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Briefings in Bioinformatics Advance Access published online on May 14, 2007
Briefings in Bioinformatics, doi:10.1093/bib/bbm015
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© The Author 2007. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

Using provenance to manage knowledge of In Silico experiments

Robert Stevens, Jun Zhao and Carole Goble

Corresponding author. Robert Stevens, BioHealth and Information Management Groups, School of Computer Science, University of Manchester, Oxford Road, Manchester, UK, M13 9PL. E-mail: Robert.Stevens{at}manchester.ac.uk

This article offers a briefing in one of the knowledge management issues of in silico experimentation in bioinformatics. Recording of the provenance of an experiment—what was done; where, how and why, etc. is an important aspect of scientific best practice that should be extended to in silico experimentation. We will do this in the context of eScience which has been part of the move of bioinformatics towards an industrial setting. Despite the computational nature of bioinformatics, these analyses are scientific and thus necessitate their own versions of typical scientific rigour. Just as recording who, what, why, when, where and how of an experiment is central to the scientific process in laboratory science, so it should be in silico science. The generation and recording of these aspects, or provenance, of an experiment are necessary knowledge management goals if we are to introduce scientific rigour into routine bioinformatics. In Silico experimental protocols should themselves be a form of managing the knowledge of how to perform bioinformatics analyses. Several systems now exist that offer support for the generation and collection of provenance information about how a particular in silico experiment was run, what results were generated, how they were generated, etc. In reviewing provenance support, we will review one of the important knowledge management issues in bioinformatics.

Keywords: In Silico experiments, provenance, workflow, data derivation, validation and verification of results

Submitted: January 15, 2007. Received (in revised form): March 18, 2007.


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