Enhancing Workflow with a Semantic Description of Scientific Intent

Abstract

Scientists are becoming increasingly dependent upon resources available through the
Internet including, for example, datasets and computational modelling services, which are changing the
way they conduct their research activities. This paper investigates the use of workflow tools enhanced
with semantics to facilitate the design, execution, analysis and interpretation of workflow experiments
and exploratory studies. Current workflow technologies do not incorporate any representation of
experimental constraints and goals, which we refer to in this paper as scientist's intent. This paper
proposes an abstract model of intent based on the Open Provenance Model (OPM) specification. To
realise this model a framework based upon a number of Semantic Web technologies has been
developed, including the OWL ontology language and the Semantic Web Rule Language (SWRL).
Through the use of social simulation case studies the paper illustrates the benefits of using this
framework in terms of workflow monitoring, workflow provenance and annotation of experimental
results