A linked data approach to sharing workflows and workflow results

  • Authors:

  • Marco Roos;Sean Bechhofer;Jun Zhao;Paolo Missier;David R. Newman;David De Roure;M. Scott Marshall

  • Affiliations:

  • BioSemantics Group, Department of Human and Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands and Informatics Institute, Faculty of Science, University of Amsterdam, Ams ...;School of Computer Science, The University of Manchester, Manchester, UK;Department of Zoology, University of Oxford, Oxford;School of Computer Science, The University of Manchester, Manchester, UK;School of Electronics and Computer Science, University of Southampton, Southampton, UK;Oxford e-Research Centre, University of Oxford, Oxford, UK;Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands and Department of Medical Statistics and Bioinformatics, Leiden University Medical Centre, Leiden, Th ...

  • Venue:
  • ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
  • Year:
  • 2010

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Abstract

A bioinformatics analysis pipeline is often highly elaborate, due to the inherent complexity of biological systems and the variety and size of datasets. A digital equivalent of the 'Materials and Methods' section in wet laboratory publications would be highly beneficial to bioinformatics, for evaluating evidence and examining data across related experiments, while introducing the potential to find associated resources and integrate them as data and services. We present initial steps towards preserving bioinformatics 'materials and methods' by exploiting the workflow paradigm for capturing the design of a data analysis pipeline, and RDF to link the workflow, its component services, runtime provenance, and a personalized biological interpretation of the results. An example shows the reproduction of the unique graph of an analysis procedure, its results, provenance, and personal interpretation of a text mining experiment. It links data from Taverna, myExperiment.org, BioCatalogue.org, and ConceptWiki. org. The approach is relatively 'light-weight' and unobtrusive to bioinformatics users.