[1] Development of CWL is focused particularly on serving the data-intensive sciences, such as bioinformatics,[2] medical imaging, astronomy, physics, and chemistry.

A key goal of the CWL is to allow the creation of a workflow that is portable and thus may be run reproducibly in different computational environments.

[3] The CWL originated from discussions in 2014 between Peter Amstutz, John Chilton, Nebojša Tijanić, and Michael R. Crusoe (at that time their respective affiliations were: Galaxy, Arvados, Seven Bridges, and Michigan State University) at the Open Bioinformatics Foundation BOSC 2014 codefest.

CWL is supported by multiple analysis runners and platforms[4] such as Apache Airflow (via CWL-Airflow [5]), Arvados, Rabix,[6] Cromwell workflow engine, Toil, REANA - Reusable Analyses and CWLEXEC for IBM Spectrum LSF, and was identified in 2017 as one of the future trends for bioinformatics pipeline development.

A member project of Software Freedom Conservancy, it publishes the CWL standards freely available via its GitHub repository under a permissive Apache License 2.0.