ArticleJournal of biomedical semantics2016
Generation of open biomedical datasets through ontology-driven transformation and integration processes.
Article in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- An epidemiological knowledge graph extracted from the World Health Organization's Disease Outbreak News.Scientific data · 2025Article
- Representation of chemistry transport models simulations using knowledge graphs.Journal of cheminformatics · 2025Article
- Ontologies as the semantic bridge between artificial intelligence and healthcare.Frontiers in digital health · 2025Article
- Use of Metadata-Driven Approaches for Data Harmonization in the Medical Domain: Scoping Review.JMIR medical informatics · 2024Article
- BioHackathon 2015: Semantics of data for life sciences and reproducible research.F1000Research · 2020Article
- The Semantic Data Dictionary - An Approach for Describing and Annotating Data.Data intelligence · 2020Article
- Linked open data-based framework for automatic biomedical ontology generation.BMC bioinformatics · 2018Article
- Long-term preservation of biomedical research data.F1000Research · 2018Article
- Analysis and visualization of disease courses in a semantically-enabled cancer registry.Journal of biomedical semantics · 2017Article
- Semantic annotation in biomedicine: the current landscape.Journal of biomedical semantics · 2017Review
- PIBAS FedSPARQL: a web-based platform for integration and exploration of bioinformatics datasets.Journal of biomedical semantics · 2017Article
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Authors and funding
4 authors.
Funding
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Abstract
backgroundBiomedical research usually requires combining large volumes of data from multiple heterogeneous sources, which makes difficult the integrated exploitation of such data. The Semantic Web paradigm offers a natural technological space for data integration and exploitation by generating content readable by machines. Linked Open Data is a Semantic Web initiative that promotes the publication and sharing of data in machine readable semantic formats.
methodsWe present an approach for the transformation and integration of heterogeneous biomedical data with the objective of generating open biomedical datasets in Semantic Web formats. The transformation of the data is based on the mappings between the entities of the data schema and the ontological infrastructure that provides the meaning to the content. Our approach permits different types of mappings and includes the possibility of defining complex transformation patterns. Once the mappings are defined, they can be automatically applied to datasets to generate logically consistent content and the mappings can be reused in further transformation processes.
resultsThe results of our research are (1) a common transformation and integration process for heterogeneous biomedical data; (2) the application of Linked Open Data principles to generate interoperable, open, biomedical datasets; (3) a software tool, called SWIT, that implements the approach. In this paper we also describe how we have applied SWIT in different biomedical scenarios and some lessons learned.
conclusionsWe have presented an approach that is able to generate open biomedical repositories in Semantic Web formats. SWIT is able to apply the Linked Open Data principles in the generation of the datasets, so allowing for linking their content to external repositories and creating linked open datasets. SWIT datasets may contain data from multiple sources and schemas, thus becoming integrated datasets.
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