Workflow technologies provide scientific researchers with a flexible problem-solving environment, by facilitating the creation and execution of experiments from a pool of available services. In this paper we argue that in order to better characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process. Current workflow technologies do not incorporate any representation of such experimental constraints and goals, which we refer to as the scientist's intent. We have developed a framework based upon use of a number of Semantic Web technologies, including the OWL ontology language and the Semantic Web Rule Language (SWRL), to capture scientist's intent. Through the use of a social simulation case study we illustrate the benefits of using this framework in terms of workflow monitoring, workflow provenance and enrichment of experimental results.
|Title of host publication||2008 Third Workshop on Workflows in Support of Large-Scale Science (WORKS 2008)|
|Number of pages||3|
|Publication status||Published - 2008|
|Event||3rd Workshop on Workflows in Support of Large-Scale Science - Austin|
Duration: 17 Nov 2008 → …
|Conference||3rd Workshop on Workflows in Support of Large-Scale Science|
|Period||17/11/08 → …|