Abstract
Making data FAIR is an elaborate task. Hospitals and/or departments have to invest into technologies usually unknown and often do not have the resources to make data FAIR. Our work aims to provide a framework and tooling where users can easily make their data (more) FAIR. This framework uses RDF and OWL-based inferencing to annotate existing databases or comma-separated files. For every database, a custom ontology is build based on the database schema, which can be annotated to describe matching standardized terminologies. In this work, we describe the tooling developed, and the current implementation in an institutional datawarehouse pertaining over 3000 rectal cancer patients. We report on the performance (time) of the extraction and annotation process by the developed tooling. Furthermore, we do show that annotation of existing databases using OWL2-based reasoning is possible. Furthermore, we show that the ontology extracted from existing databases can provide a description framework to describe and annotate existing data sources. This would target mostly the “Interoperable” aspect of FAIR.
Original language | English |
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Title of host publication | Semantic Web Applications and Tools for Health Care and Life Sciences |
Pages | 94-101 |
Number of pages | 8 |
Volume | 2849 |
Publication status | Published - 1 Jan 2019 |
Event | 12th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences - Edinburgh, United Kingdom Duration: 10 Dec 2019 → 11 Dec 2019 Conference number: 12 |
Publication series
Series | CEUR Workshop Proceedings |
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ISSN | 1613-0073 |
Conference
Conference | 12th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences |
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Abbreviated title | SWAT4HCLS 2019 |
Country/Territory | United Kingdom |
City | Edinburgh |
Period | 10/12/19 → 11/12/19 |
Keywords
- Annotations
- FAIR
- Linked data
- Terminologies