Semantic Workflow Management for E-Social Science

In the e-Science context, workflow technologies provide a problem-solving environment for researchers by facilitating the creation and execution of experiments from a pool of available data and computation services. Recent activities in the field of social simulation indicate the need to improve the scientific rigour of agent-based modelling by making simulation experiments more transparent. We argue that in order to characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process making the experiment’s constraints and goals transparent. Current workflow technologies do not incorporate any representation of these goals and conditions, which we call the scientist’s intent. Our hypothesis is that by extending workflow representation in this way, researchers would be able to analyse, verify, execute, monitor and re-use scientific workflows more effectively.