NGNP Risk Management Database: A Model for Managing Risk

International Nuclear Information System (INIS)

Collins, John

2009-01-01

To facilitate the implementation of the Risk Management Plan, the Next Generation Nuclear Plant (NGNP) Project has developed and employed an analytical software tool called the NGNP Risk Management System (RMS). A relational database developed in Microsoft(reg s ign) Access, the RMS provides conventional database utility including data maintenance, archiving, configuration control, and query ability. Additionally, the tool's design provides a number of unique capabilities specifically designed to facilitate the development and execution of activities outlined in the Risk Management Plan. Specifically, the RMS provides the capability to establish the risk baseline, document and analyze the risk reduction plan, track the current risk reduction status, organize risks by reference configuration system, subsystem, and component (SSC) and Area, and increase the level of NGNP decision making.

NGNP Risk Management Database: A Model for Managing Risk

Energy Technology Data Exchange (ETDEWEB)

John Collins

2009-09-01

To facilitate the implementation of the Risk Management Plan, the Next Generation Nuclear Plant (NGNP) Project has developed and employed an analytical software tool called the NGNP Risk Management System (RMS). A relational database developed in Microsoft® Access, the RMS provides conventional database utility including data maintenance, archiving, configuration control, and query ability. Additionally, the tool’s design provides a number of unique capabilities specifically designed to facilitate the development and execution of activities outlined in the Risk Management Plan. Specifically, the RMS provides the capability to establish the risk baseline, document and analyze the risk reduction plan, track the current risk reduction status, organize risks by reference configuration system, subsystem, and component (SSC) and Area, and increase the level of NGNP decision making.

Bibliographical database of radiation biological dosimetry and risk assessment: Part 2

International Nuclear Information System (INIS)

Straume, T.; Ricker, Y.; Thut, M.

1990-09-01

This is part 11 of a database constructed to support research in radiation biological dosimetry and risk assessment. Relevant publications were identified through detailed searches of national and international electronic databases and through our personal knowledge of the subject. Publications were numbered and key worded, and referenced in an electronic data-retrieval system that permits quick access through computerized searches on authors, key words, title, year, journal name, or publication number. Photocopies of the publications contained in the database are maintained in a file that is numerically arranged by our publication acquisition numbers. This volume contains 1048 additional entries, which are listed in alphabetical order by author. The computer software used for the database is a simple but sophisticated relational database program that permits quick information access, high flexibility, and the creation of customized reports. This program is inexpensive and is commercially available for the Macintosh and the IBM PC. Although the database entries were made using a Macintosh computer, we have the capability to convert the files into the IBM PC version. As of this date, the database cites 2260 publications. Citations in the database are from 200 different scientific journals. There are also references to 80 books and published symposia, and 158 reports. Information relevant to radiation biological dosimetry and risk assessment is widely distributed within the scientific literature, although a few journals clearly predominate. The journals publishing the largest number of relevant papers are Health Physics, with a total of 242 citations in the database, and Mutation Research, with 185 citations. Other journals with over 100 citations in the database, are Radiation Research, with 136, and International Journal of Radiation Biology, with 132

47 CFR 69.120 - Line information database.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Line information database. 69.120 Section 69...) ACCESS CHARGES Computation of Charges § 69.120 Line information database. (a) A charge that is expressed... from a local exchange carrier database to recover the costs of: (1) The transmission facilities between...

Spatial interactions database development for effective probabilistic risk assessment

International Nuclear Information System (INIS)

Liming, J. K.; Dunn, R. F.

2008-01-01

In preparation for a subsequent probabilistic risk assessment (PRA) fire risk analysis update, the STP Nuclear Operating Company (STPNOC) is updating its spatial interactions database (SID). This work is being performed to support updating the spatial interactions analysis (SIA) initially performed for the original South Texas Project Electric Generating Station (STPEGS) probabilistic safely assessment (PSA) and updated in the STPEGS Level 2 PSA and IPE Report. S/A is a large-scope screening analysis performed for nuclear power plant PRA that serves as a prerequisite basis for more detailed location-dependent, hazard-spec analyses in the PRA, such as fire risk analysis, flooding risk analysis, etc. SIA is required to support the 'completeness' argument for the PRA scope. The objectives of the current SID development effort are to update the spatial interactions analysis data, to the greatest degree practical, to be consistent with the following: the as-built plant as of December 31, 2007 the in-effect STPNOC STPEGS Units 1 and 2 PRA the current technology and intent of NUREG/CR-6850 guidance for lire risk analysis database support the requirements for PRA SIA, including fire and flooding risk analysis, established by NRC Regulatory Guide 1.200 and the ASME PRA Standard (ASME RA-S-2002 updated through ASME RA-Sc-2007,) This paper presents the approach and methodology for state-of-the-art SID development and applications, including an overview of the SIA process for nuclear power plant PRA. The paper shows how current relational database technology and existing, conventional station information sources can be employed to collect, process, and analyze spatial interactions data for the plant in an effective and efficient manner to meet the often challenging requirements of industry guidelines and standards such as NUREG/CR-6850, NRC Regulatory Guide 1.200, and ASME RA-S-2002 (updated through ASME RA-Sc 2007). This paper includes tables and figures illustrating how SIA

Nuclear Criticality Information System. Database examples

Energy Technology Data Exchange (ETDEWEB)

Foret, C.A.

1984-06-01

The purpose of this publication is to provide our users with a guide to using the Nuclear Criticality Information System (NCIS). It is comprised of an introduction, an information and resources section, a how-to-use section, and several useful appendices. The main objective of this report is to present a clear picture of the NCIS project and its available resources as well as assisting our users in accessing the database and using the TIS computer to process data. The introduction gives a brief description of the NCIS project, the Technology Information System (TIS), online user information, future plans and lists individuals to contact for additional information about the NCIS project. The information and resources section outlines the NCIS database and describes the resources that are available. The how-to-use section illustrates access to the NCIS database as well as searching datafiles for general or specific data. It also shows how to access and read the NCIS news section as well as connecting to other information centers through the TIS computer.

Nuclear Criticality Information System. Database examples

International Nuclear Information System (INIS)

Foret, C.A.

1984-06-01

The purpose of this publication is to provide our users with a guide to using the Nuclear Criticality Information System (NCIS). It is comprised of an introduction, an information and resources section, a how-to-use section, and several useful appendices. The main objective of this report is to present a clear picture of the NCIS project and its available resources as well as assisting our users in accessing the database and using the TIS computer to process data. The introduction gives a brief description of the NCIS project, the Technology Information System (TIS), online user information, future plans and lists individuals to contact for additional information about the NCIS project. The information and resources section outlines the NCIS database and describes the resources that are available. The how-to-use section illustrates access to the NCIS database as well as searching datafiles for general or specific data. It also shows how to access and read the NCIS news section as well as connecting to other information centers through the TIS computer

A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution

Directory of Open Access Journals (Sweden)

Marc Wieland

2017-04-01

Full Text Available With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout the different phases of risk management reaching from pre-disaster mitigation to the response after an event and the long-term recovery of affected assets. Spatio-temporal changes need to be integrated into a sound conceptual and technological framework able to deal with data coming from different sources, at varying scales, and changing in space and time. Especially managing the information life-cycle, the integration of heterogeneous information and the distributed versioning and release of geospatial information are important topics that need to become essential parts of modern exposure modelling solutions. The main purpose of this study is to provide a conceptual and technological framework to tackle the requirements implied by disaster risk management for describing exposed assets in space and time. An information life-cycle management solution is proposed, based on a relational spatio-temporal database model coupled with Git and GeoGig repositories for distributed versioning. Two application scenarios focusing on the modelling of residential building stocks are presented to show the capabilities of the implemented solution. A prototype database model is shared on GitHub along with the necessary scenario data.

Discovering new information in bibliographic databases

Directory of Open Access Journals (Sweden)

Emil Hudomalj

2005-01-01

Full Text Available Databases contain information that can usually not be revealed by standard query systems. For that purpose, the methods for knowledge discovery from databases can be applied, which enable the user to browse aggregated data, discover trends, produce online reports, explore possible new associations within the data etc. Such methods are successfully employed in various fields, such as banking, insurance and telecommunications, while they are seldom used in libraries. The article reviews the development of query systems for bibliographic databases, including some early attempts to apply modern knowledge discovery methods. Analytical databases are described in more detail, since they usually serve as the basis for knowledge discovery. Data mining approaches are presented, since they are a central step in the knowledge discovery process. The key role of librarians who can play a key part in developing systems for finding new information in existing bibliographic databases is stressed.

Selection of nuclear power information database management system

International Nuclear Information System (INIS)

Zhang Shuxin; Wu Jianlei

1996-01-01

In the condition of the present database technology, in order to build the Chinese nuclear power information database (NPIDB) in the nuclear industry system efficiently at a high starting point, an important task is to select a proper database management system (DBMS), which is the hinge of the matter to build the database successfully. Therefore, this article explains how to build a practical information database about nuclear power, the functions of different database management systems, the reason of selecting relation database management system (RDBMS), the principles of selecting RDBMS, the recommendation of ORACLE management system as the software to build database and so on

Risk assessment and toxicology databases for health effects assessment

Energy Technology Data Exchange (ETDEWEB)

Lu, P.Y.; Wassom, J.S. [Oak Ridge National Laboratory, TN (United States)

1990-12-31

Scientific and technological developments bring unprecedented stress to our environment. Society has to predict the results of potential health risks from technologically based actions that may have serious, far-reaching consequences. The potential for error in making such predictions or assessment is great and multiplies with the increasing size and complexity of the problem being studied. Because of this, the availability and use of reliable data is the key to any successful forecasting effort. Scientific research and development generate new data and information. Much of the scientific data being produced daily is stored in computers for subsequent analysis. This situation provides both an invaluable resource and an enormous challenge. With large amounts of government funds being devoted to health and environmental research programs and with maintenance of our living environment at stake, we must make maximum use of the resulting data to forecast and avert catastrophic effects. Along with the readily available. The most efficient means of obtaining the data necessary for assessing the health effects of chemicals is to utilize applications include the toxicology databases and information files developed at ORNL. To make most efficient use of the data/information that has already been prepared, attention and resources should be directed toward projects that meticulously evaluate the available data/information and create specialized peer-reviewed value-added databases. Such projects include the National Library of Medicine`s Hazardous Substances Data Bank, and the U.S. Air Force Installation Restoration Toxicology Guide. These and similar value-added toxicology databases were developed at ORNL and are being maintained and updated. These databases and supporting information files, as well as some data evaluation techniques are discussed in this paper with special focus on how they are used to assess potential health effects of environmental agents. 19 refs., 5 tabs.

Creating databases for biological information: an introduction.

Science.gov (United States)

Stein, Lincoln

2013-06-01

The essence of bioinformatics is dealing with large quantities of information. Whether it be sequencing data, microarray data files, mass spectrometric data (e.g., fingerprints), the catalog of strains arising from an insertional mutagenesis project, or even large numbers of PDF files, there inevitably comes a time when the information can simply no longer be managed with files and directories. This is where databases come into play. This unit briefly reviews the characteristics of several database management systems, including flat file, indexed file, relational databases, and NoSQL databases. It compares their strengths and weaknesses and offers some general guidelines for selecting an appropriate database management system. Copyright 2013 by JohnWiley & Sons, Inc.

Saccharomyces genome database informs human biology

OpenAIRE

Skrzypek, Marek S; Nash, Robert S; Wong, Edith D; MacPherson, Kevin A; Hellerstedt, Sage T; Engel, Stacia R; Karra, Kalpana; Weng, Shuai; Sheppard, Travis K; Binkley, Gail; Simison, Matt; Miyasato, Stuart R; Cherry, J Michael

2017-01-01

Abstract The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is an expertly curated database of literature-derived functional information for the model organism budding yeast, Saccharomyces cerevisiae. SGD constantly strives to synergize new types of experimental data and bioinformatics predictions with existing data, and to organize them into a comprehensive and up-to-date information resource. The primary mission of SGD is to facilitate research into the biology of yeast and...

A database to manage flood risk in Catalonia

Science.gov (United States)

Echeverria, S.; Toldrà, R.; Verdaguer, I.

2009-09-01

We call priority action spots those local sites where heavy rain, increased river flow, sea storms and other flooding phenomena can cause human casualties or severe damage to property. Some examples are campsites, car parks, roads, chemical factories… In order to keep to a minimum the risk of these spots, both a prevention programme and an emergency response programme are required. The flood emergency plan of Catalonia (INUNCAT) prepared in 2005 included already a listing of priority action spots compiled by the Catalan Water Agency (ACA), which was elaborated taking into account past experience, hydraulic studies and information available by several knowledgeable sources. However, since land use evolves with time this listing of priority action spots has become outdated and incomplete. A new database is being built. Not only does this new database update and expand the previous listing, but adds to each entry information regarding prevention measures and emergency response: which spots are the most hazardous, under which weather conditions problems arise, which ones should have their access closed as soon as these conditions are forecast or actually given, which ones should be evacuated, who is in charge of the preventive actions or emergency response and so on. Carrying out this programme has to be done with the help and collaboration of all the organizations involved, foremost with the local authorities in the areas at risk. In order to achieve this goal a suitable geographical information system is necessary which can be easily used by all actors involved in this project. The best option has turned out to be the Spatial Data Infrastructure of Catalonia (IDEC), a platform to share spatial data on the Internet involving the Generalitat de Catalunya, Localret (a consortium of local authorities that promotes information technology) and other institutions.

Content-Based Information Retrieval from Forensic Databases

NARCIS (Netherlands)

Geradts, Z.J.M.H.

2002-01-01

In forensic science, the number of image databases is growing rapidly. For this reason, it is necessary to have a proper procedure for searching in these images databases based on content. The use of image databases results in more solved crimes; furthermore, statistical information can be obtained

Database for the degradation risk assessment of groundwater resources (Southern Italy)

Science.gov (United States)

Polemio, M.; Dragone, V.; Mitolo, D.

2003-04-01

The risk characterisation of quality degradation and availability lowering of groundwater resources has been pursued for a wide coastal plain (Basilicata region, Southern Italy), an area covering 40 km along the Ionian Sea and 10 km inland. The quality degradation is due two phenomena: pollution due to discharge of waste water (coming from urban areas) and due to salt pollution, related to seawater intrusion but not only. The availability lowering is due to overexploitation but also due to drought effects. To this purpose the historical data of 1,130 wells have been collected. Wells, homogenously distributed in the area, were the source of geological, stratigraphical, hydrogeological, geochemical data. In order to manage space-related information via a GIS, a database system has been devised to encompass all the surveyed wells and the body of information available per well. Geo-databases were designed to comprise the four types of data collected: a database including geometrical, geological and hydrogeological data on wells (WDB), a database devoted to chemical and physical data on groundwater (CDB), a database including the geotechnical parameters (GDB), a database concering piezometric and hydrological (rainfall, air temperature, river discharge) data (HDB). The record pertaining to each well is identified in these databases by the progressive number of the well itself. Every database is designed as follows: a) the HDB contains 1,158 records, 28 of and 31 fields, mainly describing the geometry of the well and of the stratigraphy; b) the CDB encompasses data about 157 wells, based on which the chemical and physical analyses of groundwater have been carried out. More than one record has been associated with these 157 wells, due to periodic monitoring and analysis; c) the GDB covers 61 wells to which the geotechnical parameters obtained by soil samples taken at various depths; the HDB is designed to permit the analysis of long time series (from 1918) of piezometric

A new Volcanic managEment Risk Database desIgn (VERDI): Application to El Hierro Island (Canary Islands)

Science.gov (United States)

Bartolini, S.; Becerril, L.; Martí, J.

2014-11-01

One of the most important issues in modern volcanology is the assessment of volcanic risk, which will depend - among other factors - on both the quantity and quality of the available data and an optimum storage mechanism. This will require the design of purpose-built databases that take into account data format and availability and afford easy data storage and sharing, and will provide for a more complete risk assessment that combines different analyses but avoids any duplication of information. Data contained in any such database should facilitate spatial and temporal analysis that will (1) produce probabilistic hazard models for future vent opening, (2) simulate volcanic hazards and (3) assess their socio-economic impact. We describe the design of a new spatial database structure, VERDI (Volcanic managEment Risk Database desIgn), which allows different types of data, including geological, volcanological, meteorological, monitoring and socio-economic information, to be manipulated, organized and managed. The root of the question is to ensure that VERDI will serve as a tool for connecting different kinds of data sources, GIS platforms and modeling applications. We present an overview of the database design, its components and the attributes that play an important role in the database model. The potential of the VERDI structure and the possibilities it offers in regard to data organization are here shown through its application on El Hierro (Canary Islands). The VERDI database will provide scientists and decision makers with a useful tool that will assist to conduct volcanic risk assessment and management.

Use of national clinical databases for informing and for evaluating health care policies.

Science.gov (United States)

Black, Nick; Tan, Stefanie

2013-02-01

Policy-makers and analysts could make use of national clinical databases either to inform or to evaluate meso-level (organisation and delivery of health care) and macro-level (national) policies. Reviewing the use of 15 of the best established databases in England, we identify and describe four published examples of each use. These show that policy-makers can either make use of the data itself or of research based on the database. For evaluating policies, the major advantages are the huge sample sizes available, the generalisability of the data, its immediate availability and historic information. The principal methodological challenges involve the need for risk adjustment and time-series analysis. Given their usefulness in the policy arena, there are several reasons why national clinical databases have not been used more, some due to a lack of 'push' by their custodians and some to the lack of 'pull' by policy-makers. Greater exploitation of these valuable resources would be facilitated by policy-makers' and custodians' increased awareness, minimisation of legal restrictions on data use, improvements in the quality of databases and a library of examples of applications to policy. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Advanced approaches to intelligent information and database systems

CERN Document Server

Boonjing, Veera; Chittayasothorn, Suphamit

2014-01-01

This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis, and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications, and multimedia systems methods and applications. The book will be interesting for both practitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced ...

Ten Years Experience In Geo-Databases For Linear Facilities Risk Assessment (Lfra)

Science.gov (United States)

Oboni, F.

2003-04-01

Keywords: geo-environmental, database, ISO14000, management, decision-making, risk, pipelines, roads, railroads, loss control, SAR, hazard identification ABSTRACT: During the past decades, characterized by the development of the Risk Management (RM) culture, a variety of different RM models have been proposed by governmental agencies in various parts of the world. The most structured models appear to have originated in the field of environmental RM. These models are briefly reviewed in the first section of the paper focusing the attention on the difference between Hazard Management and Risk Management and the need to use databases in order to allow retrieval of specific information and effective updating. The core of the paper reviews a number of different RM approaches, based on extensions of geo-databases, specifically developed for linear facilities (LF) in transportation corridors since the early 90s in Switzerland, Italy, Canada, the US and South America. The applications are compared in terms of methodology, capabilities and resources necessary to their implementation. The paper then focuses the attention on the level of detail that applications and related data have to attain. Common pitfalls related to decision making based on hazards rather than on risks are discussed. The paper focuses the last sections on the description of the next generation of linear facility RA application, including examples of results and discussion of future methodological research. It is shown that geo-databases should be linked to loss control and accident reports in order to maximize their benefits. The links between RA and ISO 14000 (environmental management code) are explicitly considered.

DOE technology information management system database study report

Energy Technology Data Exchange (ETDEWEB)

Widing, M.A.; Blodgett, D.W.; Braun, M.D.; Jusko, M.J.; Keisler, J.M.; Love, R.J.; Robinson, G.L. [Argonne National Lab., IL (United States). Decision and Information Sciences Div.

1994-11-01

To support the missions of the US Department of Energy (DOE) Special Technologies Program, Argonne National Laboratory is defining the requirements for an automated software system that will search electronic databases on technology. This report examines the work done and results to date. Argonne studied existing commercial and government sources of technology databases in five general areas: on-line services, patent database sources, government sources, aerospace technology sources, and general technology sources. First, it conducted a preliminary investigation of these sources to obtain information on the content, cost, frequency of updates, and other aspects of their databases. The Laboratory then performed detailed examinations of at least one source in each area. On this basis, Argonne recommended which databases should be incorporated in DOE`s Technology Information Management System.

Status report on nuclear power - information from STN databases

International Nuclear Information System (INIS)

Prinz, H.

1995-01-01

The worldwide future of nuclear power as seen about 25 years ago is presented based on a literature search in the INIS database. The role of nuclear power today, after TMI and Chernobyl, in energy supplies and in combating the greehouse effect is evaluated by literature searches in STN databases (e.g. INIS, ETDE, COMPENDEX, CA, ULIDAT, INSPEC). An evaluation is given of the different information contents of bibliographic databases such as INIS and pure information databases such as NLDB. (orig./HP)

Informational database methodology for urban risk analysis.Case study: the historic centre of Bucharest

Science.gov (United States)

Armas, I.; Dumitrascu, S.

2009-04-01

, but is also a very populated area, this being factors that favour a high susceptibility level. In addition, the majority of the buildings are included in the first and second categories of seismic risk, being built between 1875 and 1940, the age of the buildings establishing an increased vulnerability to natural hazards. The methodology was developed through the contribution of three partner universities from Bucharest: the University of Bucharest, the Academy for Economic Studies and the Technical University of Constructions. The method suggested was based on the analysis and processing of digital and statistical spatial information resulted from 1:500 topographical plans, satellite pictures, archives and historical maps used for the identification of the age of the buildings. Also, an important stage was represented by the field investigations that resulted with the data used in the assessment of the buildings: year of construction, location and vicinity, height, number of floors, state and function of the building, equipment and construction type. The information collected from the field together with the data resulted from the digitization of the ortophotoplans were inserted in ArcGIS in order to compile the database. Furthermore, the team from the Cybernetics Faculty developed a special software package in Visual Studio and SQL server in order to insert the sheets in GIS so that they could be statistically processed. The final product of the study is a program that includes as main functions editing, the analysis based on selected factors (individual or group) and viewing of building information in the shape of maps or 3D visualization. The strengths of the informational system resulted are given by the extended range of applicability, the short processing period, accessibility, capacity of support for a large amount of information and, thus, standing out as an adequate instrument to fit the needs of a susceptible population.

A New Breed of Database System: Volcano Global Risk Identification and Analysis Project (VOGRIPA)

Science.gov (United States)

Crosweller, H. S.; Sparks, R. S.; Siebert, L.

2009-12-01

VOGRIPA originated as part of the Global Risk Identification Programme (GRIP) that is being co-ordinated from the Earth Institute of Columbia University under the auspices of the United Nations and World Bank. GRIP is a five-year programme aiming at improving global knowledge about risk from natural hazards and is part of the international response to the catastrophic 2004 Asian tsunami. VOGRIPA is also a formal IAVCEI project. The objectives of VOGRIPA are to create a global database of volcanic activity, hazards and vulnerability information that can be analysed to identify locations at high risk from volcanism, gaps in knowledge about hazards and risk, and will allow scientists and disaster managers at specific locations to analyse risk within a global context of systematic information. It is this added scope of risk and vulnerability as well as hazard which sets VOGRIPA apart from most previous databases. The University of Bristol is the central coordinating centre for the project, which is an international partnership including the Smithsonian Institution, the Geological Survey of Japan, the Earth Observatory of Singapore (Chris Newhall), the British Geological Survey, the University of Buffalo (SUNY) and Munich Re. The partnership is intended to grow and any individuals or institutions who are able to contribute resources to VOGRIPA objectives are welcome to participate. Work has already begun (funded principally by Munich Re) on populating a database of large magnitude explosive eruptions reaching back to the Quaternary, with extreme-value statistics being used to evaluate the magnitude-frequency relationship of such events, and also an assessment of how the quality of records affect the results. The following 4 years of funding from the European Research Council for VOGRIPA will be used to establish further international collaborations in order to develop different aspects of the database, with the data being accessible online once it is sufficiently

ANALYTICAL ISSUES OF RISK COMMUNICATION. RATIONALE FOR APPROACHES TO DEVELOPING RESEARCH DATABASES ON RADIATION SAFETY AND SOCIAL RISKS

Directory of Open Access Journals (Sweden)

L. S. Rekhtina

2017-01-01

Full Text Available One of the important stages of risk communication is the analysis of publications in traditional media and the Internet, which largely shape people’s attitudes to various issues. At the same time, the availability of large amounts of information relating to any subject area complicates the possibility of manual analysis and adequate description of all of the information. On the other hand, the availability of information causes the urgency of developing methods to improve the effectiveness of its analysis. One way to automate the analysis of large amounts of information is the development of databases or automated information systems containing information materials on the subject matter under study and suggesting the possibility of automated processing. The objective of this work is to analyze the experience of developing such systems and databases by the research teams of the St. Petersburg Institute of Radiation Hygiene and St. Petersburg State University and to identify key features of the use of bases Data for social research. The results of the analysis showed that the methodological approaches used were very close. The analysis is performed according to the method of autoethnographical research. The strategy application of the comparative analysis allows identifying common features characterizing the situation of development and implementation of databases to practice of the risk communication studies. The article discusses the features associated with them, the limitations of the primary data, such as text, discursive nature of most of the materials, information noise, high dependence on context, variability, different structure, format and appearance of materials. The important parameters for solving problems of the qualitative and quantitative analysis are given in the article. An important condition of creating effective, from the point of view of socio-communication studies information system is to implement the processing

Building Inventory Database on the Urban Scale Using GIS for Earthquake Risk Assessment

Science.gov (United States)

Kaplan, O.; Avdan, U.; Guney, Y.; Helvaci, C.

2016-12-01

The majority of the existing buildings are not safe against earthquakes in most of the developing countries. Before a devastating earthquake, existing buildings need to be assessed and the vulnerable ones must be determined. Determining the seismic performance of existing buildings which is usually made with collecting the attributes of existing buildings, making the analysis and the necessary queries, and producing the result maps is very hard and complicated procedure that can be simplified with Geographic Information System (GIS). The aim of this study is to produce a building inventory database using GIS for assessing the earthquake risk of existing buildings. In this paper, a building inventory database for 310 buildings, located in Eskisehir, Turkey, was produced in order to assess the earthquake risk of the buildings. The results from this study show that 26% of the buildings have high earthquake risk, 33% of the buildings have medium earthquake risk and the 41% of the buildings have low earthquake risk. The produced building inventory database can be very useful especially for governments in dealing with the problem of determining seismically vulnerable buildings in the large existing building stocks. With the help of this kind of methods, determination of the buildings, which may collapse and cause life and property loss during a possible future earthquake, will be very quick, cheap and reliable.

Audit Database and Information Tracking System

Data.gov (United States)

Social Security Administration — This database contains information about the Social Security Administration's audits regarding SSA agency performance and compliance. These audits can be requested...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLUMBIA COUNTY, WISCONSIN, USA - MIP Columbia Portion Baraboo River Watershed RiskMap DFIRM Update

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk;...

Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources

Directory of Open Access Journals (Sweden)

A Mitnitski

2003-01-01

Full Text Available To better understand information about human health from databases we analyzed three datasets collected for different purposes in Canada: a biomedical database of older adults, a large population survey across all adult ages, and vital statistics. Redundancy in the variables was established, and this led us to derive a generalized (macroscopic state variable, being a fitness/frailty index that reflects both individual and group health status. Evaluation of the relationship between fitness/frailty and the mortality rate revealed that the latter could be expressed in terms of variables generally available from any cross-sectional database. In practical terms, this means that the risk of mortality might readily be assessed from standard biomedical appraisals collected for other purposes.

Development of technical information database for high level waste disposal

International Nuclear Information System (INIS)

Kudo, Koji; Takada, Susumu; Kawanishi, Motoi

2005-01-01

A concept design of the high level waste disposal information database and the disposal technologies information database are explained. The high level waste disposal information database contains information on technologies, waste, management and rules, R and D, each step of disposal site selection, characteristics of sites, demonstration of disposal technology, design of disposal site, application for disposal permit, construction of disposal site, operation and closing. Construction of the disposal technologies information system and the geological disposal technologies information system is described. The screen image of the geological disposal technologies information system is shown. User is able to search the full text retrieval and attribute retrieval in the image. (S.Y. )

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DODGE COUNTY, WISCONSIN, USA - MIP Dodge Portion Upper Rock River Watershed RiskMap DFIRM Update

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk;...

Databases applicable to quantitative hazard/risk assessment-Towards a predictive systems toxicology

International Nuclear Information System (INIS)

Waters, Michael; Jackson, Marcus

2008-01-01

The Workshop on The Power of Aggregated Toxicity Data addressed the requirement for distributed databases to support quantitative hazard and risk assessment. The authors have conceived and constructed with federal support several databases that have been used in hazard identification and risk assessment. The first of these databases, the EPA Gene-Tox Database was developed for the EPA Office of Toxic Substances by the Oak Ridge National Laboratory, and is currently hosted by the National Library of Medicine. This public resource is based on the collaborative evaluation, by government, academia, and industry, of short-term tests for the detection of mutagens and presumptive carcinogens. The two-phased evaluation process resulted in more than 50 peer-reviewed publications on test system performance and a qualitative database on thousands of chemicals. Subsequently, the graphic and quantitative EPA/IARC Genetic Activity Profile (GAP) Database was developed in collaboration with the International Agency for Research on Cancer (IARC). A chemical database driven by consideration of the lowest effective dose, GAP has served IARC for many years in support of hazard classification of potential human carcinogens. The Toxicological Activity Profile (TAP) prototype database was patterned after GAP and utilized acute, subchronic, and chronic data from the Office of Air Quality Planning and Standards. TAP demonstrated the flexibility of the GAP format for air toxics, water pollutants and other environmental agents. The GAP format was also applied to developmental toxicants and was modified to represent quantitative results from the rodent carcinogen bioassay. More recently, the authors have constructed: 1) the NIEHS Genetic Alterations in Cancer (GAC) Database which quantifies specific mutations found in cancers induced by environmental agents, and 2) the NIEHS Chemical Effects in Biological Systems (CEBS) Knowledgebase that integrates genomic and other biological data including

Design and Establishment of Quality Model of Fundamental Geographic Information Database

Science.gov (United States)

Ma, W.; Zhang, J.; Zhao, Y.; Zhang, P.; Dang, Y.; Zhao, T.

2018-04-01

In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

Report on the basic design of the FY 1998 technical information database; 1998 nendo gijutsu joho database no kihon sekkei hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-03-01

For the purpose of promoting the effective transfer of the results of technical development and the technical information distribution, study and basic design were conducted of a concept of the new technical database run by NEDO. In the study, the following were conducted to extract the subjects: analysis of examples of project databases such as CADDET, scientific technology research information (JCLEARING), evaluation/survey of the present situation of database users, etc. In the study of a concept of technical information database, clarified were the classification of information, definition of the details, finding-out of relations between various kinds of information, mechanism of collection/processing/storage/dispatch/exchange of information, role of NEDO, etc. In the basic design, as the NEDO technical information database viable for the moment, the rough design was conducted of the project information, information on result reports, and information on research institutes. Further, to handle in unity the database controlled in different method, studied were the applicability to the project database of the general combined concept, advantages, restricted items, etc. (NEDO)

48 CFR 804.1102 - Vendor Information Pages (VIP) Database.

Science.gov (United States)

2010-10-01

... (VIP) Database. 804.1102 Section 804.1102 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS GENERAL ADMINISTRATIVE MATTERS Contract Execution 804.1102 Vendor Information Pages (VIP) Database. Prior to January 1, 2012, all VOSBs and SDVOSBs must be listed in the VIP database, available at http...

Overview of the plant risk status information management system

International Nuclear Information System (INIS)

Kirchner, J.R.; Campbell, D.J.

1987-01-01

The Plant Risk Status Information Management System (PRISIM) is a personal computer program that presents PRA results and related information for use by decision-makers. The program was originally developed for NRC inspectors, but now an expanded version of the program with more potential applications is complete. Prototypes of both versions have been developed for Arkansas Nuclear One - Unit 1, and the inspection-related version is currently being field-tested. Interim results of these field tests are favorable. The PRISIM database contains both pre-processed information that is useful for long-term planning and a plant risk model for assessing the risk implications of the current plant status. The program provides rapid access to specific information by making extensive use of menus. Development of PRISIM programs for Peach Bottom-Unit 2 is underway, and there are plans to create programs for other plants

Bibliographical database of radiation biological dosimetry and risk assessment: Part 1, through June 1988

Energy Technology Data Exchange (ETDEWEB)

Straume, T.; Ricker, Y.; Thut, M.

1988-08-29

This database was constructed to support research in radiation biological dosimetry and risk assessment. Relevant publications were identified through detailed searches of national and international electronic databases and through our personal knowledge of the subject. Publications were numbered and key worded, and referenced in an electronic data-retrieval system that permits quick access through computerized searches on publication number, authors, key words, title, year, and journal name. Photocopies of all publications contained in the database are maintained in a file that is numerically arranged by citation number. This report of the database is provided as a useful reference and overview. It should be emphasized that the database will grow as new citations are added to it. With that in mind, we arranged this report in order of ascending citation number so that follow-up reports will simply extend this document. The database cite 1212 publications. Publications are from 119 different scientific journals, 27 of these journals are cited at least 5 times. It also contains reference to 42 books and published symposia, and 129 reports. Information relevant to radiation biological dosimetry and risk assessment is widely distributed among the scientific literature, although a few journals clearly dominate. The four journals publishing the largest number of relevant papers are Health Physics, Mutation Research, Radiation Research, and International Journal of Radiation Biology. Publications in Health Physics make up almost 10% of the current database.

Bibliographical database of radiation biological dosimetry and risk assessment: Part 1, through June 1988

International Nuclear Information System (INIS)

Straume, T.; Ricker, Y.; Thut, M.

1988-01-01

This database was constructed to support research in radiation biological dosimetry and risk assessment. Relevant publications were identified through detailed searches of national and international electronic databases and through our personal knowledge of the subject. Publications were numbered and key worded, and referenced in an electronic data-retrieval system that permits quick access through computerized searches on publication number, authors, key words, title, year, and journal name. Photocopies of all publications contained in the database are maintained in a file that is numerically arranged by citation number. This report of the database is provided as a useful reference and overview. It should be emphasized that the database will grow as new citations are added to it. With that in mind, we arranged this report in order of ascending citation number so that follow-up reports will simply extend this document. The database cite 1212 publications. Publications are from 119 different scientific journals, 27 of these journals are cited at least 5 times. It also contains reference to 42 books and published symposia, and 129 reports. Information relevant to radiation biological dosimetry and risk assessment is widely distributed among the scientific literature, although a few journals clearly dominate. The four journals publishing the largest number of relevant papers are Health Physics, Mutation Research, Radiation Research, and International Journal of Radiation Biology. Publications in Health Physics make up almost 10% of the current database

Repetitive Bibliographical Information in Relational Databases.

Science.gov (United States)

Brooks, Terrence A.

1988-01-01

Proposes a solution to the problem of loading repetitive bibliographic information in a microcomputer-based relational database management system. The alternative design described is based on a representational redundancy design and normalization theory. (12 references) (Author/CLB)

Database structure and file layout of Nuclear Power Plant Database. Database for design information on Light Water Reactors in Japan

International Nuclear Information System (INIS)

Yamamoto, Nobuo; Izumi, Fumio.

1995-12-01

The Nuclear Power Plant Database (PPD) has been developed at the Japan Atomic Energy Research Institute (JAERI) to provide plant design information on domestic Light Water Reactors (LWRs) to be used for nuclear safety research and so forth. This database can run on the main frame computer in the JAERI Tokai Establishment. The PPD contains the information on the plant design concepts, the numbers, capacities, materials, structures and types of equipment and components, etc, based on the safety analysis reports of the domestic LWRs. This report describes the details of the PPD focusing on the database structure and layout of data files so that the users can utilize it efficiently. (author)

Fish Karyome: A karyological information network database of Indian Fishes.

Science.gov (United States)

Nagpure, Naresh Sahebrao; Pathak, Ajey Kumar; Pati, Rameshwar; Singh, Shri Prakash; Singh, Mahender; Sarkar, Uttam Kumar; Kushwaha, Basdeo; Kumar, Ravindra

2012-01-01

'Fish Karyome', a database on karyological information of Indian fishes have been developed that serves as central source for karyotype data about Indian fishes compiled from the published literature. Fish Karyome has been intended to serve as a liaison tool for the researchers and contains karyological information about 171 out of 2438 finfish species reported in India and is publically available via World Wide Web. The database provides information on chromosome number, morphology, sex chromosomes, karyotype formula and cytogenetic markers etc. Additionally, it also provides the phenotypic information that includes species name, its classification, and locality of sample collection, common name, local name, sex, geographical distribution, and IUCN Red list status. Besides, fish and karyotype images, references for 171 finfish species have been included in the database. Fish Karyome has been developed using SQL Server 2008, a relational database management system, Microsoft's ASP.NET-2008 and Macromedia's FLASH Technology under Windows 7 operating environment. The system also enables users to input new information and images into the database, search and view the information and images of interest using various search options. Fish Karyome has wide range of applications in species characterization and identification, sex determination, chromosomal mapping, karyo-evolution and systematics of fishes.

Information persistence using XML database technology

Science.gov (United States)

Clark, Thomas A.; Lipa, Brian E. G.; Macera, Anthony R.; Staskevich, Gennady R.

2005-05-01

The Joint Battlespace Infosphere (JBI) Information Management (IM) services provide information exchange and persistence capabilities that support tailored, dynamic, and timely access to required information, enabling near real-time planning, control, and execution for DoD decision making. JBI IM services will be built on a substrate of network centric core enterprise services and when transitioned, will establish an interoperable information space that aggregates, integrates, fuses, and intelligently disseminates relevant information to support effective warfighter business processes. This virtual information space provides individual users with information tailored to their specific functional responsibilities and provides a highly tailored repository of, or access to, information that is designed to support a specific Community of Interest (COI), geographic area or mission. Critical to effective operation of JBI IM services is the implementation of repositories, where data, represented as information, is represented and persisted for quick and easy retrieval. This paper will address information representation, persistence and retrieval using existing database technologies to manage structured data in Extensible Markup Language (XML) format as well as unstructured data in an IM services-oriented environment. Three basic categories of database technologies will be compared and contrasted: Relational, XML-Enabled, and Native XML. These technologies have diverse properties such as maturity, performance, query language specifications, indexing, and retrieval methods. We will describe our application of these evolving technologies within the context of a JBI Reference Implementation (RI) by providing some hopefully insightful anecdotes and lessons learned along the way. This paper will also outline future directions, promising technologies and emerging COTS products that can offer more powerful information management representations, better persistence mechanisms and

NABIC marker database: A molecular markers information network of agricultural crops.

Science.gov (United States)

Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

2013-01-01

In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

Breach Risk Magnitude: A Quantitative Measure of Database Security.

Science.gov (United States)

Yasnoff, William A

2016-01-01

A quantitative methodology is described that provides objective evaluation of the potential for health record system breaches. It assumes that breach risk increases with the number of potential records that could be exposed, while it decreases when more authentication steps are required for access. The breach risk magnitude (BRM) is the maximum value for any system user of the common logarithm of the number of accessible database records divided by the number of authentication steps needed to achieve such access. For a one million record relational database, the BRM varies from 5.52 to 6 depending on authentication protocols. For an alternative data architecture designed specifically to increase security by separately storing and encrypting each patient record, the BRM ranges from 1.3 to 2.6. While the BRM only provides a limited quantitative assessment of breach risk, it may be useful to objectively evaluate the security implications of alternative database organization approaches.

The Eruption Forecasting Information System (EFIS) database project

Science.gov (United States)

Ogburn, Sarah; Harpel, Chris; Pesicek, Jeremy; Wellik, Jay; Pallister, John; Wright, Heather

2016-04-01

The Eruption Forecasting Information System (EFIS) project is a new initiative of the U.S. Geological Survey-USAID Volcano Disaster Assistance Program (VDAP) with the goal of enhancing VDAP's ability to forecast the outcome of volcanic unrest. The EFIS project seeks to: (1) Move away from relying on the collective memory to probability estimation using databases (2) Create databases useful for pattern recognition and for answering common VDAP questions; e.g. how commonly does unrest lead to eruption? how commonly do phreatic eruptions portend magmatic eruptions and what is the range of antecedence times? (3) Create generic probabilistic event trees using global data for different volcano 'types' (4) Create background, volcano-specific, probabilistic event trees for frequently active or particularly hazardous volcanoes in advance of a crisis (5) Quantify and communicate uncertainty in probabilities A major component of the project is the global EFIS relational database, which contains multiple modules designed to aid in the construction of probabilistic event trees and to answer common questions that arise during volcanic crises. The primary module contains chronologies of volcanic unrest, including the timing of phreatic eruptions, column heights, eruptive products, etc. and will be initially populated using chronicles of eruptive activity from Alaskan volcanic eruptions in the GeoDIVA database (Cameron et al. 2013). This database module allows us to query across other global databases such as the WOVOdat database of monitoring data and the Smithsonian Institution's Global Volcanism Program (GVP) database of eruptive histories and volcano information. The EFIS database is in the early stages of development and population; thus, this contribution also serves as a request for feedback from the community.

Development of Information Technology of Object-relational Databases Design

Directory of Open Access Journals (Sweden)

Valentyn A. Filatov

2012-12-01

Full Text Available The article is concerned with the development of information technology of object-relational databases design and study of object features infological and logical database schemes entities and connections.

Risk estimates for hip fracture from clinical and densitometric variables and impact of database selection in Lebanese subjects.

Science.gov (United States)

Badra, Mohammad; Mehio-Sibai, Abla; Zeki Al-Hazzouri, Adina; Abou Naja, Hala; Baliki, Ghassan; Salamoun, Mariana; Afeiche, Nadim; Baddoura, Omar; Bulos, Suhayl; Haidar, Rachid; Lakkis, Suhayl; Musharrafieh, Ramzi; Nsouli, Afif; Taha, Assaad; Tayim, Ahmad; El-Hajj Fuleihan, Ghada

2009-01-01

Bone mineral density (BMD) and fracture incidence vary greatly worldwide. The data, if any, on clinical and densitometric characteristics of patients with hip fractures from the Middle East are scarce. The objective of the study was to define risk estimates from clinical and densitometric variables and the impact of database selection on such estimates. Clinical and densitometric information were obtained in 60 hip fracture patients and 90 controls. Hip fracture subjects were 74 yr (9.4) old, were significantly taller, lighter, and more likely to be taking anxiolytics and sleeping pills than controls. National Health and Nutrition Examination Survey (NHANES) database selection resulted in a higher sensitivity and almost equal specificity in identifying patients with a hip fracture compared with the Lebanese database. The odds ratio (OR) and its confidence interval (CI) for hip fracture per standard deviation (SD) decrease in total hip BMD was 2.1 (1.45-3.05) with the NHANES database, and 2.11 (1.36-2.37) when adjusted for age and body mass index (BMI). Risk estimates were higher in male compared with female subjects. In Lebanese subjects, BMD- and BMI-derived hip fracture risk estimates are comparable to western standards. The study validates the universal use of the NHANES database, and the applicability of BMD- and BMI-derived risk fracture estimates in the World Health Organization (WHO) global fracture risk model, to the Lebanese.

Key Techniques for Dynamic Updating of National Fundamental Geographic Information Database

Directory of Open Access Journals (Sweden)

WANG Donghua

2015-07-01

Full Text Available One of the most important missions of fundamental surveying and mapping work is to keep the fundamental geographic information fresh. In this respect, National Administration of Surveying, Mapping and Geoinformation has launched the project of dynamic updating of national fundamental geographic information database since 2012, which aims to update 1:50 000, 1:250 000 and 1:1 000 000 national fundamental geographic information database continuously and quickly, by updating and publishing once a year. This paper introduces the general technical thinking of dynamic updating, states main technical methods, such as dynamic updating of fundamental database, linkage updating of derived databases, and multi-tense database management and service and so on, and finally introduces main technical characteristics and engineering applications.

7th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2015)

CERN Document Server

Nguyen, Ngoc; Batubara, John; New Trends in Intelligent Information and Database Systems

2015-01-01

Intelligent information and database systems are two closely related subfields of modern computer science which have been known for over thirty years. They focus on the integration of artificial intelligence and classic database technologies to create the class of next generation information systems. The book focuses on new trends in intelligent information and database systems and discusses topics addressed to the foundations and principles of data, information, and knowledge models, methodologies for intelligent information and database systems analysis, design, and implementation, their validation, maintenance and evolution. They cover a broad spectrum of research topics discussed both from the practical and theoretical points of view such as: intelligent information retrieval, natural language processing, semantic web, social networks, machine learning, knowledge discovery, data mining, uncertainty management and reasoning under uncertainty, intelligent optimization techniques in information systems, secu...

A Reaction Database for Small Molecule Pharmaceutical Processes Integrated with Process Information

Directory of Open Access Journals (Sweden)

Emmanouil Papadakis

2017-10-01

Full Text Available This article describes the development of a reaction database with the objective to collect data for multiphase reactions involved in small molecule pharmaceutical processes with a search engine to retrieve necessary data in investigations of reaction-separation schemes, such as the role of organic solvents in reaction performance improvement. The focus of this reaction database is to provide a data rich environment with process information available to assist during the early stage synthesis of pharmaceutical products. The database is structured in terms of reaction classification of reaction types; compounds participating in the reaction; use of organic solvents and their function; information for single step and multistep reactions; target products; reaction conditions and reaction data. Information for reactor scale-up together with information for the separation and other relevant information for each reaction and reference are also available in the database. Additionally, the retrieved information obtained from the database can be evaluated in terms of sustainability using well-known “green” metrics published in the scientific literature. The application of the database is illustrated through the synthesis of ibuprofen, for which data on different reaction pathways have been retrieved from the database and compared using “green” chemistry metrics.

HIERARCHICAL ORGANIZATION OF INFORMATION, IN RELATIONAL DATABASES

Directory of Open Access Journals (Sweden)

Demian Horia

2008-05-01

Full Text Available In this paper I will present different types of representation, of hierarchical information inside a relational database. I also will compare them to find the best organization for specific scenarios.

[Construction of chemical information database based on optical structure recognition technique].

Science.gov (United States)

Lv, C Y; Li, M N; Zhang, L R; Liu, Z M

2018-04-18

To create a protocol that could be used to construct chemical information database from scientific literature quickly and automatically. Scientific literature, patents and technical reports from different chemical disciplines were collected and stored in PDF format as fundamental datasets. Chemical structures were transformed from published documents and images to machine-readable data by using the name conversion technology and optical structure recognition tool CLiDE. In the process of molecular structure information extraction, Markush structures were enumerated into well-defined monomer molecules by means of QueryTools in molecule editor ChemDraw. Document management software EndNote X8 was applied to acquire bibliographical references involving title, author, journal and year of publication. Text mining toolkit ChemDataExtractor was adopted to retrieve information that could be used to populate structured chemical database from figures, tables, and textual paragraphs. After this step, detailed manual revision and annotation were conducted in order to ensure the accuracy and completeness of the data. In addition to the literature data, computing simulation platform Pipeline Pilot 7.5 was utilized to calculate the physical and chemical properties and predict molecular attributes. Furthermore, open database ChEMBL was linked to fetch known bioactivities, such as indications and targets. After information extraction and data expansion, five separate metadata files were generated, including molecular structure data file, molecular information, bibliographical references, predictable attributes and known bioactivities. Canonical simplified molecular input line entry specification as primary key, metadata files were associated through common key nodes including molecular number and PDF number to construct an integrated chemical information database. A reasonable construction protocol of chemical information database was created successfully. A total of 174 research

Information Retrieval in Telemedicine: a Comparative Study on Bibliographic Databases.

Science.gov (United States)

Ahmadi, Maryam; Sarabi, Roghayeh Ershad; Orak, Roohangiz Jamshidi; Bahaadinbeigy, Kambiz

2015-06-01

The first step in each systematic review is selection of the most valid database that can provide the highest number of relevant references. This study was carried out to determine the most suitable database for information retrieval in telemedicine field. Cinhal, PubMed, Web of Science and Scopus databases were searched for telemedicine matched with Education, cost benefit and patient satisfaction. After analysis of the obtained results, the accuracy coefficient, sensitivity, uniqueness and overlap of databases were calculated. The studied databases differed in the number of retrieved articles. PubMed was identified as the most suitable database for retrieving information on the selected topics with the accuracy and sensitivity ratios of 50.7% and 61.4% respectively. The uniqueness percent of retrieved articles ranged from 38% for Pubmed to 3.0% for Cinhal. The highest overlap rate (18.6%) was found between PubMed and Web of Science. Less than 1% of articles have been indexed in all searched databases. PubMed is suggested as the most suitable database for starting search in telemedicine and after PubMed, Scopus and Web of Science can retrieve about 90% of the relevant articles.

2008 Availability and Utilization of Electronic Information Databases ...

African Journals Online (AJOL)

Gbaje E.S

electronic information databases include; research work, to update knowledge in their field of interest and Current awareness. ... be read by a computer device. CD ROMs are ... business and government innovation. Its ... technologies, ideas and management practices ..... sources of information and storage devices bring.

The Hanford Site generic component failure-rate database compared with other generic failure-rate databases

International Nuclear Information System (INIS)

Reardon, M.F.; Zentner, M.D.

1992-11-01

The Risk Assessment Technology Group, Westinghouse Hanford Company (WHC), has compiled a component failure rate database to be used during risk and reliability analysis of nonreactor facilities. Because site-specific data for the Hanford Site are generally not kept or not compiled in a usable form, the database was assembled using information from a variety of other established sources. Generally, the most conservative failure rates were chosen from the databases reviewed. The Hanford Site database has since been used extensively in fault tree modeling of many Hanford Site facilities and systems. The purpose of this study was to evaluate the reasonableness of the data chosen for the Hanford Site database by comparing the values chosen with the values from the other databases

DFIRM Database, COVINGTON COUNTY, ALABAMA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE,

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

FINAL Database, LAKE COUNTY, FLORIDA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DFIRM DATABASE, YOUNG COUNTY, TEXAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

24 CFR 81.72 - Public-use database and public information.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Public-use database and public... Public-use database and public information. (a) General. Except as provided in paragraph (c) of this section, the Secretary shall establish and make available for public use, a public-use database containing...

New perspectives in toxicological information management, and the role of ISSTOX databases in assessing chemical mutagenicity and carcinogenicity.

Science.gov (United States)

Benigni, Romualdo; Battistelli, Chiara Laura; Bossa, Cecilia; Tcheremenskaia, Olga; Crettaz, Pierre

2013-07-01

Currently, the public has access to a variety of databases containing mutagenicity and carcinogenicity data. These resources are crucial for the toxicologists and regulators involved in the risk assessment of chemicals, which necessitates access to all the relevant literature, and the capability to search across toxicity databases using both biological and chemical criteria. Towards the larger goal of screening chemicals for a wide range of toxicity end points of potential interest, publicly available resources across a large spectrum of biological and chemical data space must be effectively harnessed with current and evolving information technologies (i.e. systematised, integrated and mined), if long-term screening and prediction objectives are to be achieved. A key to rapid progress in the field of chemical toxicity databases is that of combining information technology with the chemical structure as identifier of the molecules. This permits an enormous range of operations (e.g. retrieving chemicals or chemical classes, describing the content of databases, finding similar chemicals, crossing biological and chemical interrogations, etc.) that other more classical databases cannot allow. This article describes the progress in the technology of toxicity databases, including the concepts of Chemical Relational Database and Toxicological Standardized Controlled Vocabularies (Ontology). Then it describes the ISSTOX cluster of toxicological databases at the Istituto Superiore di Sanitá. It consists of freely available databases characterised by the use of modern information technologies and by curation of the quality of the biological data. Finally, this article provides examples of analyses and results made possible by ISSTOX.

Database system selection for marketing strategies support in information systems

Directory of Open Access Journals (Sweden)

František Dařena

2007-01-01

Full Text Available In today’s dynamically changing environment marketing has a significant role. Creating successful marketing strategies requires large amount of high quality information of various kinds and data types. A powerful database management system is a necessary condition for marketing strategies creation support. The paper briefly describes the field of marketing strategies and specifies the features that should be provided by database systems in connection with these strategies support. Major commercial (Oracle, DB2, MS SQL, Sybase and open-source (PostgreSQL, MySQL, Firebird databases are than examined from the point of view of accordance with these characteristics and their comparison in made. The results are useful for making the decision before acquisition of a database system during information system’s hardware architecture specification.

An online database for informing ecological network models: http://kelpforest.ucsc.edu.

Science.gov (United States)

Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).

Database and applications security integrating information security and data management

CERN Document Server

Thuraisingham, Bhavani

2005-01-01

This is the first book to provide an in-depth coverage of all the developments, issues and challenges in secure databases and applications. It provides directions for data and application security, including securing emerging applications such as bioinformatics, stream information processing and peer-to-peer computing. Divided into eight sections, each of which focuses on a key concept of secure databases and applications, this book deals with all aspects of technology, including secure relational databases, inference problems, secure object databases, secure distributed databases and emerging

ORF information - KOME | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ... File URL: ftp://ftp.biosciencedbc.jp/archive/kome/LATEST/kome_orf_infomation.zip File size: 526 KB Simple s...ut This Database Database Description Download License Update History of This Database Site Policy | Contact Us ORF information - KOME | LSDB Archive ...

Advanced information technology: Building stronger databases

Energy Technology Data Exchange (ETDEWEB)

Price, D. [Lawrence Livermore National Lab., CA (United States)

1994-12-01

This paper discusses the attributes of the Advanced Information Technology (AIT) tool set, a database application builder designed at the Lawrence Livermore National Laboratory. AIT consists of a C library and several utilities that provide referential integrity across a database, interactive menu and field level help, and a code generator for building tightly controlled data entry support. AIT also provides for dynamic menu trees, report generation support, and creation of user groups. Composition of the library and utilities is discussed, along with relative strengths and weaknesses. In addition, an instantiation of the AIT tool set is presented using a specific application. Conclusions about the future and value of the tool set are then drawn based on the use of the tool set with that specific application.

Usefulness of administrative databases for risk adjustment of adverse events in surgical patients.

Science.gov (United States)

Rodrigo-Rincón, Isabel; Martin-Vizcaíno, Marta P; Tirapu-León, Belén; Zabalza-López, Pedro; Abad-Vicente, Francisco J; Merino-Peralta, Asunción; Oteiza-Martínez, Fabiola

2016-03-01

The aim of this study was to assess the usefulness of clinical-administrative databases for the development of risk adjustment in the assessment of adverse events in surgical patients. The study was conducted at the Hospital of Navarra, a tertiary teaching hospital in northern Spain. We studied 1602 hospitalizations of surgical patients from 2008 to 2010. We analysed 40 comorbidity variables included in the National Surgical Quality Improvement (NSQIP) Program of the American College of Surgeons using 2 sources of information: The clinical and administrative database (CADB) and the data extracted from the complete clinical records (CR), which was considered the gold standard. Variables were catalogued according to compliance with the established criteria: sensitivity, positive predictive value and kappa coefficient >0.6. The average number of comorbidities per study participant was 1.6 using the CR and 0.95 based on CADB (p<.0001). Thirteen types of comorbidities (accounting for 8% of the comorbidities detected in the CR) were not identified when the CADB was the source of information. Five of the 27 remaining comorbidities complied with the 3 established criteria; 2 pathologies fulfilled 2 criteria, whereas 11 fulfilled 1, and 9 did not fulfil any criterion. CADB detected prevalent comorbidities such as comorbid hypertension and diabetes. However, the CABD did not provide enough information to assess the variables needed to perform the risk adjustment proposed by the NSQIP for the assessment of adverse events in surgical patients. Copyright © 2015. Publicado por Elsevier España, S.L.U.

Use of epidemiologic data in Integrated Risk Information System (IRIS) assessments

International Nuclear Information System (INIS)

Persad, Amanda S.; Cooper, Glinda S.

2008-01-01

In human health risk assessment, information from epidemiologic studies is typically utilized in the hazard identification step of the risk assessment paradigm. However, in the assessment of many chemicals by the Integrated Risk Information System (IRIS), epidemiologic data, both observational and experimental, have also been used in the derivation of toxicological risk estimates (i.e., reference doses [RfD], reference concentrations [RfC], oral cancer slope factors [CSF] and inhalation unit risks [IUR]). Of the 545 health assessments posted on the IRIS database as of June 2007, 44 assessments derived non-cancer or cancer risk estimates based on human data. RfD and RfC calculations were based on a spectrum of endpoints from changes in enzyme activity to specific neurological or dermal effects. There are 12 assessments with IURs based on human data, two assessments that extrapolated human inhalation data to derive CSFs and one that used human data to directly derive a CSF. Lung or respiratory cancer is the most common endpoint for cancer assessments based on human data. To date, only one chemical, benzene, has utilized human data for derivation of all three quantitative risk estimates (i.e., RfC, RfD, and dose-response modeling for cancer assessment). Through examples from the IRIS database, this paper will demonstrate how epidemiologic data have been used in IRIS assessments for both adding to the body of evidence in the hazard identification process and in the quantification of risk estimates in the dose-response component of the risk assessment paradigm

FINAL DFIRM DATABASE, LIMESTONE COUNTY, TEXAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, , USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

FINAL DFIRM DATABASE, UNION PARISH, LOUISIANA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

FINAL DFIRM DATABASE, SHARP COUNTY, ARKANSAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

FINAL DFIRM DATABASE, BRYAN COUNTY, OKLAHOMA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

On Region Algebras, XML Databases, and Information Retrieval

NARCIS (Netherlands)

Mihajlovic, V.; Hiemstra, Djoerd; Apers, Peter M.G.

2003-01-01

This paper describes some new ideas on developing a logical algebra for databases that manage textual data and support information retrieval functionality. We describe a first prototype of such a system.

Integration of an Evidence Base into a Probabilistic Risk Assessment Model. The Integrated Medical Model Database: An Organized Evidence Base for Assessing In-Flight Crew Health Risk and System Design

Science.gov (United States)

Saile, Lynn; Lopez, Vilma; Bickham, Grandin; FreiredeCarvalho, Mary; Kerstman, Eric; Byrne, Vicky; Butler, Douglas; Myers, Jerry; Walton, Marlei

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) database, which is an organized evidence base for assessing in-flight crew health risk. The database is a relational database accessible to many people. The database quantifies the model inputs by a ranking based on the highest value of the data as Level of Evidence (LOE) and the quality of evidence (QOE) score that provides an assessment of the evidence base for each medical condition. The IMM evidence base has already been able to provide invaluable information for designers, and for other uses.

A press database on natural risks and its application in the study of floods in Northeastern Spain

Directory of Open Access Journals (Sweden)

M. C. Llasat

2009-12-01

Full Text Available The aim of this work is to introduce a systematic press database on natural hazards and climate change in Catalonia (NE of Spain and to analyze its potential application to social-impact studies. For this reason, a review of the concepts of risk, hazard, vulnerability and social perception is also included. This database has been built for the period 1982–2007 and contains all the news related with those issues published by the oldest still-active newspaper in Catalonia. Some parameters are registered for each article and for each event, including criteria that enable us to determine the importance accorded to it by the newspaper, and a compilation of information about it. This ACCESS data base allows each article to be classified on the basis of the seven defined topics and key words, as well as summary information about the format and structuring of the new itself, the social impact of the event and data about the magnitude or intensity of the event. The coverage given to this type of news has been assessed because of its influence on construction of the social perception of natural risk and climate change, and as a potential source of information about them. The treatment accorded by the press to different risks is also considered. More than 14 000 press articles have been classified. Results show that the largest number of news items for the period 1982–2007 relates to forest fires and droughts, followed by floods and heavy rainfalls, although floods are the major risk in the region of study. Two flood events recorded in 2002 have been analyzed in order to show an example of the role of the press information as indicator of risk perception.

Database Description - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Trypanosomes Database Database Description General information of database Database name Trypanosomes Database...stitute of Genetics Research Organization of Information and Systems Yata 1111, Mishima, Shizuoka 411-8540, JAPAN E mail: Database...y Name: Trypanosoma Taxonomy ID: 5690 Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database description The... Article title: Author name(s): Journal: External Links: Original website information Database maintenance s...DB (Protein Data Bank) KEGG PATHWAY Database DrugPort Entry list Available Query search Available Web servic

Content Is King: Databases Preserve the Collective Information of Science.

Science.gov (United States)

Yates, John R

2018-04-01

Databases store sequence information experimentally gathered to create resources that further science. In the last 20 years databases have become critical components of fields like proteomics where they provide the basis for large-scale and high-throughput proteomic informatics. Amos Bairoch, winner of the Association of Biomolecular Resource Facilities Frederick Sanger Award, has created some of the important databases proteomic research depends upon for accurate interpretation of data.

Large-scale Health Information Database and Privacy Protection.

Science.gov (United States)

Yamamoto, Ryuichi

2016-09-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law that aims to ensure healthcare for the elderly; however, there is no mention in the act about using these databases for public interest in general. Thus, an initiative for such use must proceed carefully and attentively. The PMDA projects that collect a large amount of medical record information from large hospitals and the health database development project that the Ministry of Health, Labour and Welfare (MHLW) is working on will soon begin to operate according to a general consensus; however, the validity of this consensus can be questioned if issues of anonymity arise. The likelihood that researchers conducting a study for public interest would intentionally invade the privacy of their subjects is slim. However, patients could develop a sense of distrust about their data being used since legal requirements are ambiguous. Nevertheless, without using patients' medical records for public interest, progress in medicine will grind to a halt. Proper legislation that is clear for both researchers and patients will therefore be highly desirable. A revision of the Act on the Protection of Personal Information is currently in progress. In reality, however, privacy is not something that laws alone can protect; it will also require guidelines and self-discipline. We now live in an information capitalization age. I will introduce the trends in legal reform regarding healthcare information and discuss some basics to help people properly face the issue of health big data and privacy

Brain Tumor Database, a free relational database for collection and analysis of brain tumor patient information.

Science.gov (United States)

Bergamino, Maurizio; Hamilton, David J; Castelletti, Lara; Barletta, Laura; Castellan, Lucio

2015-03-01

In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org. © The Author(s) 2013.

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

Science.gov (United States)

Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem

2016-01-01

Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

A proposal for a drug information database and text templates for generating package inserts

Directory of Open Access Journals (Sweden)

Okuya R

2013-07-01

Full Text Available Ryo Okuya,1 Masaomi Kimura,2 Michiko Ohkura,2 Fumito Tsuchiya3 1Graduate School of Engineering and Science, 2Faculty of Engineering, Shibaura Institute of Technology, Tokyo, 3School of Pharmacy, International University of Health and Welfare, Tokyo, Japan Abstract: To prevent prescription errors caused by information systems, a database to store complete and accurate drug information in a user-friendly format is needed. In previous studies, the primary method for obtaining data stored in a database is to extract drug information from package inserts by employing pattern matching or more sophisticated methods such as text mining. However, it is difficult to obtain a complete database because there is no strict rule concerning expressions used to describe drug information in package inserts. The authors' strategy was to first build a database and then automatically generate package inserts by embedding data in the database using templates. To create this database, the support of pharmaceutical companies to input accurate data is required. It is expected that this system will work, because these companies can earn merit for newly developed drugs to decrease the effort to create package inserts from scratch. This study designed the table schemata for the database and text templates to generate the package inserts. To handle the variety of drug-specific information in the package inserts, this information in drug composition descriptions was replaced with labels and the replacement descriptions utilizing cluster analysis were analyzed. To improve the method by which frequently repeated ingredient information and/or supplementary information are stored, the method was modified by introducing repeat tags in the templates to indicate repetition and improving the insertion of data into the database. The validity of this method was confirmed by inputting the drug information described in existing package inserts and checking that the method could

Visualizing information across multidimensional post-genomic structured and textual databases.

Science.gov (United States)

Tao, Ying; Friedman, Carol; Lussier, Yves A

2005-04-15

Visualizing relationships among biological information to facilitate understanding is crucial to biological research during the post-genomic era. Although different systems have been developed to view gene-phenotype relationships for specific databases, very few have been designed specifically as a general flexible tool for visualizing multidimensional genotypic and phenotypic information together. Our goal is to develop a method for visualizing multidimensional genotypic and phenotypic information and a model that unifies different biological databases in order to present the integrated knowledge using a uniform interface. We developed a novel, flexible and generalizable visualization tool, called PhenoGenesviewer (PGviewer), which in this paper was used to display gene-phenotype relationships from a human-curated database (OMIM) and from an automatic method using a Natural Language Processing tool called BioMedLEE. Data obtained from multiple databases were first integrated into a uniform structure and then organized by PGviewer. PGviewer provides a flexible query interface that allows dynamic selection and ordering of any desired dimension in the databases. Based on users' queries, results can be visualized using hierarchical expandable trees that present views specified by users according to their research interests. We believe that this method, which allows users to dynamically organize and visualize multiple dimensions, is a potentially powerful and promising tool that should substantially facilitate biological research. PhenogenesViewer as well as its support and tutorial are available at http://www.dbmi.columbia.edu/pgviewer/ Lussier@dbmi.columbia.edu.

Database Description - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Yeast Interacting Proteins Database Database Description General information of database Database... name Yeast Interacting Proteins Database Alternative name - DOI 10.18908/lsdba.nbdc00742-000 Creator C...-ken 277-8561 Tel: +81-4-7136-3989 FAX: +81-4-7136-3979 E-mail : Database classif...s cerevisiae Taxonomy ID: 4932 Database description Information on interactions and related information obta...l Acad Sci U S A. 2001 Apr 10;98(8):4569-74. Epub 2001 Mar 13. External Links: Original website information Database

The Research on Safety Management Information System of Railway Passenger Based on Risk Management Theory

Science.gov (United States)

Zhu, Wenmin; Jia, Yuanhua

2018-01-01

Based on the risk management theory and the PDCA cycle model, requirements of the railway passenger transport safety production is analyzed, and the establishment of the security risk assessment team is proposed to manage risk by FTA with Delphi from both qualitative and quantitative aspects. The safety production committee is also established to accomplish performance appraisal, which is for further ensuring the correctness of risk management results, optimizing the safety management business processes and improving risk management capabilities. The basic framework and risk information database of risk management information system of railway passenger transport safety are designed by Ajax, Web Services and SQL technologies. The system realizes functions about risk management, performance appraisal and data management, and provides an efficient and convenient information management platform for railway passenger safety manager.

Information support of monitoring of technical condition of buildings in construction risk area

Science.gov (United States)

Skachkova, M. E.; Lepihina, O. Y.; Ignatova, V. V.

2018-05-01

The paper presents the results of the research devoted to the development of a model of information support of monitoring buildings technical condition; these buildings are located in the construction risk area. As a result of the visual and instrumental survey, as well as the analysis of existing approaches and techniques, attributive and cartographic databases have been created. These databases allow monitoring defects and damages of buildings located in a 30-meter risk area from the object under construction. The classification of structures and defects of these buildings under survey is presented. The functional capabilities of the developed model and the field of it practical applications are determined.

FINAL DFIRM DATABASE, PALO PINTO COUNTY, TEXAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Information retrieval system of nuclear power plant database (PPD) user's guide

International Nuclear Information System (INIS)

Izumi, Fumio; Horikami, Kunihiko; Kobayashi, Kensuke.

1990-12-01

A nuclear power plant database (PPD) and its retrieval system have been developed. The database involves a large number of safety design data of nuclear power plants, operating and planned in Japan. The information stored in the database can be retrieved at high speed, whenever they are needed, by use of the retrieval system. The report is a user's manual of the system to access the database utilizing a display unit of the JAERI computer network system. (author)

Integrated application of the database for airborne geophysical survey achievement information

International Nuclear Information System (INIS)

Ji Zengxian; Zhang Junwei

2006-01-01

The paper briefly introduces the database of information for airborne geophysical survey achievements. This database was developed on the platform of Microsoft Windows System with the technical methods of Visual C++ 6.0 and MapGIS. It is an information management system concerning airborne geophysical surveying achievements with perfect functions in graphic display, graphic cutting and output, query of data, printing of documents and reports, maintenance of database, etc. All information of airborne geophysical survey achievements in nuclear industry from 1972 to 2003 was embedded in. Based on regional geological map and Meso-Cenozoic basin map, the detailed statistical information of each airborne survey area, each airborne radioactive anomalous point and high field point can be presented visually by combining geological or basin research result. The successful development of this system will provide a fairly good base and platform for management of archives and data of airborne geophysical survey achievements in nuclear industry. (authors)

Coupling an Unstructured NoSQL Database with a Geographic Information System

OpenAIRE

Holemans, Amandine; Kasprzyk, Jean-Paul; Donnay, Jean-Paul

2018-01-01

The management of unstructured NoSQL (Not only Structured Query Language) databases has undergone a great development in the last years mainly thanks to Big Data. Nevertheless, the specificity of spatial information is not purposely taken into account. To overcome this difficulty, we propose to couple a NoSQL database with a spatial Relational Data Base Management System (RDBMS). Exchanges of information between these two systems are illustrated with relevant examples ...

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

Directory of Open Access Journals (Sweden)

Ahmad Tamimi

Full Text Available Profile Hidden Markov Model (Profile-HMM is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

Construction of a bibliographic information database for the nuclear engineering

International Nuclear Information System (INIS)

Kim, Tae Whan; Lim, Yeon Soo; Kwac, Dong Chul

1991-12-01

The major goal of the project is to develop a nuclear science database of materials that have been published in Korea and to establish a network system that will give relevant information to people in the nuclear industry by linking this system with the proposed National Science Technical Information Network. This project aims to establish a database consisted of about 1,000 research reports that were prepared by KAERI from 1979 to 1990. The contents of the project are as follows: 1. Materials Selection and Collection 2. Index and Abstract Preparation 3. Data Input and Transmission. This project is intended to achieve the goal of maximum utilization of nuclear information in Korea. (Author)

Proposed Regulatory Guideline on the PSA Quality for Risk-informed Applications

International Nuclear Information System (INIS)

Lee, Chang Ju; Choi, Jong Soo

2005-01-01

In the policy statement on nuclear safety issued by the Korean government in 1994, the introduction of risk-informed regulations in licensing and regulation of nuclear power plants was emphasized for the first time. It also describes the implementation of comprehensive safety assessment utilizing PSA (probabilistic safety assessment). Since then, because risk-informed environment and fundamentals had not been strong, several R and D on PSA and risk-informed regulation have been done even though their application has been delayed. However, today it is not the case. Since the follow-up policy statement (called Severe Accident Policy) was issued, which prescribes strong items such as PSA implementation and its periodic reassessment, reliability database, and risk monitoring program to the utility, we have a chance to easily get all kinds of risk information for improving current regulatory framework. In addition, with the overall availability of PSA results for all operating nuclear power plants, it is expected that many risk-informed applications (RIAs) will be submitted to the regulatory authority. In general, there are a lot of regulatory concerns associated with the quality assurance of licensee's submittals for RIA. It is also noted that making general requirements and touching specific check points are essential for the regulatory decision making process. This paper summarizes the structure and contents of our regulatory guideline for assuring PSA quality

16th East-European Conference on Advances in Databases and Information Systems (ADBIS 2012)

CERN Document Server

Härder, Theo; Wrembel, Robert; Advances in Databases and Information Systems

2013-01-01

This volume is the second one of the 16th East-European Conference on Advances in Databases and Information Systems (ADBIS 2012), held on September 18-21, 2012, in Poznań, Poland. The first one has been published in the LNCS series.   This volume includes 27 research contributions, selected out of 90. The contributions cover a wide spectrum of topics in the database and information systems field, including: database foundation and theory, data modeling and database design, business process modeling, query optimization in relational and object databases, materialized view selection algorithms, index data structures, distributed systems, system and data integration, semi-structured data and databases, semantic data management, information retrieval, data mining techniques, data stream processing, trust and reputation in the Internet, and social networks. Thus, the content of this volume covers the research areas from fundamentals of databases, through still hot topic research problems (e.g., data mining, XML ...

The IPE Database: providing information on plant design, core damage frequency and containment performance

International Nuclear Information System (INIS)

Lehner, J.R.; Lin, C.C.; Pratt, W.T.; Su, T.; Danziger, L.

1996-01-01

A database, called the IPE Database has been developed that stores data obtained from the Individual Plant Examinations (IPEs) which licensees of nuclear power plants have conducted in response to the Nuclear Regulatory Commission's (NRC) Generic Letter GL88-20. The IPE Database is a collection of linked files which store information about plant design, core damage frequency (CDF), and containment performance in a uniform, structured way. The information contained in the various files is based on data contained in the IPE submittals. The information extracted from the submittals and entered into the IPE Database can be manipulated so that queries regarding individual or groups of plants can be answered using the IPE Database

Use of information resources by the state of Tennessee in risk assessment applications

Energy Technology Data Exchange (ETDEWEB)

Bashor, B.S. [Tennessee Department of Health and Environment, Nashville (United States)

1990-12-31

The major resources used by the Bureau of Environment, and Environmental Epidemiology (EEP) for risk assessment are: the Integrated Risk Information System (IRIS), Health and Environmental Effects Summary Table (HEAST), Agency for Toxic Substances and disease Registry (ATSDR) Toxicological Profiles, databases at the National Library of Medicine (NLM), World Health Organization (WHO) ENvironmental Criteria, and documents that the Environmental Protection Agency (EPA) has published on Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) risk assessment activities. The Risk Assessment Review has been helpful in providing information about availability of new documents or information. No systematic method has been made available to us to locate information resources. IRIS User`s Support has been helpful in making appropriate and timely referrals. Most other EPA resources were located by serendipity and persistence. The CERCLA methodology for risk assessments is being used in environmental programs, and at present, one person is responsible for all risk assessment activities in the department, but plans are underway to train one or two people from each program area. 2 figs.

Let the IRIS Bloom:Regrowing the integrated risk information system (IRIS) of the U.S. Environmental Protection Agency.

Science.gov (United States)

Dourson, Michael L

2018-05-03

The Integrated Risk Information System (IRIS) of the U.S. Environmental Protection Agency (EPA) has an important role in protecting public health. Originally it provided a single database listing official risk values equally valid for all Agency offices, and was an important tool for risk assessment communication across EPA. Started in 1986, IRIS achieved full standing in 1990 when it listed 500 risk values, the effort of two senior EPA groups over 5 years of monthly face-to-face meetings, to assess combined risk data from multiple Agency offices. Those groups were disbanded in 1995, and the lack of continuing face-to-face meetings meant that IRIS became no longer EPA's comprehensive database of risk values or their latest evaluations. As a remedy, a work group of the Agency's senior scientists should be re-established to evaluate new risks and to update older ones. Risk values to be reviewed would come from the same EPA offices now developing such information on their own. Still, this senior group would have the final authority on posting a risk value in IRIS, independently of individual EPA offices. This approach could also lay the groundwork for an all-government IRIS database, especially needed as more government Agencies, industries and non-governmental organizations are addressing evolving risk characterizations. Copyright © 2018. Published by Elsevier Inc.

Practice databases and their uses in clinical research.

Science.gov (United States)

Tierney, W M; McDonald, C J

1991-04-01

A few large clinical information databases have been established within larger medical information systems. Although they are smaller than claims databases, these clinical databases offer several advantages: accurate and timely data, rich clinical detail, and continuous parameters (for example, vital signs and laboratory results). However, the nature of the data vary considerably, which affects the kinds of secondary analyses that can be performed. These databases have been used to investigate clinical epidemiology, risk assessment, post-marketing surveillance of drugs, practice variation, resource use, quality assurance, and decision analysis. In addition, practice databases can be used to identify subjects for prospective studies. Further methodologic developments are necessary to deal with the prevalent problems of missing data and various forms of bias if such databases are to grow and contribute valuable clinical information.

Genetic and bibliographic information - GenLibi | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available n Data acquisition method Articles related to genes were obtained from the bibliography database (JDream II)...provided from the JST bibliographic information system (JDream II) About This Database Database Description

Filling Terrorism Gaps: VEOs, Evaluating Databases, and Applying Risk Terrain Modeling to Terrorism

Energy Technology Data Exchange (ETDEWEB)

Hagan, Ross F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2016-08-29

This paper aims to address three issues: the lack of literature differentiating terrorism and violent extremist organizations (VEOs), terrorism incident databases, and the applicability of Risk Terrain Modeling (RTM) to terrorism. Current open source literature and publicly available government sources do not differentiate between terrorism and VEOs; furthermore, they fail to define them. Addressing the lack of a comprehensive comparison of existing terrorism data sources, a matrix comparing a dozen terrorism databases is constructed, providing insight toward the array of data available. RTM, a method for spatial risk analysis at a micro level, has some applicability to terrorism research, particularly for studies looking at risk indicators of terrorism. Leveraging attack data from multiple databases, combined with RTM, offers one avenue for closing existing research gaps in terrorism literature.

Database system of geological information for geological evaluation base of NPP sites(I)

International Nuclear Information System (INIS)

Lim, C. B.; Choi, K. R.; Sim, T. M.; No, M. H.; Lee, H. W.; Kim, T. K.; Lim, Y. S.; Hwang, S. K.

2002-01-01

This study aims to provide database system for site suitability analyses of geological information and a processing program for domestic NPP site evaluation. This database system program includes MapObject provided by ESRI and Spread 3.5 OCX, and is coded with Visual Basic language. Major functions of the systematic database program includes vector and raster farmat topographic maps, database design and application, geological symbol plot, the database search for the plotted geological symbol, and so on. The program can also be applied in analyzing not only for lineament trends but also for statistic treatment from geologically site and laboratory information and sources in digital form and algorithm, which is usually used internationally

Database Description - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us SKIP Stemcell Database Database Description General information of database Database name SKIP Stemcell Database...rsity Journal Search: Contact address http://www.skip.med.keio.ac.jp/en/contact/ Database classification Human Genes and Diseases Dat...abase classification Stemcell Article Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database...ks: Original website information Database maintenance site Center for Medical Genetics, School of medicine, ...lable Web services Not available URL of Web services - Need for user registration Not available About This Database Database

A Parallel Relational Database Management System Approach to Relevance Feedback in Information Retrieval.

Science.gov (United States)

Lundquist, Carol; Frieder, Ophir; Holmes, David O.; Grossman, David

1999-01-01

Describes a scalable, parallel, relational database-drive information retrieval engine. To support portability across a wide range of execution environments, all algorithms adhere to the SQL-92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database-driven information retrieval efforts. Presents…

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OSCEOLA COUNTY, FL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HART COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE,GRAVES COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LYON COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WOLFE COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WEBSTER COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHRISTIAN COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DAVIESS COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARLBORO COUNTY, SC

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDDLESEX, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SCOTT COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, GEORGIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LUCAS COUNTY, OHIO

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARDIN COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SARPY COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUFFOLK COUNTY, MASSACHUSETTS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FAIRFIELD COUNTY, CONNECTICUT

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BUTLER COUNTY, NE

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Wilcox COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASHINGTON COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BALLARD COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARRISON COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POWELL COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Eddy County, NM

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Winston COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Mitchell County, GA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ANGELINA COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ATASCOSA COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FLEMING COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEWARD COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCCRACKEN COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Flood Insurance Rate Map Database, Kent County, Delaware, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAUNDERS COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, KANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARLAN COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RENO COUNTY, KANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FURNAS COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLAMAKEE COUNTY, IOWA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CASS COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCPHERSON COUNTY, KANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DAWES COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VALLEY COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ELLSWORTH COUNTY, KANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHERMAN COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARVEY COUNTY, KANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PLATTE COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLFAX COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, THURSTON COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TAMA COUNTY, IOWA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WEBSTER COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BONNER COUNTY, IDAHO

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ROBERTSON COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRANT COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ESSEX COUNTY, MA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEBASTIAN COUNTY, AR

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEBASTIAN COUNTY, ARKANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHAMBERS COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NELSON COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCLEAN COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RUSK COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PEMBINA COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JOHNSON COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Harris COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PIKE COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, FLORIDA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOUSTON COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Marshall COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRIMES COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALLER COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CARBON COUNTY, UTAH

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Liberty County, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TYLER COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Stafford County , VIRGINIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUMNER COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HILLSBOROUGH COUNTY, FLORIDA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LEE COUNTY, FLORIDA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WAYNE COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Jefferson COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Kenton COUNTY, Kentucky

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RUSSELL COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST. LOUIS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALPENA COUNTY, MI

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Dougherty County, GA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCDONALD COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MERCER COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Crawford County, PA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BATH COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Douglas COUNTY, Nevada

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Elbert County, Colorado

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JASPER COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Cleburne COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE,CAMDEN COUNTY, GEORGIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MENDOCINO COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ETOWAH COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HUNTERDON CO., NJ

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FINNEY COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CULLMAN COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LEBANON COUNTY, PENNSYLVANIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ELLIOTT COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GAGE COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLARK COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDDLESEX COUNTY, MASSACHUSETTS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ESCAMBIA COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Baldwin COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SONOMA COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BENTON COUNTY, ARKANSAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GORDON COUNTY, GEORGIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information And supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARIN COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BOYLE COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Bell COUNTY, Kentucky

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BATH COUNTY, VIRGINIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SIMPSON COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BANDERA COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Washington COUNTY, NE

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Mercer County, PA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DUKES COUNTY, MA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Terrell County, GA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GLOUCESTER, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WORCESTER COUNTY, MA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Cherokee COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JACKSON COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NORFOLK COUNTY, MASSACHUSETTS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COWLEY COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TALBOT, MARYLAND, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NANTUCKET COUNTY, MASSACHUSETTS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHESTERFIELD, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WORCESTER COUNTY, MASSACHUSETTS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OTTAWA COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRAND COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DILLON COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLEN COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOLMES COUNTY, OHIO

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOLMES COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KOOTENAI COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Accomack County, VIRGINIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LYCOMING COUNTY, PENNSYLVANIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WHATCOM COUNTY, WASHINGTON

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARRISON COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MATHEWS COUNTY, VIRGINIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HIGHLAND COUNTY, VIRGINIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUMTER COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RALLS COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOUSTON COUNTY, Georgia

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YOLO COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Tuolumne County, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MADERA COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TEHAMA COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SACRAMENTO COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOPKINS COUNTY, KY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Butts County, GA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MAYES COUNTY, OK

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRADY COUNTY, OKLAHOMA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHASTA COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ROSS COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BALTIMORE CITY, MARYLAND

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Chambers COUNTY, AL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ROGERS COUNTY, OKLAHOMA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MEDINA COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, STARK COUNTY, OHIO

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALBEMARLE COUNTY, VIRGINIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Large-scale Health Information Database and Privacy Protection*1

Science.gov (United States)

YAMAMOTO, Ryuichi

2016-01-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law that aims to ensure healthcare for the elderly; however, there is no mention in the act about using these databases for public interest in general. Thus, an initiative for such use must proceed carefully and attentively. The PMDA*2 projects that collect a large amount of medical record information from large hospitals and the health database development project that the Ministry of Health, Labour and Welfare (MHLW) is working on will soon begin to operate according to a general consensus; however, the validity of this consensus can be questioned if issues of anonymity arise. The likelihood that researchers conducting a study for public interest would intentionally invade the privacy of their subjects is slim. However, patients could develop a sense of distrust about their data being used since legal requirements are ambiguous. Nevertheless, without using patients’ medical records for public interest, progress in medicine will grind to a halt. Proper legislation that is clear for both researchers and patients will therefore be highly desirable. A revision of the Act on the Protection of Personal Information is currently in progress. In reality, however, privacy is not something that laws alone can protect; it will also require guidelines and self-discipline. We now live in an information capitalization age. I will introduce the trends in legal reform regarding healthcare information and discuss some basics to help people properly face the issue of health big data and privacy

Availability and Utilization of Electronic Information Databases by ...

African Journals Online (AJOL)

The study was undertaken to determine the Availability and Utilization of Electronic Information Database by Staff of the Agricultural Complex, Ahmadu Bello University, Zaria. A survey method was used for the study. Stratified sampling method was used to select 209 respondents to accommodate the different strata of the ...

GIS Database and Google Map of the Population at Risk of Cholangiocarcinoma in Mueang Yang District, Nakhon Ratchasima Province of Thailand.

Science.gov (United States)

Kaewpitoon, Soraya J; Rujirakul, Ratana; Joosiri, Apinya; Jantakate, Sirinun; Sangkudloa, Amnat; Kaewthani, Sarochinee; Chimplee, Kanokporn; Khemplila, Kritsakorn; Kaewpitoon, Natthawut

2016-01-01

Cholangiocarcinoma (CCA) is a serious problem in Thailand, particularly in the northeastern and northern regions. Database of population at risk are need required for monitoring, surveillance, home health care, and home visit. Therefore, this study aimed to develop a geographic information system (GIS) database and Google map of the population at risk of CCA in Mueang Yang district, Nakhon Ratchasima province, northeastern Thailand during June to October 2015. Populations at risk were screened using the Korat CCA verbal screening test (KCVST). Software included Microsoft Excel, ArcGIS, and Google Maps. The secondary data included the point of villages, sub-district boundaries, district boundaries, point of hospital in Mueang Yang district, used for created the spatial databese. The populations at risk for CCA and opisthorchiasis were used to create an arttribute database. Data were tranfered to WGS84 UTM ZONE 48. After the conversion, all of the data were imported into Google Earth using online web pages www.earthpoint.us. Some 222 from a 4,800 population at risk for CCA constituted a high risk group. Geo-visual display available at following www.google.com/maps/d/u/0/ edit?mid=zPxtcHv_iDLo.kvPpxl5mAs90 and hl=th. Geo-visual display 5 layers including: layer 1, village location and number of the population at risk for CCA; layer 2, sub-district health promotion hospital in Mueang Yang district and number of opisthorchiasis; layer 3, sub-district district and the number of population at risk for CCA; layer 4, district hospital and the number of population at risk for CCA and number of opisthorchiasis; and layer 5, district and the number of population at risk for CCA and number of opisthorchiasis. This GIS database and Google map production process is suitable for further monitoring, surveillance, and home health care for CCA sufferers.

International Nuclear Safety Center (INSC) database

International Nuclear Information System (INIS)

Sofu, T.; Ley, H.; Turski, R.B.

1997-01-01

As an integral part of DOE's International Nuclear Safety Center (INSC) at Argonne National Laboratory, the INSC Database has been established to provide an interactively accessible information resource for the world's nuclear facilities and to promote free and open exchange of nuclear safety information among nations. The INSC Database is a comprehensive resource database aimed at a scope and level of detail suitable for safety analysis and risk evaluation for the world's nuclear power plants and facilities. It also provides an electronic forum for international collaborative safety research for the Department of Energy and its international partners. The database is intended to provide plant design information, material properties, computational tools, and results of safety analysis. Initial emphasis in data gathering is given to Soviet-designed reactors in Russia, the former Soviet Union, and Eastern Europe. The implementation is performed under the Oracle database management system, and the World Wide Web is used to serve as the access path for remote users. An interface between the Oracle database and the Web server is established through a custom designed Web-Oracle gateway which is used mainly to perform queries on the stored data in the database tables

Application of database management software to probabilistic risk assessment calculations

International Nuclear Information System (INIS)

Wyss, G.D.

1993-01-01

Probabilistic risk assessment (PRA) calculations require the management and processing of large amounts of information. This data normally falls into two general categories. For example, a commercial nuclear power plant PRA study makes use of plant blueprints and system schematics, formal plant safety analysis reports, incident reports, letters, memos, handwritten notes from plant visits, and even the analyst's ''engineering judgment''. This information must be documented and cross-referenced in order to properly execute and substantiate the models used in a PRA study. The first category is composed of raw data that is accumulated from equipment testing and operational experiences. These data describe the equipment, its service or testing conditions, its failure mode, and its performance history. The second category is composed of statistical distributions. These distributions can represent probabilities, frequencies, or values of important parameters that are not time-related. Probability and frequency distributions are often obtained by fitting raw data to an appropriate statistical distribution. Database management software is used to store both types of data so that it can be readily queried, manipulated, and archived. This paper provides an overview of the information models used for storing PRA data and illustrates the implementation of these models using examples from current PRA software packages

YAdumper: extracting and translating large information volumes from relational databases to structured flat files.

Science.gov (United States)

Fernández, José M; Valencia, Alfonso

2004-10-12

Downloading the information stored in relational databases into XML and other flat formats is a common task in bioinformatics. This periodical dumping of information requires considerable CPU time, disk and memory resources. YAdumper has been developed as a purpose-specific tool to deal with the integral structured information download of relational databases. YAdumper is a Java application that organizes database extraction following an XML template based on an external Document Type Declaration. Compared with other non-native alternatives, YAdumper substantially reduces memory requirements and considerably improves writing performance.

Databases and information systems: Applications in biogeography

International Nuclear Information System (INIS)

Escalante E, Tania; Llorente B, Jorge; Espinoza O, David N; Soberon M, Jorge

2000-01-01

Some aspects of the new instrumentalization and methodological elements that make up information systems in biodiversity (ISB) are described. The use of accurate geographically referenced data allows a broad range of available sources: natural history collections and scientific literature require the use of databases and geographic information systems (GIS). The conceptualization of ISB and GIS, based in the use of extensive data bases, has implied detailed modeling and the construction of authoritative archives: exhaustive catalogues of nomenclature and synonymies, complete bibliographic lists, list of names proposed, historical-geographic gazetteers with localities and their synonyms united under a global positioning system which produces a geospheric conception of the earth and its biota. Certain difficulties in the development of the system and the construction of the biological databases are explained: quality control of data, for example. The use of such systems is basic in order to respond to many questions at the frontier of current studies of biodiversity and conservation. In particular, some applications in biogeography and their importance for modeling distributions, to identify and contrast areas of endemism and biological richness for conservation, and their use as tools in what we identify as predictive and experimental faunistics are detailed. Lastly, the process as well as its relevance is emphasized at national and regional levels

Information needs and risk perception as predictors of risk information seeking

NARCIS (Netherlands)

ter Huurne, E.F.J.; Gutteling, Jan M.

2008-01-01

This paper introduces a theoretical framework that describes the importance of public's information sufficiency, risk perception, and self-efficacy as predictors of intended risk information seeking behaviour. Based on theoretical assumptions, measurement instruments for relevant concepts were

Development of reliability databases and the particular requirements of probabilistic risk analyses

International Nuclear Information System (INIS)

Meslin, T.

1989-01-01

Nuclear utilities have an increasing need to develop reliability databases for their operating experience. The purposes of these databases are often multiple, including both equipment maintenance aspects and probabilistic risk analyses. EDF has therefore been developing experience feedback databases, including the Reliability Data Recording System (SRDF) and the Event File, as well as the history of numerous operating documents. Furthermore, since the end of 1985, EDF has been preparing a probabilistic safety analysis applied to one 1,300 MWe unit, for which a large amount of data of French origin is necessary. This data concerns both component reliability parameters and initiating event frequencies. The study has thus been an opportunity for trying out the performance databases for a specific application, as well as in-depth audits of a number of nuclear sites to make it possible to validate numerous results. Computer aided data collection is also on trial in a number of plants. After describing the EDF operating experience feedback files, we discuss the particular requirements of probabilistic risk analyses, and the resources implemented by EDF to satisfy them. (author). 5 refs

Online drug databases: a new method to assess and compare inclusion of clinically relevant information.

Science.gov (United States)

Silva, Cristina; Fresco, Paula; Monteiro, Joaquim; Rama, Ana Cristina Ribeiro

2013-08-01

Evidence-Based Practice requires health care decisions to be based on the best available evidence. The model "Information Mastery" proposes that clinicians should use sources of information that have previously evaluated relevance and validity, provided at the point of care. Drug databases (DB) allow easy and fast access to information and have the benefit of more frequent content updates. Relevant information, in the context of drug therapy, is that which supports safe and effective use of medicines. Accordingly, the European Guideline on the Summary of Product Characteristics (EG-SmPC) was used as a standard to evaluate the inclusion of relevant information contents in DB. To develop and test a method to evaluate relevancy of DB contents, by assessing the inclusion of information items deemed relevant for effective and safe drug use. Hierarchical organisation and selection of the principles defined in the EGSmPC; definition of criteria to assess inclusion of selected information items; creation of a categorisation and quantification system that allows score calculation; calculation of relative differences (RD) of scores for comparison with an "ideal" database, defined as the one that achieves the best quantification possible for each of the information items; pilot test on a sample of 9 drug databases, using 10 drugs frequently associated in literature with morbidity-mortality and also being widely consumed in Portugal. Main outcome measure Calculate individual and global scores for clinically relevant information items of drug monographs in databases, using the categorisation and quantification system created. A--Method development: selection of sections, subsections, relevant information items and corresponding requisites; system to categorise and quantify their inclusion; score and RD calculation procedure. B--Pilot test: calculated scores for the 9 databases; globally, all databases evaluated significantly differed from the "ideal" database; some DB performed

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCINTOSH COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAWAII COUNTY, HAWAII, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, KENTUCKY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHRISTIAN COUNTY, ILLINOIS USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BENTON COUNTY, MINNESOTA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MONROE COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HENRY COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

FINAL DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENWOOD COUNTY, SC

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RICE COUNTY, MINNESOTA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KARNES COUNTY, TEXAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VOLUSIA COUNTY, FL, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, IA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POTTAWATTAMIE COUNTY, IOWA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MITCHELL COUNTY, IOWA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLAYTON COUNTY, IOWA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOWARD COUNTY, IOWA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NASSAU COUNTY, NEW YORK

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SULLIVAN COUNTY, NEW YORK

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, PRINCE GEORGE, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, OHIO, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WAGONER COUNTY, OKLAHOMA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, SC

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Buchanan County, Iowa, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SACRAMENTO COUNTY, CALIFORNIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CITY OF SACRAMENTO, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HONOLULU COUNTY, HI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KAUAI COUNTY, HAWAII, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PASCO COUNTY, FLORIDA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GILMER COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIAMI - DADE COUNTY, FLORIDA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, APPLING COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LINCOLN COUNTY, ARKANSAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CARROLL COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CONVERSE COUNTY, WYOMING, USA.

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, ILLINOIS USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Douglas County, Oregon, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLFAX COUNTY, New Mexico

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SOLANO COUNTY, CALIFORNIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TAYLOR COUNTY, FL, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLEN COUNTY, INDIANA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, NEBRASKA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWPORT COUNTY, RHODE ISLAND

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Charles COUNTY, MD, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OTTAWA COUNTY, OHIO, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE ROCKLAND COUNTY, NY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Richmond County, Virginia, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASATCH COUNTY, UTAH, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Westmoreland County, Virginia, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TOM GREEN COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Berks County, Pennsylvania, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, STONE COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VAL VERDE COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RED WILLOW COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE FOR HOWARD COUNTY, NEBRASKA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LANCASTER COUNTY, NE, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FERGUS COUNTY, MONTANA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN JOAQUIN COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LORAIN COUNTY, OHIO USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COSHOCTON COUNTY, OHIO, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAMILTON COUNTY, OHIO, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RAY COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JEFFERSON COUNTY, IDAHO, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LAWRENCE COUNTY, OHIO, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRANT COUNTY, WISCONSIN, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Nelson County, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST. FRANCOIS COUNTY, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LAFAYETTE COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RANDALL COUNTY, TX, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENVILLE COUNTY, SOUTH CAROLINA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, McCormick County, SC

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, McCURTAIN COUNTY, OK

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DICKENSON COUNTY, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARIPOSA_CO_CA, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Charles County, Maryland, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Essex County, Virginia, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Calvert County, Maryland, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Bradford County, Pennsylvania, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DESOTO COUNTY, FL, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FANNIN COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HEMPSTEAD COUNTY, AR

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHATHAM COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN JACINTO COUNTY, TX

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, New London County, CT

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Westmoreland County, PA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Sussex County, Delaware, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DELAWARE COUNTY, OK, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, UNION COUNTY, FLORIDA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAMILTON COUNTY, FLORIDA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALTON COUNTY, FL, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LANCASTER COUNTY, SC

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Rate Map Database, Allegheny County, Pennsylvania, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BARTOW COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CALDWELL PARISH, LOUISIANA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHIAWASSEE COUNTY, MICHIGAN, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FRANKLIN COUNTY, OHIO,USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, EL DORADO COUNTY, CALIFORNIA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GADSDEN COUNTY, FL, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LACLEDE COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLINTON COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, AUGUSTA COUNTY, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, OH, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Spartanburg County, South Carolina

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Rio Grande County, Colorado

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE,FREDERICK COUNTY, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Roosevelt COUNTY, New Mexico

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Linn County, Oregon, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TEHAMA COUNTY, CALIFORNIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Wythe County, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SULLIVAN COUNTY, PA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

Digital Flood Insurance Database Submission for Saline County, AR ,USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KITSAP COUNTY, WASHINGTON, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Northumberland County, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CADDO PARISH, LOUISIANA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FORT BEND COUNTY, TEXAS

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEDGWICK COUNTY, KANSAS, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JOHNSON COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

Digital Flood Insurance Database Submission for Boone County, AR ,USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CRAWFORD COUNTY, AR ,USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MONMOUTH COUNTY, NEW JERSEY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YORK COUNTY, PA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUSSEX COUNTY, NEW JERSEY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLEARFIELD COUNTY, PA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COOPER COUNTY, MISSOURI, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CAMERON COUNTY, PA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, NEW JERSEY

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FAYETTE COUNTY, GEORGIA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUFFOLK COUNTY, NEW YORK

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, INDIAN RIVER COUNTY, FL

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CAROLINE COUNTY, VA, USA

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST JOSEPH COUNTY, MI