TY - JOUR

T1 - Using provenance to manage knowledge of In Silico experiments

AU - Stevens, Robert

AU - Zhao, Jun

AU - Goble, Carole

PY - 2007/5

Y1 - 2007/5

N2 - 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.

AB - 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.

KW - In Silico experiments

KW - provenance

KW - workflow

KW - data derivation

KW - validation and verification of results

U2 - 10.1093/bib/bbm015

DO - 10.1093/bib/bbm015

M3 - Journal article

VL - 8

SP - 183

EP - 194

JO - Briefings in Bioinformatics

JF - Briefings in Bioinformatics

SN - 1467-5463

IS - 3

ER -