It is not enough to be able to just run an e-Science in silico experiment; it is also vital to be able to understand and interpret the outputs of those experiments. The results have little value if other scientists, or even the same scientist at a later date, are unable to identify their origin, or provenance. In myGrid, in silico experiments are run as workflows; these produce three kinds of results: data outcomes, knowledge outcomes and provenance about the experiment. These results have a complex interlinking relationship between each other, within the context of the workflow that gave rise to them, as well as across workflows executed in the same or a different study. This poster describes the kind of provenance data recorded in myGrid during a workflow. It introduces myGrid's provenance data model and the Semantic Web-based technology used to support provenance-based tasks. These tasks include the verification and validation of results; the sharing and annotation of results; and the management of resources. For e-Science to succeed it must have provenance data support as its cornerstone.
[1]
Sean Martin,et al.
Globally distributed object identification for biological knowledgebases
,
2004,
Briefings Bioinform..
[2]
Matthew R. Pocock,et al.
Taverna: a tool for the composition and enactment of bioinformatics workflows
,
2004,
Bioinform..
[3]
V. Vianu,et al.
Edinburgh Why and Where: A Characterization of Data Provenance
,
2017
.
[4]
Carole A. Goble,et al.
Exploring Williams-Beuren syndrome using myGrid
,
2004,
ISMB/ECCB.
[5]
D. A. Quan,et al.
How to make a semantic web browser
,
2004,
WWW '04.
[6]
Carole A. Goble,et al.
Semantically Linking and Browsing Provenance Logs for E-science
,
2004,
ICSNW.
[7]
Luc Moreau,et al.
Recording and Reasoning over Data Provenance in Web and Grid Services
,
2003,
OTM.