 In many signs of new fields such as bioinformatics, medical imaging and astronomy, large quantities of data need to be analyzed. This can involve large-scale repetitive processes in all pipelines of different tools referred to as workflows. It can be very time-consumed to read data through all these different tools by hand and convert outputs to various formats with the compatible with the next step. Workflow management systems are designed to alleviate this problem by allowing these workflows to be expressed formally and providing the infrastructure to set up ex-teams to monitor them. This formal expression of workflows allows scientists to easily share and reuse them. Crucially, they can also be used to verify results of computation for published work. However, there are many competing standards for describing workflows, which is a various vision. Currently, there are about a few different data analysis workflows with no internal ability between them. The need has arisen to have a single common standard, so the Common Workflow Language Project was created. An open standard designed to express workflows led to a group to demonstrate text files. So that was the 60-second introduction to the Common Workflow Language Project. I'm Michael Crusoe. I'm one of the co-founders in the project lead and talking to you today from Vilnius, Lithuania. We work on standards for this other sort of workflow, not a publishing workflow that that did announce this workflow. But there's also a publishing story there. We really excited to, we were hoping to have been there in person, but to make connections across the scholarly creation and dissemination publishing workflows using standards. Another project I collaborate with is the researchobject.org standards, which is a data manifest or data container that brings these things together. And I think in the next breakout session, there'll be a group talking about this. So I hope to talk to you all remotely and see many of you around the world in the future too. Thanks.