EOSC-Life Workflow Collaboratory for the Life Sciences
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Published:2023-09-07
Issue:
Volume:1
Page:
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ISSN:2941-296X
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Container-title:Proceedings of the Conference on Research Data Infrastructure
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language:
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Short-container-title:Proc Conf Res Data Infrastr
Author:
Goble CaroleORCID, Bacall Finn, Soiland-Reyes Stian, Owen Stuart, Eguinoa Ignacio, Droesbeke Bert, Ménager Hervé, Rodriguez-Navas Laura, Fernández José M.ORCID, Grüning BjörnORCID, Leo Simone, Pireddu LucaORCID, Crusoe MichaelORCID, Gustafsson Johan, Capella-Gutierrez SalvadorORCID, Coppens Frederik
Abstract
Workflows have become a major tool for the processing of Research Data, for example, data collection and data cleaning pipelines, data analytics, and data update feeds populating public archives. The EOSC-Life Research Infrastructure Cluster project brought together Europe’s Life Science Research Infrastructures to create an Open, Digital and Collaborative space for biological and medical research to develop a cloud-based Workflow Collaboratory. As adopting FAIR practices extends beyond data, the Workflow Collaboratory drives the implementation of FAIR computational workflows and tools. It fosters tool-focused collaborations and reuse via the sharing of data analysis workflows and offers an ecosystem of services for researchers and workflow specialists to find, use and reuse workflows. It’s web-friendly Digital Object Metadata Framework, based on RO-Crate and Bioschemas, supports the description and exchange of workflows across the services.
Funder
H2020 Research Infrastructures Bioplatforms Australia
Publisher
TIB Open Publishing
Reference15 articles.
1. T. Reiter, P.T. Brooks, L. Irber, S.E.K. Joslin, C.M. Reid, C. Scott, C.T. Brown, N.T. Pierce-Ward, “Streamlining data-intensive biology with workflow systems”, GigaSci-ence, vol.10, no.1, pp:1-19, January 2021, https://doi.org/10.1093/gigascience/giaa140 2. C. Goble, S. Cohen-Boulakia, S. Soiland-Reyes, D. Garijo, Y. Gil, M.R. Crusoe, K. Peters, D. Schober, “FAIR Computational Workflows. Data Intelligence” vol.2, no.1, pp:108–121, 2020, https://doi.org/10.1162/dint_a_00033 3. T. Kluyver, B. Ragan-Kelley, F. Pérez, B.E. Granger, M. Bussonnier, J. Frederic, K. Kelley, J.B. Hamrick, J. Grout, S. Corlay et al “Jupyter notebooks—a publishing for-mat for reproducible computational workflows” In F Loizides, B Scmidt (eds) Interna-tional conference on electronic publishing. IOS Press, ELPUB, Göttingen, 2016, pp:87–90 4. P. Di Tommaso, M. Chatzou, E. Floden, P.P. Barja, E. Palumbo, C. Notredame, “Nextflow enables reproducible computational workflows”. Nat Biotechnol vol.35, pp:316–319, 2017, https://doi.org/10.1038/nbt.3820 5. J. Köster, S. Rahmann, “Snakemake—a scalable bioinformatics workflow engine”, Bioinformatics, vol.28, no.19, pp:2520–2522, October 2012, https://doi.org/10.1093/bioinformatics/bts480
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