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|Publication type:||Book part|
|Type of review:||Editorial review|
|Title:||Semantic integration and enrichment of heterogeneous biological databases|
de Farias, Tarcisio Mendes
|Published in:||Evolutionary genomics : statistical and computational methods|
|Editors of the parent work:||Anisimova, Maria|
|Series:||Methods in Molecular Biology|
|Publisher / Ed. Institution:||Springer|
|Publisher / Ed. Institution:||New York|
|Subjects:||Data integration; Keyword search; Knowledge representation; Ontology-based data access; Query processing; RDF store; Relational database|
|Subject (DDC):||005: Computer programming, programs and data|
|Abstract:||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.|
|Fulltext version:||Published version|
|License (according to publishing contract):||CC BY 4.0: Attribution 4.0 International|
|Departement:||School of Engineering |
Life Sciences and Facility Management
|Organisational Unit:||Institute of Applied Information Technology (InIT) |
Institute of Computational Life Sciences (ICLS)
|Published as part of the ZHAW project:||Bio-SODA: Enabling Complex, Semantic Queries to Bioinformatics Databases through Intuitive Searching over Data|
|Appears in collections:||Publikationen School of Engineering|
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|2019_Semantic Integration and Enrichment of Heterogeneous_Sima_Stockinger_etal_EvolutionaryGenomics.pdf||841.13 kB||Adobe PDF|
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Sima, A.-C., Stockinger, K., de Farias, T. M., & Gil, M. (2019). Semantic integration and enrichment of heterogeneous biological databases. In M. Anisimova (Ed.), Evolutionary genomics : statistical and computational methods (pp. 655–690). Springer. https://doi.org/10.21256/zhaw-3138
Sima, A.-C. et al. (2019) ‘Semantic integration and enrichment of heterogeneous biological databases’, in M. Anisimova (ed.) Evolutionary genomics : statistical and computational methods. New York: Springer, pp. 655–690. Available at: https://doi.org/10.21256/zhaw-3138.
A.-C. Sima, K. Stockinger, T. M. de Farias, and M. Gil, “Semantic integration and enrichment of heterogeneous biological databases,” in Evolutionary genomics : statistical and computational methods, M. Anisimova, Ed. New York: Springer, 2019, pp. 655–690. doi: 10.21256/zhaw-3138.
Sima, Ana-Claudia, et al. “Semantic Integration and Enrichment of Heterogeneous Biological Databases.” Evolutionary Genomics : Statistical and Computational Methods, edited by Maria Anisimova, Springer, 2019, pp. 655–90, https://doi.org/10.21256/zhaw-3138.
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