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SCALEUS-FD: A FAIR Data Tool for Biomedical Applications.

Arnaldo PereiraRui Pedro LopesJosé Luís Oliveira
Published in: BioMed research international (2020)
The Semantic Web and Linked Data concepts and technologies have empowered the scientific community with solutions to take full advantage of the increasingly available distributed and heterogeneous data in distinct silos. Additionally, FAIR Data principles established guidelines for data to be Findable, Accessible, Interoperable, and Reusable, and they are gaining traction in data stewardship. However, to explore their full potential, we must be able to transform legacy solutions smoothly into the FAIR Data ecosystem. In this paper, we introduce SCALEUS-FD, a FAIR Data extension of a legacy semantic web tool successfully used for data integration and semantic annotation and enrichment. The core functionalities of the solution follow the Semantic Web and Linked Data principles, offering a FAIR REST API for machine-to-machine operations. We applied a set of metrics to evaluate its "FAIRness" and created an application scenario in the rare diseases domain.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • data analysis
  • risk assessment
  • deep learning
  • single cell