About

The Workflow Description Language (WDL) is a way to specify data processing workflows with a human-readable and -writeable syntax. WDL makes it straightforward to define analysis tasks, chain them together in workflows, and parallelize their execution. The language makes common patterns simple to express, while also admitting uncommon or complicated behavior; and strives to achieve portability not only across execution platforms, but also different types of users. Whether one is an analyst, a programmer, an operator of a production system, or any other sort of user, WDL should be accessible and understandable.

WDL was originally developed for genome analysis pipelines by the Broad Institute. As its community grew, both end users as well as other organizations using WDL for their own software, it became clear that there was a need to allow WDL to become a true community driven standard. The OpenWDL community has thus been formed to steward the WDL language specification and advocate its adoption.

Citation

To reference the Workflow Description Language and the WDL project in scholarly work, please use the following citation:

  • Voss K, Van der Auwera G and Gentry J. Full-stack genomics pipelining with GATK4 + WDL + Cromwell [version 1; not peer reviewed]. F1000Research 2017, 6(ISCB Comm J):1381 (slides) DOI:10.7490/f1000research.1114634.1

Governance

The WDL specification is entirely community driven; however, it is overseen by a Governance committee.

If you are interested in being involved in WDL governance, please join the Slack and post a message in the #general channel.

OpenWDL is led by a small core group who help govern the language specfication. Current members include:

  • Jeff Gentry, Fulcrum Genomics
  • Mike Lin, Chan Zuckerberg Initiative
  • Patrick Magee, DNAstack
  • Brian O’Connor, Sage Bionetworks
  • Christopher Llanwarne, Broad Institute
  • John Didion, Fulcrum Genomics
  • Michael Franklin, Centre for Population Genomics
  • Amy Paguirigan, Fred Hutch
  • Ruben Vorderman, Leiden University Medical Center
  • Venkat Malladi, Microsoft
  • Lee Pang, Amazon
  • Mark Schreiber, Amazon

Former Members

  • Brad Chapman
  • Abirami Prabhakaran
  • Geraldine Van der Auwera