Presenter: Mahnoor Zulfiqar, Friedrich Schiller University Jena @zmahnoor
- Session 1:
(Americas-EMEA) Monday, February 27th 09:00 - 13:00 US EST / 14:00 - 18:00 UTC - Session 2:
(EMEA-APAC) Wednesday, March 1st 07:00 - 11:00 UTC / 16:00 - 20:00 Japanese Standard Time
In the age of high-throughput data, computational workflows have made data processing tasks flexible, manageable, and automated. To administer different computational activities in a workflow, different workflow management systems (WMS) are used that necessitate a sophisticated level of standardisation. Standardisation and reproducibility can be achieved by using standard formats for specifying workflows, such as Common Workflow Language (CWL), and provenance gathering with the standard W3C PROV ontology model. During initial stages of workflow design, the FAIR principles, specifically Reusability, are often not followed. And such workflows remain “unmanaged”. Over the years, an increase is observed in metabolomics workflows used to analyze chemical information. To support standardisation and reproducibility in these workflows, we specified and executed the “Metabolome Annotation Workflow” (MAW), which performs chemical structure identification, in CWL and collected provenance using CWLProv to ensure the interoperability and reusability of the workflow. To further improve reproducibility, Docker containers preserving the runtime environment are available for executing the computational activities of the workflow.
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