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    Rights statement: © 2014 Hettne et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

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Structuring research methods and data with the research object model: genomics workflows as a case study

Research output: Contribution to journalJournal articlepeer-review

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  • Kristina M. Hettne
  • Harish Dharuri
  • Jun Zhao
  • Katherine Wolstencroft
  • Khalid Belhajjame
  • Stian Soiland-Reyes
  • Eleni Mina
  • Mark Thompson
  • Don Cruickshank
  • Lourdes Verdes-Montenegro
  • Julian Garrido
  • David de Roure
  • Oscar Corcho
  • Graham Klyne
  • Reinout van Schouwen
  • Peter A. C. 't Hoen
  • Sean Bechhofer
  • Carole Goble
  • Marco Roos
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Article number41
<mark>Journal publication date</mark>18/09/2014
<mark>Journal</mark>Journal of Biomedical Semantics
Volume5
Number of pages16
Publication StatusPublished
<mark>Original language</mark>English

Abstract

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e. g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows.

Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?".

Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

Availability: The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/ro

Bibliographic note

© 2014 Hettne et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 39 pages, 13 figures, submitted to Journal of Biomedical Semantics on 2013-05-13, resubmitted after review 2013-11-09. Research Object homepage: http://www.researchobject.org/