Data Integration in the Life Sciences: Fun, Findings and Frustrations
DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
International Journal of Sensor Networks
Open workflow infrastructure: a research agenda
Proceedings of the 1st International Workshop on Workflow Approaches to New Data-centric Science
SEGEDMA: Sensor grid enhancement data management system for Health Care computing
Expert Systems with Applications: An International Journal
Ubiquitous Healthcare Computing with Sensor Grid Enhancement with Data Management System (SEGEDMA)
Journal of Medical Systems
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The activity of e-Science involves making discoveries by analysing data to find new knowledge. Discoveries of value cannot be made by simply performing a pre-defined set of steps to produce a result. Rather, there is an original, creative aspect to the activity that by its nature cannot be automated. In addition to finding new knowledge, discovery therefore also concerns finding a process to find new knowledge. How discovery processes are modelled is therefore key to effectively practicing e-Science. We argue that since a discovery process instance serves a similar purpose to a mathematical proof it should have similar properties, namely it allows results to be deterministically reproduced when re-executed and that intermediate results can be viewed to aid examination and comprehension. We examine the issues involved for software environments used to make discoveries to preserve these properties, and show how they are tackled in the Discovery Net system. Copyright © 2006 John Wiley & Sons, Ltd.