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Recording provenance of workflow runs with RO-Crate.
Leo, Simone; Crusoe, Michael R; Rodríguez-Navas, Laura; Sirvent, Raül; Kanitz, Alexander; De Geest, Paul; Wittner, Rudolf; Pireddu, Luca; Garijo, Daniel; Fernández, José M; Colonnelli, Iacopo; Gallo, Matej; Ohta, Tazro; Suetake, Hirotaka; Capella-Gutierrez, Salvador; de Wit, Renske; Kinoshita, Bruno P; Soiland-Reyes, Stian.
Afiliación
  • Leo S; Center for Advanced Studies, Research, and Development in Sardinia (CRS4), Pula (CA), Italy.
  • Crusoe MR; Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
  • Rodríguez-Navas L; DTL Projects, Utrecht, The Netherlands.
  • Sirvent R; Forschungszentrum Jülich, Jülich, Germany.
  • Kanitz A; Barcelona Supercomputing Center, Barcelona, Spain.
  • De Geest P; Barcelona Supercomputing Center, Barcelona, Spain.
  • Wittner R; Biozentrum, University of Basel, Basel, Switzerland.
  • Pireddu L; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
  • Garijo D; VIB Data Core, Gent, Belgium.
  • Fernández JM; Faculty of Informatics, Masaryk University, Brno, Czech Republic.
  • Colonnelli I; Institute of Computer Science, Masaryk University, Brno, Czech Republic.
  • Gallo M; BBMRI-ERIC, Graz, Austria.
  • Ohta T; Center for Advanced Studies, Research, and Development in Sardinia (CRS4), Pula (CA), Italy.
  • Suetake H; Ontology Engineering Group, Universidad Politécnica de Madrid, Madrid, Spain.
  • Capella-Gutierrez S; Barcelona Supercomputing Center, Barcelona, Spain.
  • de Wit R; Computer Science Department, Università degli Studi di Torino, Torino, Italy.
  • Kinoshita BP; Faculty of Informatics, Masaryk University, Brno, Czech Republic.
  • Soiland-Reyes S; Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Shizuoka, Japan.
PLoS One ; 19(9): e0309210, 2024.
Article en En | MEDLINE | ID: mdl-39255315
ABSTRACT
Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Flujo de Trabajo Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Flujo de Trabajo Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos