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.

The PolicyGrid project is exploring the role of Grid, Semantic Web, and Web 2.0 technologies to support e-Social Science, with particular emphasis on tools to facilitate evidence-based policy making. In this article, we discuss the challenges associated with construction of a provenance framework to support evidence-based policy assessment. We then discuss ourSpaces, a virtual research environment for e-Social Science that uses the Web 2.0 paradigm as well as Semantic Grid technologies and which provides researchers with facilities for management of digital resources using a novel natural language interface.

In this paper we investigate the role of provenance in agentbased simulation and discuss typical queries we need to perform over a provenance record. Using examples based on a simulation environment using OWL ontologies to represent the state and structure of the simulation, we discuss some of the challenges posed by the large volume of fine-grained provenance associated with the execution of simulation models.

Abstract. We outline a framework for managing information quality (IQ) in eScience, using ontologies, semantic annotation of resources, and data bindings. Scientists define the quality characteristics that are of importance in their particular domain by extending an OWL DL IQ ontology, which classifies and organises these domain-specific quality characteristics within an overall quality management framework. RDF is used to annotate data resources, with reference to IQ indicators defined in the ontology. Data bindings -again defined in RDF -are used to represent mappings between data elements (e.g. defined in XML Schemas) and the IQ ontology. As a practical illustration of our approach, we present a case study from the domain of proteomics.

a b s t r a c tThe ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups.