International FAIR Convergence Symposium 2020 Workshop on FAIR Workflows

Scientific workflows capture precise descriptions of the steps and data dependencies needed to carry out computational experiments in many areas of Science, ranging from Astrophysics to Bioinformatics or Geosciences. In order to promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become findable, accessible, understandable, reusable, and citable so that author’s credit is attributed fairly and accurately.

The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. Workshop goals While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists. This workshop will provide a forum to discuss and review the core FAIR principles for computational workflows both considering the problem of designing and developing FAIR workflows and evaluating the ability of workflows (computational analysis pipelines) to provide FAIR data and FAIR software.

As a result, we aim to obtain feedback from the scientific workflow community of users and developers to better understand the current limitations and what are the next steps (in terms of guidelines or standardization activities) to push forward.


Teams: FAIR Computational Workflows

Carole Goble

30th Nov 2020 at 21:13

30th Nov 2020 at 21:13



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