Presenter: Pavlo Lutsik, DKFZ and KU Leuven
- Session 2:
(EMEA-APAC) Wednesday, March 1st 07:00 - 11:00 UTC / 16:00 - 20:00 Japanese Standard Time
Major challenges that affect reproducibility in scientific data analysis include: (i) interoperability, i.e. compatibility of tools input and output data types that determines their capacity for being connected into data analytical workflows; (ii) portability, i.e. ability to deploy software developed on a certain platform to other computational environments; (iii) scalability, i.e. supporting the analysis of ever-increasing amounts of data; and, the less acknowledged one, (iv) accessibility, i.e. being comprehensive and manageable to researchers with limited computational background and skills. In the attempt to mitigate some of these problems, we aimed to provide an open and fully interoperable solution that would make most of the benefits provided by state-of-the-art solutions for each of the challenge above. Here we propose WorkflUX, a lightweight and easy to install platform for seamless and user-friendly deployment of scientific workflows to an unlimited set of computational environments. WorkflUX supports interoperable analyses through workflow definition languages, foremost CWL, harnesses portability through containerisation features, scalability is supported by configurable execution backends and intuitive web-based user interface guarantees accessibility to a broad range of researchers.
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