The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated research claims, and a steep learning curve. To address some of these challenges and lay the groundwork for transforming workflows research and development, the WorkflowsRI and ExaWorks projects partnered to bring the international workflows community together. This paper reports on discussions and findings from two virtual "Workflows Community Summits" (January and April, 2021). The overarching goals of these workshops were to develop a view of the state of the art, identify crucial research challenges in the workflows community, articulate a vision for potential community efforts, and discuss technical approaches for realizing this vision. To this end, participants identified six broad themes: FAIR computational workflows; AI workflows; exascale challenges; APIs, interoperability, reuse, and standards; training and education; and building a workflows community. We summarize discussions and recommendations for each of these themes.
@article{arxiv.2110.02168,
title = {A Community Roadmap for Scientific Workflows Research and Development},
author = {Rafael Ferreira da Silva and Henri Casanova and Kyle Chard and Ilkay Altintas and Rosa M Badia and Bartosz Balis and Tainã Coleman and Frederik Coppens and Frank Di Natale and Bjoern Enders and Thomas Fahringer and Rosa Filgueira and Grigori Fursin and Daniel Garijo and Carole Goble and Dorran Howell and Shantenu Jha and Daniel S. Katz and Daniel Laney and Ulf Leser and Maciej Malawski and Kshitij Mehta and Loïc Pottier and Jonathan Ozik and J. Luc Peterson and Lavanya Ramakrishnan and Stian Soiland-Reyes and Douglas Thain and Matthew Wolf},
journal= {arXiv preprint arXiv:2110.02168},
year = {2022}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2103.09181