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dc.contributor.authorMöller, Steffen
dc.contributor.authorPrescott, Stuart W.
dc.contributor.authorWirzenius, Lars
dc.contributor.authorReinholdtsen, Petter
dc.contributor.authorChapman, Brad
dc.contributor.authorPrins, Pjotr
dc.contributor.authorSoiland-Reyes, Stian
dc.contributor.authorKlötzl, Fabian
dc.contributor.authorBagnacani, Andrea
dc.contributor.authorKalaš, Matúš
dc.contributor.authorTille, Andreas
dc.contributor.authorCrusoe, Michael R.
dc.PublishedMöller S, Prescott, Wirzenius, Reinholdtsen P, Chapman B, Prins P, Soiland-Reyes S, Klötzl, Bagnacani, Kalaš M, Tille A, Crusoe MR. Robust Cross-Platform Workflows: How Technical and Scientific Communities Collaborate to Develop, Test and Share Best Practices for Data Analysis. Data Science and Engineering. 2017;2(3):232-244eng
dc.description.abstractInformation integration and workflow technologies for data analysis have always been major fields of investigation in bioinformatics. A range of popular workflow suites are available to support analyses in computational biology. Commercial providers tend to offer prepared applications remote to their clients. However, for most academic environments with local expertise, novel data collection techniques or novel data analysis, it is essential to have all the flexibility of open-source tools and open-source workflow descriptions. Workflows in data-driven science such as computational biology have considerably gained in complexity. New tools or new releases with additional features arrive at an enormous pace, and new reference data or concepts for quality control are emerging. A well-abstracted workflow and the exchange of the same across work groups have an enormous impact on the efficiency of research and the further development of the field. High-throughput sequencing adds to the avalanche of data available in the field; efficient computation and, in particular, parallel execution motivate the transition from traditional scripts and Makefiles to workflows. We here review the extant software development and distribution model with a focus on the role of integration testing and discuss the effect of common workflow language on distributions of open-source scientific software to swiftly and reliably provide the tools demanded for the execution of such formally described workflows. It is contended that, alleviated from technical differences for the execution on local machines, clusters or the cloud, communities also gain the technical means to test workflow-driven interaction across several software packages.en_US
dc.rightsAttribution CC BYeng
dc.subjectContinuous integration testingeng
dc.subjectCommon workflow languageeng
dc.subjectSoftware distributioneng
dc.subjectAutomated installationeng
dc.titleRobust Cross-Platform Workflows: How Technical and Scientific Communities Collaborate to Develop, Test and Share Best Practices for Data Analysisen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright 2017 The Author(s)en_US
dc.source.journalData Science and Engineering
dc.subject.nsiVDP::Matematikk og naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420
dc.subject.nsiVDP::Mathematics and natural scienses: 400::Information and communication science: 420

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