Semantic Integration and Enrichment of Heterogeneous Biological Databases.

Détails

ID Serval
serval:BIB_3D396F44C44D
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Semantic Integration and Enrichment of Heterogeneous Biological Databases.
Périodique
Methods in molecular biology
Auteur(s)
Sima A.C., Stockinger K., de Farias T.M., Gil M.
ISSN
1940-6029 (Electronic)
ISSN-L
1064-3745
Statut éditorial
Publié
Date de publication
2019
Peer-reviewed
Oui
Volume
1910
Pages
655-690
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Biological databases are growing at an exponential rate, currently being among the major producers of Big Data, almost on par with commercial generators, such as YouTube or Twitter. While traditionally biological databases evolved as independent silos, each purposely built by a different research group in order to answer specific research questions; more recently significant efforts have been made toward integrating these heterogeneous sources into unified data access systems or interoperable systems using the FAIR principles of data sharing. Semantic Web technologies have been key enablers in this process, opening the path for new insights into the unified data, which were not visible at the level of each independent database. In this chapter, we first provide an introduction into two of the most used database models for biological data: relational databases and RDF stores. Next, we discuss ontology-based data integration, which serves to unify and enrich heterogeneous data sources. We present an extensive timeline of milestones in data integration based on Semantic Web technologies in the field of life sciences. Finally, we discuss some of the remaining challenges in making ontology-based data access (OBDA) systems easily accessible to a larger audience. In particular, we introduce natural language search interfaces, which alleviate the need for database users to be familiar with technical query languages. We illustrate the main theoretical concepts of data integration through concrete examples, using two well-known biological databases: a gene expression database, Bgee, and an orthology database, OMA.
Mots-clé
Database Management Systems, Databases, Factual, Databases, Genetic, Humans, Models, Theoretical, Semantic Web, Semantics, Systems Integration, Data integration, Keyword search, Knowledge representation, Ontology-based data access, Query processing, RDF stores, Relational databases
Pubmed
Open Access
Oui
Création de la notice
19/08/2019 14:53
Dernière modification de la notice
17/01/2020 7:26
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