EDAM is a domain ontology of data analysis and data management in bio- and other sciences, and science-based applications. It comprises concepts related to analysis, modelling, optimisation, and data life cycle. Targetting usability by diverse users, the structure of EDAM is relatively simple, divided into 4 main sections: Topic, Operation, Data (incl. Identifier), and Format.
EDAM is particularly suitable for semantic annotations and categorisation of diverse resources related to data analysis and management: e.g. tools, workflows, learning materials, or standards. EDAM is also useful in data management itself, for recording provenance metadata of processed data.
EDAM can be browsed online at the NCBO BioPortal, at OLS, and in the EDAM Browser.
The latest version is always downloable from http://edamontology.org/EDAM.owl. For older versions, see http://edamontology.org/page#Download or /releases.
Comprehensive documentation and guidelines are available via readthedocs (maintained here; currently not 100% up-to-date).
A quick overview is at the https://edamontology.org home page.
If you refer to EDAM or its part in a scholarly publication, please cite:
Melissa Black, Lucie Lamothe, Hager Eldakroury, Mads Kierkegaard, Ankita Priya, Anne Machinda, Uttam Singh Khanduja, Drashti Patoliya, Rashika Rathi, Tawah Peggy Che Nico, Gloria Umutesi, Claudia Blankenburg, Anita Op, Precious Chieke, Omodolapo Babatunde, Steve Laurie, Steffen Neumann, Veit Schwämmle, Ivan Kuzmin, Chris Hunter, Jonathan Karr, Jon Ison, Alban Gaignard, Bryan Brancotte, Hervé Ménager, Matúš Kalaš (2022). EDAM: the bioscientific data analysis ontology (update 2021) [version 1; not peer reviewed]. F1000Research, 11(ISCB Comm J): 1. Poster. Open access
DOI representing all permanent versions, resolving to the latest: