EDAM, the life-science ontology for data analysis and management

Lucie Lamothe (1) , Alban Gaignard (2) , Mads Kierkegaard (3) , Hager Eldakroury , Melissa Black , Bryan Brancotte (4) , Jon Ison (1) , Veit Schwämmle (3) , Matúš Kalaš (5) , Hervé Ménager (1, 4)

1 IFB-CORE - Institut Français de Bioinformatique
2 ITX-lab - ITX-lab unité de recherche de l'institut du thorax UMR1087 UMR6291
3 SDU - University of Southern Denmark
4 Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics
5 UiB - University of Bergen

EDAM is a domain ontology of data analysis and data management in life sciences. It comprises concepts related to analysis, modeling, optimization, and data life-cycle, and is divided into 4 main sections: topics, operations, data, and formats.EDAM is used in numerous resources, for example bio.tools, Galaxy, CWL, Debian, BioSimulators, FAIRsharing, or the ELIXIR Europe training portal TeSS. Thanks to the annotations with EDAM, tools, workflows, standards, data, and learning materials are easier to find, compare, choose, and integrate. EDAM contributes to open science by allowing semantic annotation of research products, thus making them more understandable, findable, and comparable.EDAM is continuously evolving and expanding by improving the implementation of links to external resources (including other ontologies), definitions, and the overall quality, or the addition of new concepts. EDAM is developed in a participatory and transparent fashion, within a broad and growing community of contributors. This development model, based on the contribution of a large number of scientific experts, therefore comes with its own set of challenges.To ease the contribution processes, users can explore graphically the ontology and its most useful features using the EDAM Browser web interface.To streamline and accelerate the evolution of EDAM, we have developed and integrated a set of tools that automate the quality control and release process for the ontology. In addition to ensuring the global consistency of EDAM, it enforces edition best practices both at the syntactic and semantic levels. These tools have been integrated in a continuous integration (CI) pipeline, automated using GitHub Actions in the source-code repository.These tools participate in the improvement of EDAM’s contribution process and visibility by the community.

Mots clés: Ontology; Life sciences; Open Science; FAIR; Computational tools; Learning materials; Standards; Data management

Domaines: Sciences du Vivant [q-bio]; Informatique [cs]

Lucie Lamothe, Alban Gaignard, Mads Kierkegaard, Hager Eldakroury, Melissa Black, et al.. EDAM, the life-science ontology for data analysis and management. JOBIM, Jul 2022, Rennes, France. ⟨10.5281/zenodo.6769072⟩. ⟨hal-03702557⟩