Schema-Driven Interoperability of Biomedical Data Resources for Improved Knowledge Dissemination and Reuse

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Authors: Egon Willighagen, Tooba Abbassi‐Daloii, Anna Niehues, Magnus Palmblad, Hailiang Mei, Eleni Mina, Friederike Ehrhart, Danyel Jennen
Cited by: 2

Abstract

Biomedical data is scattered across diverse databases, each with a different scope and design, making integration and analysis challenging. This project creates an open, interoperable framework to connect these databases, enabling efficient access and data use. By applying schema harmonization, aligning database designs, and using open science approaches, it promotes data transparency, reusability, and interoperability. Our approach implements the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, ensuring analysis across databases is accurate and transparent, e.g., when combining gene expression data with gene variant knowledge. The resulting access to the integrated databases simplifies data exploration and maximizes the scientific insights.

Fields of Study & Subjects

Scientific Computing and Data Management Research Data Management Practices Biomedical Text Mining and Ontologies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
23 April 2026
Language
EN