Abstract
While literature portals in the biomedical domain already enhance their search applications with ontological concepts, data portals offering biological primary data still use a classical keyword search. Similar to publications, biological primary data are described along meta information such as author, title, location and time which is stored in a separate file in XML format. Here, we introduce a semantic search for biological data based on metadata files. The search is running over 4.6 million datasets from GFBio - The German Federation for Biological Data (GFBio, https://www.gfbio.org), a national infrastructure for long-term preservation of biological data. The semantic search method used is query expansion. Instead of looking for originally entered keywords the search terms are expanded with related concepts from different biological vocabularies. Hosting our own Terminology Service with vocabularies that are tailored to the datasets, we demonstrate how ontological concepts are integrated into the search and how it improves the search result.
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Notes
- 1.
GBIF, http://www.gbif.org/.
- 2.
Data One, https://dataone.org/.
- 3.
Dryad, https://datadryad.org/.
- 4.
PANGAEA, https://www.pangaea.de/.
- 5.
BGBM, https://www.bgbm.org/.
- 6.
- 7.
Elasticsearch, https://www.elastic.co.
- 8.
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Acknowledgements
This work was funded by the Deutsche Forschungsgemeinschaft (DFG) within the scope of the GFBio project.
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Löffler, F. et al. (2017). Honey Bee Versus Apis Mellifera: A Semantic Search for Biological Data. In: Blomqvist, E., Hose, K., Paulheim, H., Ławrynowicz, A., Ciravegna, F., Hartig, O. (eds) The Semantic Web: ESWC 2017 Satellite Events. ESWC 2017. Lecture Notes in Computer Science(), vol 10577. Springer, Cham. https://doi.org/10.1007/978-3-319-70407-4_19
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DOI: https://doi.org/10.1007/978-3-319-70407-4_19
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