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Ontology-Based Querying with Bio2RDF’s Linked Open Data

BACKGROUND: A key activity for life scientists in this post “-omics” age involves searching for and integrating biological data from a multitude of independent databases. However, our ability to find relevant data is hampered by non-standard web and database interfaces backed by an enormous variety...

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Autores principales: Callahan, Alison, Cruz-Toledo, José, Dumontier, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632999/
https://www.ncbi.nlm.nih.gov/pubmed/23735196
http://dx.doi.org/10.1186/2041-1480-4-S1-S1
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author Callahan, Alison
Cruz-Toledo, José
Dumontier, Michel
author_facet Callahan, Alison
Cruz-Toledo, José
Dumontier, Michel
author_sort Callahan, Alison
collection PubMed
description BACKGROUND: A key activity for life scientists in this post “-omics” age involves searching for and integrating biological data from a multitude of independent databases. However, our ability to find relevant data is hampered by non-standard web and database interfaces backed by an enormous variety of data formats. This heterogeneity presents an overwhelming barrier to the discovery and reuse of resources which have been developed at great public expense.To address this issue, the open-source Bio2RDF project promotes a simple convention to integrate diverse biological data using Semantic Web technologies. However, querying Bio2RDF remains difficult due to the lack of uniformity in the representation of Bio2RDF datasets. RESULTS: We describe an update to Bio2RDF that includes tighter integration across 19 new and updated RDF datasets. All available open-source scripts were first consolidated to a single GitHub repository and then redeveloped using a common API that generates normalized IRIs using a centralized dataset registry. We then mapped dataset specific types and relations to the Semanticscience Integrated Ontology (SIO) and demonstrate simplified federated queries across multiple Bio2RDF endpoints. CONCLUSIONS: This coordinated release marks an important milestone for the Bio2RDF open source linked data framework. Principally, it improves the quality of linked data in the Bio2RDF network and makes it easier to access or recreate the linked data locally. We hope to continue improving the Bio2RDF network of linked data by identifying priority databases and increasing the vocabulary coverage to additional dataset vocabularies beyond SIO.
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spelling pubmed-36329992013-04-25 Ontology-Based Querying with Bio2RDF’s Linked Open Data Callahan, Alison Cruz-Toledo, José Dumontier, Michel J Biomed Semantics Proceedings BACKGROUND: A key activity for life scientists in this post “-omics” age involves searching for and integrating biological data from a multitude of independent databases. However, our ability to find relevant data is hampered by non-standard web and database interfaces backed by an enormous variety of data formats. This heterogeneity presents an overwhelming barrier to the discovery and reuse of resources which have been developed at great public expense.To address this issue, the open-source Bio2RDF project promotes a simple convention to integrate diverse biological data using Semantic Web technologies. However, querying Bio2RDF remains difficult due to the lack of uniformity in the representation of Bio2RDF datasets. RESULTS: We describe an update to Bio2RDF that includes tighter integration across 19 new and updated RDF datasets. All available open-source scripts were first consolidated to a single GitHub repository and then redeveloped using a common API that generates normalized IRIs using a centralized dataset registry. We then mapped dataset specific types and relations to the Semanticscience Integrated Ontology (SIO) and demonstrate simplified federated queries across multiple Bio2RDF endpoints. CONCLUSIONS: This coordinated release marks an important milestone for the Bio2RDF open source linked data framework. Principally, it improves the quality of linked data in the Bio2RDF network and makes it easier to access or recreate the linked data locally. We hope to continue improving the Bio2RDF network of linked data by identifying priority databases and increasing the vocabulary coverage to additional dataset vocabularies beyond SIO. BioMed Central 2013-04-15 /pmc/articles/PMC3632999/ /pubmed/23735196 http://dx.doi.org/10.1186/2041-1480-4-S1-S1 Text en Copyright © 2013 Callahan et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Callahan, Alison
Cruz-Toledo, José
Dumontier, Michel
Ontology-Based Querying with Bio2RDF’s Linked Open Data
title Ontology-Based Querying with Bio2RDF’s Linked Open Data
title_full Ontology-Based Querying with Bio2RDF’s Linked Open Data
title_fullStr Ontology-Based Querying with Bio2RDF’s Linked Open Data
title_full_unstemmed Ontology-Based Querying with Bio2RDF’s Linked Open Data
title_short Ontology-Based Querying with Bio2RDF’s Linked Open Data
title_sort ontology-based querying with bio2rdf’s linked open data
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632999/
https://www.ncbi.nlm.nih.gov/pubmed/23735196
http://dx.doi.org/10.1186/2041-1480-4-S1-S1
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