Managing Information Quality in e-Science Using Semantic Web Technology

Abstract

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.

An ontology‐based approach to handling information quality in e‐Science

“…This involves the creation of highlevel specifications of various quality-aware data manipulation operations (such as filtering of poor quality data items) that can be compiled into environment-specific components. We are currently investigating the deployment of Qurator components in this way into the Taverna workflow enactment environment [20] and the Pedro data entry tool [11], as described in [9] and [6] respectively. We are also considering how our preference mechanism may be used in conjunction with a publish/subscribe…”

“…The Pedro data entry tool [11] has been designed for capturing and annotating genomic data for storage or dissemination using XML and has been widely used by biologists. An interface to the OntValidator Web service has recently been created as a plug-in to this tool, in a similar manner to the plug-ins described in [6].…”

“…This conformance report can then be used to generate IQ assertions for presentation according to a user's preferences. RDF is used to capture the quality evidence as annotations on the original XML dataset [6], as it provides a natural way of making statements about Web resources, and also integrates with our OWL ontology in that the RDF data includes instances of the IQ concepts in the ontology.…”

4.3 Use of the Semantic Web in e-Research

“…Without Semantic Web technology, this task would require either complex scripts to overcome incompatibilities or a laborious manual process of cutting and pasting between Web interfaces. Semantic Web technologies, including ontologies and annotation, have been shown to be very useful in preserving information quality (Preece et al 2006), and SPARQL provides a network protocol that allows effective querying.…”

Modelling a web site quality‐based recommendation system

“…It is quite common to find recommendation systems based on ontologies that model the user profile and the domain of resources to be recommended (Ziegler, 2004; Preece et al , 2006; Sena and Motz, 2007). However, it is uncommon to find models that: explicitly represent the criteria used by the recommendation systems, express the quality dimensions of resources and what quality criteria are applied, and the user context at the moment the query.…”