The Common Workflow Language (CWL) is a specification for describing analysis workflows and tools in a way that makes them portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. CWL is designed to meet the needs of data-intensive science, such as Bioinformatics, Medical Imaging, Astronomy, Physics, and Chemistry. CWL is developed by a multi-vendor working group consisting of organizations and individuals aiming to enable scientists to share data analysis workflows. The CWL project is maintained on Github and we follow the Open-Stand.org principles for collaborative open standards development. Legally, CWL is a member project of Software Freedom Conservancy and is formally managed by the elected CWL leadership team, however every-day project decisions are made by the CWL community which is open for participation by anyone. CWL builds on technologies such as JSON-LD for data modeling and Docker for portable runtime environments.
The Common Workflow Language (CWL) is a community-developed specification for interoperable scientific workflows, supported by multiple workflow engine vendors and open source projects. Started as a third-year project at The University of Manager and further developed as part of the BioExcel project, the CWL Viewer is available to visualize any CWL workflow definitions, show their annotations and composition.
The public CWL Viewer instance has become the de facto standard web visualization tool for workflows within the larger CWL community – the list of known workflows shows more than 2000 individual workflows have been visualized.
In 2017 the CWL Viewer was presented at the ISMB/ECCB conference where it won the F1000 Best Poster Award. The development and hosting of CWL Viewer is now being transitioned to Curii Corporation, an industry partner in the CWL project that is developing the Arvados platform.
CoE: BioExcel
This website is created and maintained by the project FocusCoE. FocusCoE has received funding from the European Union’s Horizon 2020 research and innovation programme under the grant agreement Nº 823964.