic Analysis (LSA)

International Nuclear Information System (INIS)

Kuo, V.

2016-01-01

Full text: The European Qualifications Framework categorizes learning objectives into three qualifiers “knowledge”, “skills”, and “competences” (KSCs) to help improve the comparability between different fields and disciplines. However, the management of KSCs remains a great challenge given their semantic fuzziness. Similar texts may describe different concepts and different texts may describe similar concepts among different domains. This is difficult for the indexing, searching and matching of semantically similar KSCs within an information system, to facilitate transfer and mobility of KSCs. We present a working example using a semantic inference method known as Latent Semantic Analysis, employing a matrix operation called Singular Value Decomposition, which have been shown to infer semantic associations within unstructured textual data comparable to that of human interpretations. In our example, a few natural language text passages representing KSCs in the nuclear sector are used to demonstrate the capabilities of the system. It can be shown that LSA is able to infer latent semantic associations between texts, and cluster and match separate text passages semantically based on these associations. We propose this methodology for modelling existing natural language KSCs in the nuclear domain so they can be semantically queried, retrieved and filtered upon request. (author

Mastering jQuery mobile

CERN Document Server

Lambert, Chip

2015-01-01

You've started down the path of jQuery Mobile, now begin mastering some of jQuery Mobile's higher level topics. Go beyond jQuery Mobile's documentation and master one of the hottest mobile technologies out there. Previous JavaScript and PHP experience can help you get the most out of this book.

CUFID-query: accurate network querying through random walk based network flow estimation.

Science.gov (United States)

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive

Efficient Storage and Querying of Horizontal Tables Using a PIVOT Operation in Commercial Relational DBMSs

Science.gov (United States)

Shin, Sung-Hyun; Moon, Yang-Sae; Kim, Jinho; Kim, Sang-Wook

In recent years, a horizontal table with a large number of attributes is widely used in OLAP or e-business applications to analyze multidimensional data efficiently. For efficient storing and querying of horizontal tables, recent works have tried to transform a horizontal table to a traditional vertical table. Existing works, however, have the drawback of not considering an optimized PIVOT operation provided (or to be provided) in recent commercial RDBMSs. In this paper we propose a formal approach that exploits the optimized PIVOT operation of commercial RDBMSs for storing and querying of horizontal tables. To achieve this goal, we first provide an overall framework that stores and queries a horizontal table using an equivalent vertical table. Under the proposed framework, we then formally define 1) a method that stores a horizontal table in an equivalent vertical table and 2) a PIVOT operation that converts a stored vertical table to an equivalent horizontal view. Next, we propose a novel method that transforms a user-specified query on horizontal tables to an equivalent PIVOT-included query on vertical tables. In particular, by providing transformation rules for all five elementary operations in relational algebra as theorems, we prove our method is theoretically applicable to commercial RDBMSs. Experimental results show that, compared with the earlier work, our method reduces storage space significantly and also improves average performance by several orders of magnitude. These results indicate that our method provides an excellent framework to maximize performance in handling horizontal tables by exploiting the optimized PIVOT operation in commercial RDBMSs.

jQuery cookbook

CERN Document Server

2010-01-01

jQuery simplifies building rich, interactive web frontends. Getting started with this JavaScript library is easy, but it can take years to fully realize its breadth and depth; this cookbook shortens the learning curve considerably. With these recipes, you'll learn patterns and practices from 19 leading developers who use jQuery for everything from integrating simple components into websites and applications to developing complex, high-performance user interfaces. Ideal for newcomers and JavaScript veterans alike, jQuery Cookbook starts with the basics and then moves to practical use cases w

User perspectives on query difficulty

DEFF Research Database (Denmark)

Lioma, Christina; Larsen, Birger; Schütze, Hinrich

2011-01-01

be difficult for the system to address? (2) Are users aware of specific features in their query (e.g., domain-specificity, vagueness) that may render their query difficult for an IR system to address? A study of 420 queries from a Web search engine query log that are pre-categorised as easy, medium, hard...

Mastering jQuery

CERN Document Server

Libby, Alex

2015-01-01

If you are a developer who is already familiar with using jQuery and wants to push your skill set further, then this book is for you. The book assumes an intermediate knowledge level of jQuery, JavaScript, HTML5, and CSS.

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.

Overtaking CPU DBMSes with a GPU in whole-query analytic processing with parallelism-friendly execution plan optimization

NARCIS (Netherlands)

A. Agbaria (Adnan); D. Minor (David); N. Peterfreund (Natan); E. Rozenberg (Eyal); O. Rosenberg (Ofer); Huawei Research

2016-01-01

textabstractExisting work on accelerating analytic DB query processing with (discrete) GPUs fails to fully realize their potential for speedup through parallelism: Published results do not achieve significant speedup over more performant CPU-only DBMSes when processing complete queries. This

SEMANTIC INDEXING OF TERRASAR-X AND IN SITU DATA FOR URBAN ANALYTICS

OpenAIRE

Espinoza Molina, D.; Alonso, K.; Datcu, M.

2015-01-01

This paper presents the semantic indexing of TerraSAR-X images and in situ data. Image processing together with machine learning methods, relevance feedback techniques, and human expertise are used to annotate the image content into a land use land cover catalogue. All the generated information is stored into a geo-database supporting the link between different types of information and the computation of queries and analytics. We used 11 TerraSAR-X scenes over Germany and LUCAS as in situ dat...

jQuery For Dummies

CERN Document Server

Beighley, Lynn

2010-01-01

Learn how jQuery can make your Web page or blog stand out from the crowd!. jQuery is free, open source software that allows you to extend and customize Joomla!, Drupal, AJAX, and WordPress via plug-ins. Assuming no previous programming experience, Lynn Beighley takes you through the basics of jQuery from the very start. You'll discover how the jQuery library separates itself from other JavaScript libraries through its ease of use, compactness, and friendliness if you're a beginner programmer. Written in the easy-to-understand style of the For Dummies brand, this book demonstrates how you can a

Web development with jQuery

CERN Document Server

York, Richard

2015-01-01

Newly revised and updated resource on jQuery's many features and advantages Web Development with jQuery offers a major update to the popular Beginning JavaScript and CSS Development with jQuery from 2009. More than half of the content is new or updated, and reflects recent innovations with regard to mobile applications, jQuery mobile, and the spectrum of associated plugins. Readers can expect thorough revisions with expanded coverage of events, CSS, AJAX, animation, and drag and drop. New chapters bring developers up to date on popular features like jQuery UI, navigation, tables, interacti

A Novel Two-Tier Cooperative Caching Mechanism for the Optimization of Multi-Attribute Periodic Queries in Wireless Sensor Networks

Science.gov (United States)

Zhou, ZhangBing; Zhao, Deng; Shu, Lei; Tsang, Kim-Fung

2015-01-01

Wireless sensor networks, serving as an important interface between physical environments and computational systems, have been used extensively for supporting domain applications, where multiple-attribute sensory data are queried from the network continuously and periodically. Usually, certain sensory data may not vary significantly within a certain time duration for certain applications. In this setting, sensory data gathered at a certain time slot can be used for answering concurrent queries and may be reused for answering the forthcoming queries when the variation of these data is within a certain threshold. To address this challenge, a popularity-based cooperative caching mechanism is proposed in this article, where the popularity of sensory data is calculated according to the queries issued in recent time slots. This popularity reflects the possibility that sensory data are interested in the forthcoming queries. Generally, sensory data with the highest popularity are cached at the sink node, while sensory data that may not be interested in the forthcoming queries are cached in the head nodes of divided grid cells. Leveraging these cooperatively cached sensory data, queries are answered through composing these two-tier cached data. Experimental evaluation shows that this approach can reduce the network communication cost significantly and increase the network capability. PMID:26131665

SEMANTIC METADATA FOR HETEROGENEOUS SPATIAL PLANNING DOCUMENTS

Directory of Open Access Journals (Sweden)

A. Iwaniak

2016-09-01

Full Text Available Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa. The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Age-related vulnerability in the neural systems supporting semantic processing

Directory of Open Access Journals (Sweden)

Jonathan E Peelle

2013-09-01

Full Text Available Our ability to form abstract representations of objects in semantic memory is crucial to language and thought. The utility of this information relies both on the representations of sensory-motor feature knowledge stored in long-term memory and the executive processes required to retrieve, manipulate, and evaluate this semantic knowledge in a task-relevant manner. These complementary components of semantic memory can be differentially impacted by aging. We investigated semantic processing in normal aging using functional magnetic resonance imaging (fMRI. Young and older adults were asked to judge whether two printed object names match on a particular feature (for example, whether a tomato and strawberry have the same color. The task thus required both retrieval of relevant visual feature knowledge of object concepts and evaluating this information. Objects were drawn from either natural kinds or manufactured objects, and were queried on either color or shape in a factorial design. Behaviorally, all subjects performed well, but older adults could be divided into those whose performance matched that of young adults (better performers and those whose performance was worse (poorer performers. All subjects activated several cortical regions while performing this task, including bilateral inferior and lateral temporal cortex and left frontal and prefrontal cortex. Better performing older adults showed increased overall activity in bilateral premotor cortex and left lateral occipital cortex compared to young adults, and increased activity in these brain regions relative to poorer performing older adults who also showed gray matter atrophy in premotor cortex. These findings highlight the contribution of domain-general executive processing brain regions to semantic memory, and illustrate differences in how these regions are recruited in healthy older adults.

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...

Semantic Labeling of Nonspeech Audio Clips

Directory of Open Access Journals (Sweden)

Xiaojuan Ma

2010-01-01

Full Text Available Human communication about entities and events is primarily linguistic in nature. While visual representations of information are shown to be highly effective as well, relatively little is known about the communicative power of auditory nonlinguistic representations. We created a collection of short nonlinguistic auditory clips encoding familiar human activities, objects, animals, natural phenomena, machinery, and social scenes. We presented these sounds to a broad spectrum of anonymous human workers using Amazon Mechanical Turk and collected verbal sound labels. We analyzed the human labels in terms of their lexical and semantic properties to ascertain that the audio clips do evoke the information suggested by their pre-defined captions. We then measured the agreement with the semantically compatible labels for each sound clip. Finally, we examined which kinds of entities and events, when captured by nonlinguistic acoustic clips, appear to be well-suited to elicit information for communication, and which ones are less discriminable. Our work is set against the broader goal of creating resources that facilitate communication for people with some types of language loss. Furthermore, our data should prove useful for future research in machine analysis/synthesis of audio, such as computational auditory scene analysis, and annotating/querying large collections of sound effects.

Efficient Semantics-Based Compliance Checking Using LTL Formulae and Unfolding

Directory of Open Access Journals (Sweden)

Liang Song

2013-01-01

Full Text Available Business process models are required to be in line with frequently changing regulations, policies, and environments. In the field of intelligent modeling, organisations concern automated business process compliance checking as the manual verification is a time-consuming and inefficient work. There exist two key issues for business process compliance checking. One is the definition of a business process retrieval language that can be employed to capture the compliance rules, the other concerns efficient evaluation of these rules. Traditional syntax-based retrieval approaches cannot deal with various important requirements of compliance checking in practice. Although a retrieval language that is based on semantics can overcome the drawback of syntax-based ones, it suffers from the well-known state space explosion. In this paper, we define a semantics-based process model query language through simplifying a property specification pattern system without affecting its expressiveness. We use this language to capture semantics-based compliance rules and constraints. We also propose a feasible approach in such a way that the compliance checking will not suffer from the state space explosion as much as possible. A tool is implemented to evaluate the efficiency. An experiment conducted on three model collections illustrates that our technology is very efficient.

Biomedical semantics in the Semantic Web.

Science.gov (United States)

Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

2011-03-07

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

Science.gov (United States)

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Preserved musical semantic memory in semantic dementia.

Science.gov (United States)

Weinstein, Jessica; Koenig, Phyllis; Gunawardena, Delani; McMillan, Corey; Bonner, Michael; Grossman, Murray

2011-02-01

To understand the scope of semantic impairment in semantic dementia. Case study. Academic medical center. A man with semantic dementia, as demonstrated by clinical, neuropsychological, and imaging studies. Music performance and magnetic resonance imaging results. Despite profoundly impaired semantic memory for words and objects due to left temporal lobe atrophy, this semiprofessional musician was creative and expressive in demonstrating preserved musical knowledge. Long-term representations of words and objects in semantic memory may be dissociated from meaningful knowledge in other domains, such as music.

Semantic orchestration of image processing services for environmental analysis

Science.gov (United States)

Ranisavljević, Élisabeth; Devin, Florent; Laffly, Dominique; Le Nir, Yannick

2013-09-01

In order to analyze environmental dynamics, a major process is the classification of the different phenomena of the site (e.g. ice and snow for a glacier). When using in situ pictures, this classification requires data pre-processing. Not all the pictures need the same sequence of processes depending on the disturbances. Until now, these sequences have been done manually, which restricts the processing of large amount of data. In this paper, we present how to realize a semantic orchestration to automate the sequencing for the analysis. It combines two advantages: solving the problem of the amount of processing, and diversifying the possibilities in the data processing. We define a BPEL description to express the sequences. This BPEL uses some web services to run the data processing. Each web service is semantically annotated using an ontology of image processing. The dynamic modification of the BPEL is done using SPARQL queries on these annotated web services. The results obtained by a prototype implementing this method validate the construction of the different workflows that can be applied to a large number of pictures.

Semantically optiMize the dAta seRvice operaTion (SMART) system for better data discovery and access

Science.gov (United States)

Yang, C.; Huang, T.; Armstrong, E. M.; Moroni, D. F.; Liu, K.; Gui, Z.

2013-12-01

Abstract: We present a Semantically optiMize the dAta seRvice operaTion (SMART) system for better data discovery and access across the NASA data systems, Global Earth Observation System of Systems (GEOSS) Clearinghouse and Data.gov to facilitate scientists to select Earth observation data that fit better their needs in four aspects: 1. Integrating and interfacing the SMART system to include the functionality of a) semantic reasoning based on Jena, an open source semantic reasoning engine, b) semantic similarity calculation, c) recommendation based on spatiotemporal, semantic, and user workflow patterns, and d) ranking results based on similarity between search terms and data ontology. 2. Collaborating with data user communities to a) capture science data ontology and record relevant ontology triple stores, b) analyze and mine user search and download patterns, c) integrate SMART into metadata-centric discovery system for community-wide usage and feedback, and d) customizing data discovery, search and access user interface to include the ranked results, recommendation components, and semantic based navigations. 3. Laying the groundwork to interface the SMART system with other data search and discovery systems as an open source data search and discovery solution. The SMART systems leverages NASA, GEO, FGDC data discovery, search and access for the Earth science community by enabling scientists to readily discover and access data appropriate to their endeavors, increasing the efficiency of data exploration and decreasing the time that scientists must spend on searching, downloading, and processing the datasets most applicable to their research. By incorporating the SMART system, it is a likely aim that the time being devoted to discovering the most applicable dataset will be substantially reduced, thereby reducing the number of user inquiries and likewise reducing the time and resources expended by a data center in addressing user inquiries. Keywords: EarthCube; ECHO

Range-clustering queries

NARCIS (Netherlands)

Abrahamsen, M.; de Berg, M.T.; Buchin, K.A.; Mehr, M.; Mehrabi, A.D.

2017-01-01

In a geometric k -clustering problem the goal is to partition a set of points in R d into k subsets such that a certain cost function of the clustering is minimized. We present data structures for orthogonal range-clustering queries on a point set S : given a query box Q and an integer k>2 , compute

Semantic mashups intelligent reuse of web resources

CERN Document Server

Endres-Niggemeyer, Brigitte

2013-01-01

Mashups are mostly lightweight Web applications that offer new functionalities by combining, aggregating and transforming resources and services available on the Web. Popular examples include a map in their main offer, for instance for real estate, hotel recommendations, or navigation tools.  Mashups may contain and mix client-side and server-side activity. Obviously, understanding the incoming resources (services, statistical figures, text, videos, etc.) is a precondition for optimally combining them, so that there is always some undercover semantics being used.  By using semantic annotations

A Ubiquitous Sensor Network Platform for Integrating Smart Devices into the Semantic Sensor Web

Science.gov (United States)

de Vera, David Díaz Pardo; Izquierdo, Álvaro Sigüenza; Vercher, Jesús Bernat; Gómez, Luis Alfonso Hernández

2014-01-01

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs. PMID:24945678

Optimizing Semantic Pointer Representations for Symbol-Like Processing in Spiking Neural Networks.

Science.gov (United States)

Gosmann, Jan; Eliasmith, Chris

2016-01-01

The Semantic Pointer Architecture (SPA) is a proposal of specifying the computations and architectural elements needed to account for cognitive functions. By means of the Neural Engineering Framework (NEF) this proposal can be realized in a spiking neural network. However, in any such network each SPA transformation will accumulate noise. By increasing the accuracy of common SPA operations, the overall network performance can be increased considerably. As well, the representations in such networks present a trade-off between being able to represent all possible values and being only able to represent the most likely values, but with high accuracy. We derive a heuristic to find the near-optimal point in this trade-off. This allows us to improve the accuracy of common SPA operations by up to 25 times. Ultimately, it allows for a reduction of neuron number and a more efficient use of both traditional and neuromorphic hardware, which we demonstrate here.

Integrating user profile in medical CBIR systems to answer perceptual similarity queries

Science.gov (United States)

Bugatti, Pedro H.; Kaster, Daniel S.; Ponciano-Silva, Marcelo; Traina, Agma J. M.; Traina, Caetano, Jr.

2011-03-01

Techniques for Content-Based Image Retrieval (CBIR) have been intensively explored due to the increase in the amount of captured images and the need of fast retrieval of them. The medical field is a specific example that generates a large flow of information, especially digital images employed for diagnosing. One issue that still remains unsolved deals with how to reach the perceptual similarity. That is, to achieve an effective retrieval, one must characterize and quantify the perceptual similarity regarding the specialist in the field. Therefore, the present paper was conceived to fill in this gap creating a consistent support to perform similarity queries over medical images, maintaining the semantics of a given query desired by the user. CBIR systems relying in relevance feedback techniques usually request the users to label relevant images. In this paper, we present a simple but highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The user profiles maintain the settings desired for each user, allowing tuning the similarity assessment, which encompasses dynamically changing the distance function employed through an interactive process. Experiments using computed tomography lung images show that the proposed approach is effective in capturing the users' perception.

BioSWR--semantic web services registry for bioinformatics.

Directory of Open Access Journals (Sweden)

Dmitry Repchevsky

Full Text Available Despite of the variety of available Web services registries specially aimed at Life Sciences, their scope is usually restricted to a limited set of well-defined types of services. While dedicated registries are generally tied to a particular format, general-purpose ones are more adherent to standards and usually rely on Web Service Definition Language (WSDL. Although WSDL is quite flexible to support common Web services types, its lack of semantic expressiveness led to various initiatives to describe Web services via ontology languages. Nevertheless, WSDL 2.0 descriptions gained a standard representation based on Web Ontology Language (OWL. BioSWR is a novel Web services registry that provides standard Resource Description Framework (RDF based Web services descriptions along with the traditional WSDL based ones. The registry provides Web-based interface for Web services registration, querying and annotation, and is also accessible programmatically via Representational State Transfer (REST API or using a SPARQL Protocol and RDF Query Language. BioSWR server is located at http://inb.bsc.es/BioSWR/and its code is available at https://sourceforge.net/projects/bioswr/under the LGPL license.

BioSWR--semantic web services registry for bioinformatics.

Science.gov (United States)

Repchevsky, Dmitry; Gelpi, Josep Ll

2014-01-01

Despite of the variety of available Web services registries specially aimed at Life Sciences, their scope is usually restricted to a limited set of well-defined types of services. While dedicated registries are generally tied to a particular format, general-purpose ones are more adherent to standards and usually rely on Web Service Definition Language (WSDL). Although WSDL is quite flexible to support common Web services types, its lack of semantic expressiveness led to various initiatives to describe Web services via ontology languages. Nevertheless, WSDL 2.0 descriptions gained a standard representation based on Web Ontology Language (OWL). BioSWR is a novel Web services registry that provides standard Resource Description Framework (RDF) based Web services descriptions along with the traditional WSDL based ones. The registry provides Web-based interface for Web services registration, querying and annotation, and is also accessible programmatically via Representational State Transfer (REST) API or using a SPARQL Protocol and RDF Query Language. BioSWR server is located at http://inb.bsc.es/BioSWR/and its code is available at https://sourceforge.net/projects/bioswr/under the LGPL license.

A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

Science.gov (United States)

Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

2012-11-01

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

Lost in translation? A multilingual Query Builder improves the quality of PubMed queries: a randomised controlled trial.

Science.gov (United States)

Schuers, Matthieu; Joulakian, Mher; Kerdelhué, Gaetan; Segas, Léa; Grosjean, Julien; Darmoni, Stéfan J; Griffon, Nicolas

2017-07-03

MEDLINE is the most widely used medical bibliographic database in the world. Most of its citations are in English and this can be an obstacle for some researchers to access the information the database contains. We created a multilingual query builder to facilitate access to the PubMed subset using a language other than English. The aim of our study was to assess the impact of this multilingual query builder on the quality of PubMed queries for non-native English speaking physicians and medical researchers. A randomised controlled study was conducted among French speaking general practice residents. We designed a multi-lingual query builder to facilitate information retrieval, based on available MeSH translations and providing users with both an interface and a controlled vocabulary in their own language. Participating residents were randomly allocated either the French or the English version of the query builder. They were asked to translate 12 short medical questions into MeSH queries. The main outcome was the quality of the query. Two librarians blind to the arm independently evaluated each query, using a modified published classification that differentiated eight types of errors. Twenty residents used the French version of the query builder and 22 used the English version. 492 queries were analysed. There were significantly more perfect queries in the French group vs. the English group (respectively 37.9% vs. 17.9%; p PubMed queries in particular for researchers whose first language is not English.

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...

Multi-Dimensional Path Queries

DEFF Research Database (Denmark)

Bækgaard, Lars

1998-01-01

to create nested path structures. We present an SQL-like query language that is based on path expressions and we show how to use it to express multi-dimensional path queries that are suited for advanced data analysis in decision support environments like data warehousing environments......We present the path-relationship model that supports multi-dimensional data modeling and querying. A path-relationship database is composed of sets of paths and sets of relationships. A path is a sequence of related elements (atoms, paths, and sets of paths). A relationship is a binary path...

Learning via Query Synthesis

KAUST Repository

Alabdulmohsin, Ibrahim

2017-01-01

Active learning is a subfield of machine learning that has been successfully used in many applications. One of the main branches of active learning is query synthe- sis, where the learning agent constructs artificial queries from scratch in order

StreamQRE: Modular Specification and Efficient Evaluation of Quantitative Queries over Streaming Data.

Science.gov (United States)

Mamouras, Konstantinos; Raghothaman, Mukund; Alur, Rajeev; Ives, Zachary G; Khanna, Sanjeev

2017-06-01

Real-time decision making in emerging IoT applications typically relies on computing quantitative summaries of large data streams in an efficient and incremental manner. To simplify the task of programming the desired logic, we propose StreamQRE, which provides natural and high-level constructs for processing streaming data. Our language has a novel integration of linguistic constructs from two distinct programming paradigms: streaming extensions of relational query languages and quantitative extensions of regular expressions. The former allows the programmer to employ relational constructs to partition the input data by keys and to integrate data streams from different sources, while the latter can be used to exploit the logical hierarchy in the input stream for modular specifications. We first present the core language with a small set of combinators, formal semantics, and a decidable type system. We then show how to express a number of common patterns with illustrative examples. Our compilation algorithm translates the high-level query into a streaming algorithm with precise complexity bounds on per-item processing time and total memory footprint. We also show how to integrate approximation algorithms into our framework. We report on an implementation in Java, and evaluate it with respect to existing high-performance engines for processing streaming data. Our experimental evaluation shows that (1) StreamQRE allows more natural and succinct specification of queries compared to existing frameworks, (2) the throughput of our implementation is higher than comparable systems (for example, two-to-four times greater than RxJava), and (3) the approximation algorithms supported by our implementation can lead to substantial memory savings.

Translating standards into practice - one Semantic Web API for Gene Expression.

Science.gov (United States)

Deus, Helena F; Prud'hommeaux, Eric; Miller, Michael; Zhao, Jun; Malone, James; Adamusiak, Tomasz; McCusker, Jim; Das, Sudeshna; Rocca Serra, Philippe; Fox, Ronan; Marshall, M Scott

2012-08-01

Sharing and describing experimental results unambiguously with sufficient detail to enable replication of results is a fundamental tenet of scientific research. In today's cluttered world of "-omics" sciences, data standards and standardized use of terminologies and ontologies for biomedical informatics play an important role in reporting high-throughput experiment results in formats that can be interpreted by both researchers and analytical tools. Increasing adoption of Semantic Web and Linked Data technologies for the integration of heterogeneous and distributed health care and life sciences (HCLSs) datasets has made the reuse of standards even more pressing; dynamic semantic query federation can be used for integrative bioinformatics when ontologies and identifiers are reused across data instances. We present here a methodology to integrate the results and experimental context of three different representations of microarray-based transcriptomic experiments: the Gene Expression Atlas, the W3C BioRDF task force approach to reporting Provenance of Microarray Experiments, and the HSCI blood genomics project. Our approach does not attempt to improve the expressivity of existing standards for genomics but, instead, to enable integration of existing datasets published from microarray-based transcriptomic experiments. SPARQL Construct is used to create a posteriori mappings of concepts and properties and linking rules that match entities based on query constraints. We discuss how our integrative approach can encourage reuse of the Experimental Factor Ontology (EFO) and the Ontology for Biomedical Investigations (OBIs) for the reporting of experimental context and results of gene expression studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Truth Space Method for Caching Database Queries

Directory of Open Access Journals (Sweden)

S. V. Mosin

2015-01-01

Full Text Available We propose a new method of client-side data caching for relational databases with a central server and distant clients. Data are loaded into the client cache based on queries executed on the server. Every query has the corresponding DB table – the result of the query execution. These queries have a special form called "universal relational query" based on three fundamental Relational Algebra operations: selection, projection and natural join. We have to mention that such a form is the closest one to the natural language and the majority of database search queries can be expressed in this way. Besides, this form allows us to analyze query correctness by checking lossless join property. A subsequent query may be executed in a client’s local cache if we can determine that the query result is entirely contained in the cache. For this we compare truth spaces of the logical restrictions in a new user’s query and the results of the queries execution in the cache. Such a comparison can be performed analytically , without need in additional Database queries. This method may be used to define lacking data in the cache and execute the query on the server only for these data. To do this the analytical approach is also used, what distinguishes our paper from the existing technologies. We propose four theorems for testing the required conditions. The first and the third theorems conditions allow us to define the existence of required data in cache. The second and the fourth theorems state conditions to execute queries with cache only. The problem of cache data actualizations is not discussed in this paper. However, it can be solved by cataloging queries on the server and their serving by triggers in background mode. The article is published in the author’s wording.

Searching for rare diseases in PubMed: a blind comparison of Orphanet expert query and query based on terminological knowledge.

Science.gov (United States)

Griffon, N; Schuers, M; Dhombres, F; Merabti, T; Kerdelhué, G; Rollin, L; Darmoni, S J

2016-08-02

Despite international initiatives like Orphanet, it remains difficult to find up-to-date information about rare diseases. The aim of this study is to propose an exhaustive set of queries for PubMed based on terminological knowledge and to evaluate it versus the queries based on expertise provided by the most frequently used resource in Europe: Orphanet. Four rare disease terminologies (MeSH, OMIM, HPO and HRDO) were manually mapped to each other permitting the automatic creation of expended terminological queries for rare diseases. For 30 rare diseases, 30 citations retrieved by Orphanet expert query and/or query based on terminological knowledge were assessed for relevance by two independent reviewers unaware of the query's origin. An adjudication procedure was used to resolve any discrepancy. Precision, relative recall and F-measure were all computed. For each Orphanet rare disease (n = 8982), there was a corresponding terminological query, in contrast with only 2284 queries provided by Orphanet. Only 553 citations were evaluated due to queries with 0 or only a few hits. There were no significant differences between the Orpha query and terminological query in terms of precision, respectively 0.61 vs 0.52 (p = 0.13). Nevertheless, terminological queries retrieved more citations more often than Orpha queries (0.57 vs. 0.33; p = 0.01). Interestingly, Orpha queries seemed to retrieve older citations than terminological queries (p < 0.0001). The terminological queries proposed in this study are now currently available for all rare diseases. They may be a useful tool for both precision or recall oriented literature search.

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.

Pro PHP and jQuery

CERN Document Server

Lengstorf, Jason

2010-01-01

This book is for intermediate programmers interested in building AJAX web applications using jQuery and PHP. Along with teaching some advanced PHP techniques, it will teach you how to take your dynamic applications to the next level by adding a JavaScript layer with jQuery. * Learn to utilize built-in PHP functions to build calendar tools.* Learn how jQuery can be used for AJAX, animation, client-side validation, and more.What you'll learn* Use PHP to build a calendar application that allows users to post, view, edit, and delete events.* Use jQuery to allow the calendar app to be viewed and ed

Query recommendation for children

NARCIS (Netherlands)

Duarte Torres, Sergio; Hiemstra, Djoerd; Weber, Ingmar; Serdyukov, Pavel

2012-01-01

One of the biggest problems that children experience while searching the web occurs during the query formulation process. Children have been found to struggle formulating queries based on keywords given their limited vocabulary and their difficulty to choose the right keywords. In this work we

Semantic Web-based Vocabulary Broker for Open Science

Science.gov (United States)

Ritschel, B.; Neher, G.; Iyemori, T.; Murayama, Y.; Kondo, Y.; Koyama, Y.; King, T. A.; Galkin, I. A.; Fung, S. F.; Wharton, S.; Cecconi, B.

2016-12-01

Communications Technology Tokyo7 Open Semantic Framework8 Space Physics Archive Search and Extract9 Simple Knowledge Organization System10 Linked Open Data11 SPARQL Protocol And RDF Query12 Resource Description Framework13 Database to RDF Query14 Inter-university Upper atmosphere Global Observation NETwork15 World Data System

Lower Bounds for Sorted Geometric Queries in the I/O Model

DEFF Research Database (Denmark)

Afshani, Peyman; Zeh, Norbert

2012-01-01

. This is highly relevant in an I/O context because storing a massive data set in a superlinear-space data structure is often infeasible. We also prove that answering queries using I/Os requires space, where N is the input size, B is the block size, and M is the size of the main memory. This bound is unlikely...... to be optimal and in fact we can show that, for a particular class of “persistence-based” data structures, the space lower bound can be improved to Ω(N2 / MO(1)). Both these lower bounds are a first step towards understanding the complexity of sorted geometric query problems. All our lower bounds assume...

Automation and integration of components for generalized semantic markup of electronic medical texts.

Science.gov (United States)

Dugan, J M; Berrios, D C; Liu, X; Kim, D K; Kaizer, H; Fagan, L M

1999-01-01

Our group has built an information retrieval system based on a complex semantic markup of medical textbooks. We describe the construction of a set of web-based knowledge-acquisition tools that expedites the collection and maintenance of the concepts required for text markup and the search interface required for information retrieval from the marked text. In the text markup system, domain experts (DEs) identify sections of text that contain one or more elements from a finite set of concepts. End users can then query the text using a predefined set of questions, each of which identifies a subset of complementary concepts. The search process matches that subset of concepts to relevant points in the text. The current process requires that the DE invest significant time to generate the required concepts and questions. We propose a new system--called ACQUIRE (Acquisition of Concepts and Queries in an Integrated Retrieval Environment)--that assists a DE in two essential tasks in the text-markup process. First, it helps her to develop, edit, and maintain the concept model: the set of concepts with which she marks the text. Second, ACQUIRE helps her to develop a query model: the set of specific questions that end users can later use to search the marked text. The DE incorporates concepts from the concept model when she creates the questions in the query model. The major benefit of the ACQUIRE system is a reduction in the time and effort required for the text-markup process. We compared the process of concept- and query-model creation using ACQUIRE to the process used in previous work by rebuilding two existing models that we previously constructed manually. We observed a significant decrease in the time required to build and maintain the concept and query models.

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

Directory of Open Access Journals (Sweden)

Ryu Miura

2013-06-01

Full Text Available An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner.

jQuery Tools UI Library

CERN Document Server

Libby, Alex

2012-01-01

A practical tutorial with powerful yet simple projects that are quick to implement. This book is aimed at developers who have prior jQuery knowledge, but may not have any prior experience with jQuery Tools. It is possible that they may have started with the basics of jQuery Tools, but want to learn more about how it can be used, as well as get ideas for future projects.

Joint Top-K Spatial Keyword Query Processing

DEFF Research Database (Denmark)

Wu, Dingming; Yiu, Man Lung; Cong, Gao

2012-01-01

Web users and content are increasingly being geopositioned, and increased focus is being given to serving local content in response to web queries. This development calls for spatial keyword queries that take into account both the locations and textual descriptions of content. We study the effici......Web users and content are increasingly being geopositioned, and increased focus is being given to serving local content in response to web queries. This development calls for spatial keyword queries that take into account both the locations and textual descriptions of content. We study...... the efficient, joint processing of multiple top-k spatial keyword queries. Such joint processing is attractive during high query loads and also occurs when multiple queries are used to obfuscate a user's true query. We propose a novel algorithm and index structure for the joint processing of top-k spatial...... keyword queries. Empirical studies show that the proposed solution is efficient on real data sets. We also offer analytical studies on synthetic data sets to demonstrate the efficiency of the proposed solution. Index Terms IEEE Terms Electronic mail , Google , Indexes , Joints , Mobile communication...

BioSWR – Semantic Web Services Registry for Bioinformatics

Science.gov (United States)

Repchevsky, Dmitry; Gelpi, Josep Ll.

2014-01-01

Despite of the variety of available Web services registries specially aimed at Life Sciences, their scope is usually restricted to a limited set of well-defined types of services. While dedicated registries are generally tied to a particular format, general-purpose ones are more adherent to standards and usually rely on Web Service Definition Language (WSDL). Although WSDL is quite flexible to support common Web services types, its lack of semantic expressiveness led to various initiatives to describe Web services via ontology languages. Nevertheless, WSDL 2.0 descriptions gained a standard representation based on Web Ontology Language (OWL). BioSWR is a novel Web services registry that provides standard Resource Description Framework (RDF) based Web services descriptions along with the traditional WSDL based ones. The registry provides Web-based interface for Web services registration, querying and annotation, and is also accessible programmatically via Representational State Transfer (REST) API or using a SPARQL Protocol and RDF Query Language. BioSWR server is located at http://inb.bsc.es/BioSWR/and its code is available at https://sourceforge.net/projects/bioswr/under the LGPL license. PMID:25233118

Research Issues in Mobile Querying

DEFF Research Database (Denmark)

Breunig, M.; Jensen, Christian Søndergaard; Klein, M.

2004-01-01

This document reports on key aspects of the discussions conducted within the working group. In particular, the document aims to offer a structured and somewhat digested summary of the group's discussions. The document first offers concepts that enable characterization of "mobile queries" as well...... as the types of systems that enable such queries. It explores the notion of context in mobile queries. The document ends with a few observations, mainly regarding challenges....

Semantic content-based recommendations using semantic graphs.

Science.gov (United States)

Guo, Weisen; Kraines, Steven B

2010-01-01

Recommender systems (RSs) can be useful for suggesting items that might be of interest to specific users. Most existing content-based recommendation (CBR) systems are designed to recommend items based on text content, and the items in these systems are usually described with keywords. However, similarity evaluations based on keywords suffer from the ambiguity of natural languages. We present a semantic CBR method that uses Semantic Web technologies to recommend items that are more similar semantically with the items that the user prefers. We use semantic graphs to represent the items and we calculate the similarity scores for each pair of semantic graphs using an inverse graph frequency algorithm. The items having higher similarity scores to the items that are known to be preferred by the user are recommended.

On tractable query evaluation for SPARQL

OpenAIRE

Mengel, Stefan; Skritek, Sebastian

2017-01-01

Despite much work within the last decade on foundational properties of SPARQL - the standard query language for RDF data - rather little is known about the exact limits of tractability for this language. In particular, this is the case for SPARQL queries that contain the OPTIONAL-operator, even though it is one of the most intensively studied features of SPARQL. The aim of our work is to provide a more thorough picture of tractable classes of SPARQL queries. In general, SPARQL query evaluatio...

Man vs. Machine: Differences in SPARQL Queries

NARCIS (Netherlands)

Rietveld, L.; Hoekstra, R.

2014-01-01

Server-side SPARQL query logs have been a topic of study for some time now. The USEWOD collection of query logs is currently the primary source of information for researchers. A recurring problem is that these logs leave application queries and queries created by humans indistinguishable. In this

Superfund Query

Data.gov (United States)

U.S. Environmental Protection Agency — The Superfund Query allows users to retrieve data from the Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) database.

Advanced Query Formulation in Deductive Databases.

Science.gov (United States)

Niemi, Timo; Jarvelin, Kalervo

1992-01-01

Discusses deductive databases and database management systems (DBMS) and introduces a framework for advanced query formulation for end users. Recursive processing is described, a sample extensional database is presented, query types are explained, and criteria for advanced query formulation from the end user's viewpoint are examined. (31…

An RDF/OWL knowledge base for query answering and decision support in clinical pharmacogenetics.

Science.gov (United States)

Samwald, Matthias; Freimuth, Robert; Luciano, Joanne S; Lin, Simon; Powers, Robert L; Marshall, M Scott; Adlassnig, Klaus-Peter; Dumontier, Michel; Boyce, Richard D

2013-01-01

Genetic testing for personalizing pharmacotherapy is bound to become an important part of clinical routine. To address associated issues with data management and quality, we are creating a semantic knowledge base for clinical pharmacogenetics. The knowledge base is made up of three components: an expressive ontology formalized in the Web Ontology Language (OWL 2 DL), a Resource Description Framework (RDF) model for capturing detailed results of manual annotation of pharmacogenomic information in drug product labels, and an RDF conversion of relevant biomedical datasets. Our work goes beyond the state of the art in that it makes both automated reasoning as well as query answering as simple as possible, and the reasoning capabilities go beyond the capabilities of previously described ontologies.

Dynamic Planar Range Maxima Queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Tsakalidis, Konstantinos

2011-01-01

We consider the dynamic two-dimensional maxima query problem. Let P be a set of n points in the plane. A point is maximal if it is not dominated by any other point in P. We describe two data structures that support the reporting of the t maximal points that dominate a given query point, and allow...... for insertions and deletions of points in P. In the pointer machine model we present a linear space data structure with O(logn + t) worst case query time and O(logn) worst case update time. This is the first dynamic data structure for the planar maxima dominance query problem that achieves these bounds...... are integers in the range U = {0, …,2 w  − 1 }. We present a linear space data structure that supports 3-sided range maxima queries in O(logn/loglogn+t) worst case time and updates in O(logn/loglogn) worst case time. These are the first sublogarithmic worst case bounds for all operations in the RAM model....

Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying.

Science.gov (United States)

Masseroli, Marco; Kaitoua, Abdulrahman; Pinoli, Pietro; Ceri, Stefano

2016-12-01

While a huge amount of (epi)genomic data of multiple types is becoming available by using Next Generation Sequencing (NGS) technologies, the most important emerging problem is the so-called tertiary analysis, concerned with sense making, e.g., discovering how different (epi)genomic regions and their products interact and cooperate with each other. We propose a paradigm shift in tertiary analysis, based on the use of the Genomic Data Model (GDM), a simple data model which links genomic feature data to their associated experimental, biological and clinical metadata. GDM encompasses all the data formats which have been produced for feature extraction from (epi)genomic datasets. We specifically describe the mapping to GDM of SAM (Sequence Alignment/Map), VCF (Variant Call Format), NARROWPEAK (for called peaks produced by NGS ChIP-seq or DNase-seq methods), and BED (Browser Extensible Data) formats, but GDM supports as well all the formats describing experimental datasets (e.g., including copy number variations, DNA somatic mutations, or gene expressions) and annotations (e.g., regarding transcription start sites, genes, enhancers or CpG islands). We downloaded and integrated samples of all the above-mentioned data types and formats from multiple sources. The GDM is able to homogeneously describe semantically heterogeneous data and makes the ground for providing data interoperability, e.g., achieved through the GenoMetric Query Language (GMQL), a high-level, declarative query language for genomic big data. The combined use of the data model and the query language allows comprehensive processing of multiple heterogeneous data, and supports the development of domain-specific data-driven computations and bio-molecular knowledge discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Nearest Neighbor Queries in Road Networks

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kolar, Jan; Pedersen, Torben Bach

2003-01-01

in road networks. Such queries may be of use in many services. Specifically, we present an easily implementable data model that serves well as a foundation for such queries. We also present the design of a prototype system that implements the queries based on the data model. The algorithm used...

OGC Geographic Information Service Deductive Semantic Reasoning Based on Description Vocabularies Reduction

Directory of Open Access Journals (Sweden)

MIAO Lizhi

2015-09-01

Full Text Available As geographic information interoperability and sharing developing, more and more interoperable OGC (open geospatial consortium Web services (OWS are generated and published through the internet. These services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with executive semantic retrieval. This is especially true when considering the weak semantic description of geographic information service data. Focusing on semantic retrieval and reasoning of the distributed OWS resources, a deductive and semantic reasoning method is proposed to describe and search relevant OWS resources. Specifically, ①description words are extracted from OWS metadata file to generate GISe ontology-database and instance-database based on geographic ontology according to basic geographic elements category, ②a description words reduction model is put forward to implement knowledge reduction on GISe instance-database based on rough set theory and generate optimized instances database, ③utilizing GISe ontology-database and optimized instance-database to implement semantic inference and reasoning of geographic searching objects is used as an example to demonstrate the efficiency, feasibility and recall ration of the proposed description-word-based reduction model.

Fingerprinting Keywords in Search Queries over Tor

Directory of Open Access Journals (Sweden)

Oh Se Eun

2017-10-01

Full Text Available Search engine queries contain a great deal of private and potentially compromising information about users. One technique to prevent search engines from identifying the source of a query, and Internet service providers (ISPs from identifying the contents of queries is to query the search engine over an anonymous network such as Tor.

Adding Query Privacy to Robust DHTs

DEFF Research Database (Denmark)

Backes, Michael; Goldberg, Ian; Kate, Aniket

2011-01-01

intermediate peers that (help to) route the queries towards their destinations. In this paper, we satisfy this requirement by presenting an approach for providing privacy for the keys in DHT queries. We use the concept of oblivious transfer (OT) in communication over DHTs to preserve query privacy without...... of obtaining query privacy over robust DHTs. Finally, we compare the performance of our privacy-preserving protocols with their more privacy-invasive counterparts. We observe that there is no increase in the message complexity and only a small overhead in the computational complexity....

QUERY SUPPORT FOR GMZ

Directory of Open Access Journals (Sweden)

A. Khandelwal

2017-07-01

Full Text Available Generic text-based compression models are simple and fast but there are two issues that needs to be addressed. They cannot leverage the structure that exists in data to achieve better compression and there is an unnecessary decompression step before the user can actually use the data. To address these issues, we came up with GMZ, a lossless compression model aimed at achieving high compression ratios. The decision to design GMZ (Khandelwal and Rajan, 2017 exclusively for GML's Simple Features Profile (SFP seems fair because of the high use of SFP in WFS and that it facilitates high optimisation of the compression model. This is an extension of our work on GMZ. In a typical server-client model such as Web Feature Service, the server is the primary creator and provider of GML, and therefore, requires compression and query capabilities. On the other hand, the client is the primary consumer of GML, and therefore, requires decompression and visualisation capabilities. In the first part of our work, we demonstrated compression using a python script that can be plugged in a server architecture, and decompression and visualisation in a web browser using a Firefox addon. The focus of this work is to develop the already existing tools to provide query capability to server. Our model provides the ability to decompress individual features in isolation, which is an essential requirement for realising query in compressed state. We con - struct an R-Tree index for spatial data and a custom index for non-spatial data and store these in a separate index file to prevent alter - ing the compression model. This facilitates independent use of compressed GMZ file where index can be constructed when required. The focus of this work is the bounding-box or range query commonly used in webGIS with provision for other spatial and non-spatial queries. The decrement in compression ratios due to the new index file is in the range of 1–3 percent which is trivial considering

Ranking Queries on Uncertain Data

CERN Document Server

Hua, Ming

2011-01-01

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorith

Predecessor queries in dynamic integer sets

DEFF Research Database (Denmark)

Brodal, Gerth Stølting

1997-01-01

We consider the problem of maintaining a set of n integers in the range 0.2w–1 under the operations of insertion, deletion, predecessor queries, minimum queries and maximum queries on a unit cost RAM with word size w bits. Let f (n) be an arbitrary nondecreasing smooth function satisfying n...

Flexible Query Answering Systems 2006

DEFF Research Database (Denmark)

-computer interaction. The overall theme of the FQAS conferences is innovative query systems aimed at providing easy, flexible, and intuitive access to information. Such systems are intended to facilitate retrieval from information repositories such as databases, libraries, and the World-Wide Web. These repositories......This volume constitutes the proceedings of the Seventh International Conference on Flexible Query Answering Systems, FQAS 2006, held in Milan, Italy, on June 7--10, 2006. FQAS is the premier conference for researchers and practitioners concerned with the vital task of providing easy, flexible...... are typically equipped with standard query systems which are often inadequate, and the focus of FQAS is the development of query systems that are more expressive, informative, cooperative, and productive. These proceedings contain contributions from invited speakers and 53 original papers out of about 100...

Linked Metadata - lightweight semantics for data integration (Invited)

Science.gov (United States)

Hendler, J. A.

2013-12-01

fly integration may prefer to do more traditional data queries and then convert and link the 'views' returned at retrieval time, providing another means of using the linked data infrastructure without having to convert whole datasets to triples to provide linking. Web companies have been taking advantage of 'lightweight' semantic metadata for search quality and optimization (cf. schema.org), linking networks within and without web sites (cf. Facebook's Open Graph Protocol), and in doing various kinds of advertisement and user modeling across datasets. Scientific metadata, on the other hand, has traditionally been geared at being largescale and highly descriptive, and scientific ontologies have been aimed at high expressivity, essentially providing complex reasoning services rather than the less expressive vocabularies needed for data discovery and simple mappings that can allow humans (or more complex systems) when full scale integration is needed. Although this work is just the beginning for providing integration, as the community creates more and more datasets, discovery of these data resources on the Web becomes a crucial starting place. Simple descriptors, that can be combined with textual fields and/or common community vocabularies, can be a great starting place on bringing scientific data into the Web of Data that is growing in other communities. References: [1] Pouchard, Line C., et al. "A Linked Science investigation: enhancing climate change data discovery with semantic technologies." Earth science informatics 6.3 (2013): 175-185.

Spatio-temporal databases complex motion pattern queries

CERN Document Server

Vieira, Marcos R

2013-01-01

This brief presents several new query processing techniques, called complex motion pattern queries, specifically designed for very large spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the integration of variables and motion patterns. This is followed by a summary of the expressive power of patterns and flexibility of pattern queries. The brief then present the Spatio-Temporal Pattern System (STPS) and density-based pattern queries. STPS databases contain millions of records with information about mobi

Ontology-Based Querying with Bio2RDF's Linked Open Data.

Science.gov (United States)

Callahan, Alison; Cruz-Toledo, José; Dumontier, Michel

2013-04-15

A key activity for life scientists in this post "-omics" age involves searching for and integrating biological data from a multitude of independent databases. However, our ability to find relevant data is hampered by non-standard web and database interfaces backed by an enormous variety of data formats. This heterogeneity presents an overwhelming barrier to the discovery and reuse of resources which have been developed at great public expense.To address this issue, the open-source Bio2RDF project promotes a simple convention to integrate diverse biological data using Semantic Web technologies. However, querying Bio2RDF remains difficult due to the lack of uniformity in the representation of Bio2RDF datasets. We describe an update to Bio2RDF that includes tighter integration across 19 new and updated RDF datasets. All available open-source scripts were first consolidated to a single GitHub repository and then redeveloped using a common API that generates normalized IRIs using a centralized dataset registry. We then mapped dataset specific types and relations to the Semanticscience Integrated Ontology (SIO) and demonstrate simplified federated queries across multiple Bio2RDF endpoints. This coordinated release marks an important milestone for the Bio2RDF open source linked data framework. Principally, it improves the quality of linked data in the Bio2RDF network and makes it easier to access or recreate the linked data locally. We hope to continue improving the Bio2RDF network of linked data by identifying priority databases and increasing the vocabulary coverage to additional dataset vocabularies beyond SIO.

Discount-Optimal Infinite Runs in Priced Timed Automata

DEFF Research Database (Denmark)

Fahrenberg, Uli; Larsen, Kim Guldstrand

2009-01-01

We introduce a new discounting semantics for priced timed automata. Discounting provides a way to model optimal-cost problems for infinite traces and has applications in optimal scheduling and other areas. In the discounting semantics, prices decrease exponentially, so that the contribution...

RANDOMNESS of Numbers DEFINITION(QUERY:WHAT? V HOW?) ONLY Via MAXWELL-BOLTZMANN CLASSICAL-Statistics(MBCS) Hot-Plasma VS. Digits-Clumping Log-Law NON-Randomness Inversion ONLY BOSE-EINSTEIN QUANTUM-Statistics(BEQS) .

Science.gov (United States)

Siegel, Z.; Siegel, Edward Carl-Ludwig

2011-03-01

RANDOMNESS of Numbers cognitive-semantics DEFINITION VIA Cognition QUERY: WHAT???, NOT HOW?) VS. computer-``science" mindLESS number-crunching (Harrel-Sipser-...) algorithmics Goldreich "PSEUDO-randomness"[Not.AMS(02)] mea-culpa is ONLY via MAXWELL-BOLTZMANN CLASSICAL-STATISTICS(NOT FDQS!!!) "hot-plasma" REPULSION VERSUS Newcomb(1881)-Weyl(1914;1916)-Benford(1938) "NeWBe" logarithmic-law digit-CLUMPING/ CLUSTERING NON-Randomness simple Siegel[AMS Joint.Mtg.(02)-Abs. # 973-60-124] algebraic-inversion to THE QUANTUM and ONLY BEQS preferentially SEQUENTIALLY lower-DIGITS CLUMPING/CLUSTERING with d = 0 BEC, is ONLY VIA Siegel-Baez FUZZYICS=CATEGORYICS (SON OF TRIZ)/"Category-Semantics"(C-S), latter intersection/union of Lawvere(1964)-Siegel(1964)] category-theory (matrix: MORPHISMS V FUNCTORS) "+" cognitive-semantics'' (matrix: ANTONYMS V SYNONYMS) yields Siegel-Baez FUZZYICS=CATEGORYICS/C-S tabular list-format matrix truth-table analytics: MBCS RANDOMNESS TRUTH/EMET!!!

CrossQuery: a web tool for easy associative querying of transcriptome data.

Directory of Open Access Journals (Sweden)

Toni U Wagner

Full Text Available Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.

CrossQuery: a web tool for easy associative querying of transcriptome data.

Science.gov (United States)

Wagner, Toni U; Fischer, Andreas; Thoma, Eva C; Schartl, Manfred

2011-01-01

Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.

Multi-Dimensional Top-k Dominating Queries

DEFF Research Database (Denmark)

Yiu, Man Lung; Mamoulis, Nikos

2009-01-01

The top-k dominating query returns k data objects which dominate the highest number of objects in a dataset. This query is an important tool for decision support since it provides data analysts an intuitive way for finding significant objects. In addition, it combines the advantages of top......-k and skyline queries without sharing their disadvantages: (i) the output size can be controlled, (ii) no ranking functions need to be specified by users, and (iii) the result is independent of the scales at different dimensions. Despite their importance, top-k dominating queries have not received adequate...

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.

Integration of Neuroimaging and Microarray Datasets  through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

Directory of Open Access Journals (Sweden)

Spiro P. Pantazatos

2009-06-01

Full Text Available An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP and a knowledge-based phenotype organizer system (PhenOS to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®. The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50, and precision of the semantic mapping between these terms across datasets was 98% (n = 100. To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets.

An Adaptive SPARQL Engine with Dynamic Partitioning for Distributed RDF Repositories

KAUST Repository

Ibrahim, Yasser E.

2012-07-01

The tremendous increase in the semantic data is driving the demand for efficient query engines. RDF data being generated at an unprecedented rate introduces a storage, indexing, and querying challenge. Due to the size of the data and the federated nature of the semantic web, it is in many cases impractical to assume a central repository, and more attention is being given to distributed RDF stores. This work is motivated by two major drawbacks of current solutions: 1) pre-processing part is very expensive and takes prohibitively long time for large datasets, and 2) current distributed systems assume that a static partitioning of the data should perform well for all kinds of queries, and do not consider fluctuations in the queryload. In this paper we propose PHD-Store, an in-memory SPARQL engine for distributed RDF repositories. Our system does not assume any particular initial placement of the data and does not require pre-processing before running the first query. It analyzes incoming queries and adjusts data placement dynamically in such a way that communication among repositories is minimized for future queries. To achieve this flexibility, frequent query patterns are detected, and data are redistributed through a Propagating Hash Distribution (PHD) algorithm to ensure optimal placement for frequent query patterns. Our experiments with large RDF graphs verify that PHD-Store scales well and executes complex queries more efficiently than existing systems.

jQuery UI 1.10 the user interface library for jQuery

CERN Document Server

Libby, Alex

2013-01-01

This book consists of an easy-to-follow, example-based approach that leads you step-by-step through the implementation and customization of each library component.This book is for frontend designers and developers who need to learn how to use jQuery UI quickly. To get the most out of this book, you should have a good working knowledge of HTML, CSS, and JavaScript, and should ideally be comfortable using jQuery.

Moving Spatial Keyword Queries

DEFF Research Database (Denmark)

Wu, Dingming; Yiu, Man Lung; Jensen, Christian S.

2013-01-01

propose two algorithms for computing safe zones that guarantee correct results at any time and that aim to optimize the server-side computation as well as the communication between the server and the client. We exploit tight and conservative approximations of safe zones and aggressive computational space...... text data. State-of-the-art solutions for moving queries employ safe zones that guarantee the validity of reported results as long as the user remains within the safe zone associated with a result. However, existing safe-zone methods focus solely on spatial locations and ignore text relevancy. We...... pruning. We present techniques that aim to compute the next safe zone efficiently, and we present two types of conservative safe zones that aim to reduce the communication cost. Empirical studies with real data suggest that the proposals are efficient. To understand the effectiveness of the proposed safe...

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,

PAQ: Persistent Adaptive Query Middleware for Dynamic Environments

Science.gov (United States)

Rajamani, Vasanth; Julien, Christine; Payton, Jamie; Roman, Gruia-Catalin

Pervasive computing applications often entail continuous monitoring tasks, issuing persistent queries that return continuously updated views of the operational environment. We present PAQ, a middleware that supports applications' needs by approximating a persistent query as a sequence of one-time queries. PAQ introduces an integration strategy abstraction that allows composition of one-time query responses into streams representing sophisticated spatio-temporal phenomena of interest. A distinguishing feature of our middleware is the realization that the suitability of a persistent query's result is a function of the application's tolerance for accuracy weighed against the associated overhead costs. In PAQ, programmers can specify an inquiry strategy that dictates how information is gathered. Since network dynamics impact the suitability of a particular inquiry strategy, PAQ associates an introspection strategy with a persistent query, that evaluates the quality of the query's results. The result of introspection can trigger application-defined adaptation strategies that alter the nature of the query. PAQ's simple API makes developing adaptive querying systems easily realizable. We present the key abstractions, describe their implementations, and demonstrate the middleware's usefulness through application examples and evaluation.

QUERY RESPONSE TIME COMPARISON NOSQLDB MONGODB WITH SQLDB ORACLE

Directory of Open Access Journals (Sweden)

Humasak T. A. Simanjuntak

2015-01-01

Full Text Available Penyimpanan data saat ini terdapat dua jenis yakni relational database dan non-relational database. Kedua jenis DBMS (Database Managemnet System tersebut berbeda dalam berbagai aspek seperti per-formansi eksekusi query, scalability, reliability maupun struktur penyimpanan data. Kajian ini memiliki tujuan untuk mengetahui perbandingan performansi DBMS antara Oracle sebagai jenis relational data-base dan MongoDB sebagai jenis non-relational database dalam mengolah data terstruktur. Eksperimen dilakukan untuk mengetahui perbandingan performansi kedua DBMS tersebut untuk operasi insert, select, update dan delete dengan menggunakan query sederhana maupun kompleks pada database Northwind. Untuk mencapai tujuan eksperimen, 18 query yang terdiri dari 2 insert query, 10 select query, 2 update query dan 2 delete query dieksekusi. Query dieksekusi melalui sebuah aplikasi .Net yang dibangun sebagai perantara antara user dengan basis data. Eksperimen dilakukan pada tabel dengan atau tanpa relasi pada Oracle dan embedded atau bukan embedded dokumen pada MongoDB. Response time untuk setiap eksekusi query dibandingkan dengan menggunakan metode statistik. Eksperimen menunjukkan response time query untuk proses select, insert, dan update pada MongoDB lebih cepatdaripada Oracle. MongoDB lebih cepat 64.8 % untuk select query;MongoDB lebihcepat 72.8 % untuk insert query dan MongoDB lebih cepat 33.9 % untuk update query. Pada delete query, Oracle lebih cepat 96.8 % daripada MongoDB untuk table yang berelasi, tetapi MongoDB lebih cepat 83.8 % daripada Oracle untuk table yang tidak memiliki relasi.Untuk query kompleks dengan Map Reduce pada MongoDB lebih lambat 97.6% daripada kompleks query dengan aggregate function pada Oracle.

Learning jQuery

CERN Document Server

Chaffer, Jonathan

2013-01-01

Step through each of the core concepts of the jQuery library, building an overall picture of its capabilities. Once you have thoroughly covered the basics, the book returns to each concept to cover more advanced examples and techniques.This book is for web designers who want to create interactive elements for their designs, and for developers who want to create the best user interface for their web applications. Basic JavaScript programming and knowledge of HTML and CSS is required. No knowledge of jQuery is assumed, nor is experience with any other JavaScript libraries.

Knowledge Query Language (KQL)

Science.gov (United States)

2016-02-12

described as a sparse, distributed multidimensional sorted map. Unlike a relational database , BigTable has no multicolumn primary keys or constraints. The...in query languages such as SQL. Figure 3. Address expression-based querying. Each circled step in Figure 3 is described below. Datastore/ Database ...implementation we describe in later sections stores the instance of registry ontology in JSON files. 7 Throughout the rest of this report, we use the

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

Science.gov (United States)

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

Varieties of semantic 'access' deficit in Wernicke's aphasia and semantic aphasia.

Science.gov (United States)

Thompson, Hannah E; Robson, Holly; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2015-12-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke's aphasia, associated with poor auditory-verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic 'access' deficit, as opposed to the 'storage' deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of 'access' impairment-related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke's aphasia). We used a case series design to compare patients with Wernicke's aphasia and those with semantic aphasia on Warrington's paradigmatic assessment of semantic 'access' deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic 'blocking' effects). Patients with Wernicke's aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability-one that mapped onto classical 'syndromes' and one that did not-predicted aspects of the semantic 'access' deficit. Both semantic aphasia and Wernicke's aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke's aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially 'beneficial' effects of stimulus repetition: cases with

Publishing high-quality climate data on the semantic web

Science.gov (United States)

Woolf, Andrew; Haller, Armin; Lefort, Laurent; Taylor, Kerry

2013-04-01

temperature dataset, Australian Climate Observations Reference Network - Surface Air Temperature (ACORN-SAT) [BoM, 2012b]. This dataset contains daily homogenised surface temperature observations for 112 locations around Australia, dating back to 1910. An ontology for the dataset was developed [Lefort et. al., 2012], based on the existing Semantic Sensor Network ontology [Compton et. al., 2012] and the W3C RDF Data Cube vocabulary [W3C, 2012]. Additional vocabularies were developed, e.g. for BoM weather stations and rainfall districts. The dataset was converted to RDF and loaded into an RDF triplestore. The Linked-Data API (http://code.google.com/p/linked-data-api) was used to configure specific URI query patterns (e.g. for observation timeseries slices by station), and a SPARQL endpoint was provided for direct querying. In addition, some demonstration 'mash-ups' were developed, providing an interactive browser-based interface to the temperature timeseries. References [Berners-Lee et. al., 2001] Tim Berners-Lee, James Hendler and Ora Lassila (2001), "The Semantic Web", Scientific American, May 2001. [Berners-Lee, 2006] Tim Berners-Lee (2006), "Linked Data - Design Issues", W3C [http://www.w3.org/DesignIssues/LinkedData.html] [BoM, 2012a] Bureau of Meteorology (2012), "Environmental information" [http://www.bom.gov.au/environment/] [BoM, 2012b] Bureau of Meteorology (2012), "Australian Climate Observations Reference Network - Surface Air Temperature" [http://www.bom.gov.au/climate/change/acorn-sat/] [Compton et. al., 2012] Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit Sheth, Kerry Taylor (2012), "The SSN Ontology of the W3C Semantic Sensor Network Incubator Group", J. Web Semantics, 17 (2012) [http

Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

Directory of Open Access Journals (Sweden)

Suzuki Motoyuki

2009-01-01

Full Text Available Abstract We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the "query relevance." Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

Directory of Open Access Journals (Sweden)

Akinori Ito

2009-01-01

Full Text Available We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the “query relevance.” Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

Implementation of Quantum Private Queries Using Nuclear Magnetic Resonance

International Nuclear Information System (INIS)

Wang Chuan; Hao Liang; Zhao Lian-Jie

2011-01-01

We present a modified protocol for the realization of a quantum private query process on a classical database. Using one-qubit query and CNOT operation, the query process can be realized in a two-mode database. In the query process, the data privacy is preserved as the sender would not reveal any information about the database besides her query information, and the database provider cannot retain any information about the query. We implement the quantum private query protocol in a nuclear magnetic resonance system. The density matrix of the memory registers are constructed. (general)

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…

SPARQL Query Re-writing Using Partonomy Based Transformation Rules

Science.gov (United States)

Jain, Prateek; Yeh, Peter Z.; Verma, Kunal; Henson, Cory A.; Sheth, Amit P.

Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology's containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query constraints and knowledge base. Our experiments were performed on completely third party datasets and queries. Evaluations were performed on Geonames dataset using questions from National Geographic Bee serialized into SPARQL and British Administrative Geography Ontology using questions from a popular trivia website. These experiments demonstrate high precision in retrieval of results and ease in writing queries.

Semantic similarity measures in the biomedical domain by leveraging a web search engine.

Science.gov (United States)

Hsieh, Sheau-Ling; Chang, Wen-Yung; Chen, Chi-Huang; Weng, Yung-Ching

2013-07-01

Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.

Semantic annotation of consumer health questions.

Science.gov (United States)

Kilicoglu, Halil; Ben Abacha, Asma; Mrabet, Yassine; Shooshan, Sonya E; Rodriguez, Laritza; Masterton, Kate; Demner-Fushman, Dina

2018-02-06

Consumers increasingly use online resources for their health information needs. While current search engines can address these needs to some extent, they generally do not take into account that most health information needs are complex and can only fully be expressed in natural language. Consumer health question answering (QA) systems aim to fill this gap. A major challenge in developing consumer health QA systems is extracting relevant semantic content from the natural language questions (question understanding). To develop effective question understanding tools, question corpora semantically annotated for relevant question elements are needed. In this paper, we present a two-part consumer health question corpus annotated with several semantic categories: named entities, question triggers/types, question frames, and question topic. The first part (CHQA-email) consists of relatively long email requests received by the U.S. National Library of Medicine (NLM) customer service, while the second part (CHQA-web) consists of shorter questions posed to MedlinePlus search engine as queries. Each question has been annotated by two annotators. The annotation methodology is largely the same between the two parts of the corpus; however, we also explain and justify the differences between them. Additionally, we provide information about corpus characteristics, inter-annotator agreement, and our attempts to measure annotation confidence in the absence of adjudication of annotations. The resulting corpus consists of 2614 questions (CHQA-email: 1740, CHQA-web: 874). Problems are the most frequent named entities, while treatment and general information questions are the most common question types. Inter-annotator agreement was generally modest: question types and topics yielded highest agreement, while the agreement for more complex frame annotations was lower. Agreement in CHQA-web was consistently higher than that in CHQA-email. Pairwise inter-annotator agreement proved most

Mobile Information Access with Spoken Query Answering

DEFF Research Database (Denmark)

Brøndsted, Tom; Larsen, Henrik Legind; Larsen, Lars Bo

2006-01-01

window focused over the part which most likely contains an answer to the query. The two systems are integrated into a full spoken query answering system. The prototype can answer queries and questions within the chosen football (soccer) test domain, but the system has the flexibility for being ported...

On the formulation of performant sparql queries

NARCIS (Netherlands)

Loizou, A.; Angles, R.; Groth, P.T.

2014-01-01

Abstract The combination of the flexibility of RDF and the expressiveness of SPARQL provides a powerful mechanism to model, integrate and query data. However, these properties also mean that it is nontrivial to write performant SPARQL queries. Indeed, it is quite easy to create queries that tax even

Relationship Structures and Semantic Type Assignments of the UMLS Enriched Semantic Network

Science.gov (United States)

Zhang, Li; Halper, Michael; Perl, Yehoshua; Geller, James; Cimino, James J.

2005-01-01

Objective: The Enriched Semantic Network (ESN) was introduced as an extension of the Unified Medical Language System (UMLS) Semantic Network (SN). Its multiple subsumption configuration and concomitant multiple inheritance make the ESN's relationship structures and semantic type assignments different from those of the SN. A technique for deriving the relationship structures of the ESN's semantic types and an automated technique for deriving the ESN's semantic type assignments from those of the SN are presented. Design: The technique to derive the ESN's relationship structures finds all newly inherited relationships in the ESN. All such relationships are audited for semantic validity, and the blocking mechanism is used to block invalid relationships. The mapping technique to derive the ESN's semantic type assignments uses current SN semantic type assignments and preserves nonredundant categorizations, while preventing new redundant categorizations. Results: Among the 426 newly inherited relationships, 326 are deemed valid. Seven blockings are applied to avoid inheritance of the 100 invalid relationships. Sixteen semantic types have different relationship structures in the ESN as compared to those in the SN. The mapping of semantic type assignments from the SN to the ESN avoids the generation of 26,950 redundant categorizations. The resulting ESN contains 138 semantic types, 149 IS-A links, 7,303 relationships, and 1,013,876 semantic type assignments. Conclusion: The ESN's multiple inheritance provides more complete relationship structures than in the SN. The ESN's semantic type assignments avoid the existing redundant categorizations appearing in the SN and prevent new ones that might arise due to multiple parents. Compared to the SN, the ESN provides a more accurate unifying semantic abstraction of the UMLS Metathesaurus. PMID:16049233

Evaluation of Sub Query Performance in SQL Server

Science.gov (United States)

Oktavia, Tanty; Sujarwo, Surya

2014-03-01

The paper explores several sub query methods used in a query and their impact on the query performance. The study uses experimental approach to evaluate the performance of each sub query methods combined with indexing strategy. The sub query methods consist of in, exists, relational operator and relational operator combined with top operator. The experimental shows that using relational operator combined with indexing strategy in sub query has greater performance compared with using same method without indexing strategy and also other methods. In summary, for application that emphasized on the performance of retrieving data from database, it better to use relational operator combined with indexing strategy. This study is done on Microsoft SQL Server 2012.

Towards the novel reasoning among particles in PSO by the use of RDF and SPARQL.

Science.gov (United States)

Fister, Iztok; Yang, Xin-She; Ljubič, Karin; Fister, Dušan; Brest, Janez; Fister, Iztok

2014-01-01

The significant development of the Internet has posed some new challenges and many new programming tools have been developed to address such challenges. Today, semantic web is a modern paradigm for representing and accessing knowledge data on the Internet. This paper tries to use the semantic tools such as resource definition framework (RDF) and RDF query language (SPARQL) for the optimization purpose. These tools are combined with particle swarm optimization (PSO) and the selection of the best solutions depends on its fitness. Instead of the local best solution, a neighborhood of solutions for each particle can be defined and used for the calculation of the new position, based on the key ideas from semantic web domain. The preliminary results by optimizing ten benchmark functions showed the promising results and thus this method should be investigated further.

Towards the Novel Reasoning among Particles in PSO by the Use of RDF and SPARQL

Directory of Open Access Journals (Sweden)

Iztok Fister

2014-01-01

Full Text Available The significant development of the Internet has posed some new challenges and many new programming tools have been developed to address such challenges. Today, semantic web is a modern paradigm for representing and accessing knowledge data on the Internet. This paper tries to use the semantic tools such as resource definition framework (RDF and RDF query language (SPARQL for the optimization purpose. These tools are combined with particle swarm optimization (PSO and the selection of the best solutions depends on its fitness. Instead of the local best solution, a neighborhood of solutions for each particle can be defined and used for the calculation of the new position, based on the key ideas from semantic web domain. The preliminary results by optimizing ten benchmark functions showed the promising results and thus this method should be investigated further.

Responsive web design with jQuery

CERN Document Server

Carlos, Gilberto

2013-01-01

Responsive Web Design with jQuery follows a standard tutorial-based approach, covering various aspects of responsive web design by building a comprehensive website.""Responsive Web Design with jQuery"" is aimed at web designers who are interested in building device-agnostic websites. You should have a grasp of standard HTML, CSS, and JavaScript development, and have a familiarity with graphic design. Some exposure to jQuery and HTML5 will be beneficial but isn't essential.

Adding query privacy to robust DHTs

DEFF Research Database (Denmark)

Backes, Michael; Goldberg, Ian; Kate, Aniket

2012-01-01

intermediate peers that (help to) route the queries towards their destinations. In this paper, we satisfy this requirement by presenting an approach for providing privacy for the keys in DHT queries. We use the concept of oblivious transfer (OT) in communication over DHTs to preserve query privacy without...... privacy over robust DHTs. Finally, we compare the performance of our privacy-preserving protocols with their more privacy-invasive counterparts. We observe that there is no increase in the message complexity...

Querying Archetype-Based Electronic Health Records Using Hadoop and Dewey Encoding of openEHR Models.

Science.gov (United States)

Sundvall, Erik; Wei-Kleiner, Fang; Freire, Sergio M; Lambrix, Patrick

2017-01-01

Archetype-based Electronic Health Record (EHR) systems using generic reference models from e.g. openEHR, ISO 13606 or CIMI should be easy to update and reconfigure with new types (or versions) of data models or entries, ideally with very limited programming or manual database tweaking. Exploratory research (e.g. epidemiology) leading to ad-hoc querying on a population-wide scale can be a challenge in such environments. This publication describes implementation and test of an archetype-aware Dewey encoding optimization that can be used to produce such systems in environments supporting relational operations, e.g. RDBMs and distributed map-reduce frameworks like Hadoop. Initial testing was done using a nine-node 2.2 GHz quad-core Hadoop cluster querying a dataset consisting of targeted extracts from 4+ million real patient EHRs, query results with sub-minute response time were obtained.

Can social semantic web techniques foster collaborative curriculum mapping in medicine?

Science.gov (United States)

Spreckelsen, Cord; Finsterer, Sonja; Cremer, Jan; Schenkat, Hennig

2013-08-15

Curriculum mapping, which is aimed at the systematic realignment of the planned, taught, and learned curriculum, is considered a challenging and ongoing effort in medical education. Second-generation curriculum managing systems foster knowledge management processes including curriculum mapping in order to give comprehensive support to learners, teachers, and administrators. The large quantity of custom-built software in this field indicates a shortcoming of available IT tools and standards. The project reported here aims at the systematic adoption of techniques and standards of the Social Semantic Web to implement collaborative curriculum mapping for a complete medical model curriculum. A semantic MediaWiki (SMW)-based Web application has been introduced as a platform for the elicitation and revision process of the Aachen Catalogue of Learning Objectives (ACLO). The semantic wiki uses a domain model of the curricular context and offers structured (form-based) data entry, multiple views, structured querying, semantic indexing, and commenting for learning objectives ("LOs"). Semantic indexing of learning objectives relies on both a controlled vocabulary of international medical classifications (ICD, MeSH) and a folksonomy maintained by the users. An additional module supporting the global checking of consistency complements the semantic wiki. Statements of the Object Constraint Language define the consistency criteria. We evaluated the application by a scenario-based formative usability study, where the participants solved tasks in the (fictional) context of 7 typical situations and answered a questionnaire containing Likert-scaled items and free-text questions. At present, ACLO contains roughly 5350 operational (ie, specific and measurable) objectives acquired during the last 25 months. The wiki-based user interface uses 13 online forms for data entry and 4 online forms for flexible searches of LOs, and all the forms are accessible by standard Web browsers. The

Trust estimation of the semantic web using semantic web clustering

Science.gov (United States)

Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid

2017-05-01

Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Science.gov (United States)

Keller, Richard M.; Ranjan, Shubha; Wei, Mie; Eshow, Michelle

2016-01-01

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

The paca that roared: Immediate cumulative semantic interference among newly acquired words.

Science.gov (United States)

Oppenheim, Gary M

2018-08-01

With 40,000 words in the average vocabulary, how can speakers find the specific words that they want so quickly and easily? Cumulative semantic interference in language production provides a clue: when naming a large series of pictures, with a few mammals sprinkled about, naming each subsequent mammal becomes slower and more error-prone. Such interference mirrors predictions from an incremental learning algorithm applied to meaning-driven retrieval from an established vocabulary, suggesting retrieval benefits from a constant, implicit, re-optimization process (Oppenheim et al., 2010). But how quickly would a new mammal (e.g. paca) engage in this re-optimization? In this experiment, 18 participants studied 3 novel and 3 familiar exemplars from each of six semantic categories, and immediately performed a timed picture-naming task. Consistent with the learning model's predictions, naming latencies revealed immediate cumulative semantic interference in all directions: from new words to new words, from new words to old words, from old words to new words, and from old words to old words. Repeating the procedure several days later produced similar-magnitude effects, demonstrating that newly acquired words can be immediately semantically integrated, at least to the extent necessary to produce typical cumulative semantic interference. These findings extend the Dark Side model's scope to include novel word production, and are considered in terms of mechanisms for lexical selection. Copyright © 2018 Elsevier B.V. All rights reserved.

Publication and Retrieval of Computational Chemical-Physical Data Via the Semantic Web. Final Technical Report

Energy Technology Data Exchange (ETDEWEB)

Ostlund, Neil [Chemical Semantics, Inc., Gainesville, FL (United States)

2017-07-20

This research showed the feasibility of applying the concepts of the Semantic Web to Computation Chemistry. We have created the first web portal (www.chemsem.com) that allows data created in the calculations of quantum chemistry, and other such chemistry calculations to be placed on the web in a way that makes the data accessible to scientists in a semantic form never before possible. The semantic web nature of the portal allows data to be searched, found, and used as an advance over the usual approach of a relational database. The semantic data on our portal has the nature of a Giant Global Graph (GGG) that can be easily merged with related data and searched globally via a SPARQL Protocol and RDF Query Language (SPARQL) that makes global searches for data easier than with traditional methods. Our Semantic Web Portal requires that the data be understood by a computer and hence defined by an ontology (vocabulary). This ontology is used by the computer in understanding the data. We have created such an ontology for computational chemistry (purl.org/gc) that encapsulates a broad knowledge of the field of computational chemistry. We refer to this ontology as the Gainesville Core. While it is perhaps the first ontology for computational chemistry and is used by our portal, it is only a start of what must be a long multi-partner effort to define computational chemistry. In conjunction with the above efforts we have defined a new potential file standard (Common Standard for eXchange – CSX for computational chemistry data). This CSX file is the precursor of data in the Resource Description Framework (RDF) form that the semantic web requires. Our portal translates CSX files (as well as other computational chemistry data files) into RDF files that are part of the graph database that the semantic web employs. We propose a CSX file as a convenient way to encapsulate computational chemistry data.

Evaluating SPARQL queries on massive RDF datasets

KAUST Repository

Al-Harbi, Razen; Abdelaziz, Ibrahim; Kalnis, Panos; Mamoulis, Nikos

2015-01-01

In this paper, we propose AdHash, a distributed RDF system which addresses the shortcomings of previous work. First, AdHash initially applies lightweight hash partitioning, which drastically minimizes the startup cost, while favoring the parallel processing of join patterns on subjects, without any data communication. Using a locality-aware planner, queries that cannot be processed in parallel are evaluated with minimal communication. Second, AdHash monitors the data access patterns and adapts dynamically to the query load by incrementally redistributing and replicating frequently accessed data. As a result, the communication cost for future queries is drastically reduced or even eliminated. Our experiments with synthetic and real data verify that AdHash (i) starts faster than all existing systems, (ii) processes thousands of queries before other systems become online, and (iii) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in sub-seconds. In this demonstration, audience can use a graphical interface of AdHash to verify its performance superiority compared to state-of-the-art distributed RDF systems.

Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

Directory of Open Access Journals (Sweden)

Wenquan Jin

2018-02-01

Full Text Available Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

Evaluating SPARQL queries on massive RDF datasets

KAUST Repository

Al-Harbi, Razen

2015-08-01

Distributed RDF systems partition data across multiple computer nodes. Partitioning is typically based on heuristics that minimize inter-node communication and it is performed in an initial, data pre-processing phase. Therefore, the resulting partitions are static and do not adapt to changes in the query workload; as a result, existing systems are unable to consistently avoid communication for queries that are not favored by the initial data partitioning. Furthermore, for very large RDF knowledge bases, the partitioning phase becomes prohibitively expensive, leading to high startup costs. In this paper, we propose AdHash, a distributed RDF system which addresses the shortcomings of previous work. First, AdHash initially applies lightweight hash partitioning, which drastically minimizes the startup cost, while favoring the parallel processing of join patterns on subjects, without any data communication. Using a locality-aware planner, queries that cannot be processed in parallel are evaluated with minimal communication. Second, AdHash monitors the data access patterns and adapts dynamically to the query load by incrementally redistributing and replicating frequently accessed data. As a result, the communication cost for future queries is drastically reduced or even eliminated. Our experiments with synthetic and real data verify that AdHash (i) starts faster than all existing systems, (ii) processes thousands of queries before other systems become online, and (iii) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in sub-seconds. In this demonstration, audience can use a graphical interface of AdHash to verify its performance superiority compared to state-of-the-art distributed RDF systems.

Code query by example

Science.gov (United States)

Vaucouleur, Sebastien

2011-02-01

We introduce code query by example for customisation of evolvable software products in general and of enterprise resource planning systems (ERPs) in particular. The concept is based on an initial empirical study on practices around ERP systems. We motivate our design choices based on those empirical results, and we show how the proposed solution helps with respect to the infamous upgrade problem: the conflict between the need for customisation and the need for upgrade of ERP systems. We further show how code query by example can be used as a form of lightweight static analysis, to detect automatically potential defects in large software products. Code query by example as a form of lightweight static analysis is particularly interesting in the context of ERP systems: it is often the case that programmers working in this field are not computer science specialists but more of domain experts. Hence, they require a simple language to express custom rules.

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.