Work

foundingGIDE Deliverable D2.1 Landscape analysis of existing ontologies and recommendations on a set of imaging ontologies

Year: 2025

Type: article

Abstract: This deliverable presents a comprehensive analysis of the current landscape of ontologies relevant to biological and preclinical imaging data. Here we identify and evaluate existing ontologies and integrate the findings into recommendations for supporting harmonized image data representation and enable interoperability of global image data resources. The recommendations from D2.1 will also serve as a guidance for data producers to adopt, in order to make their data easier to incorporate in open data repositories. This version has been approved by the EC.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16794947

Authors: Sherwood, François, Longo, Dario, Maria, Mirza

Institutions: European Bioinformatics Institute, European Molecular Biology Laboratory, European Molecular Biology Laboratory, National Research Council, Euro-BioImaging ERIC

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: European Commission

Award: Founding a Global Image Data Ecosystem