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

In this paper we outline a framework for managing information quality (IQ) in an e-Science context. In contrast to previous approaches that take a very abstract view of IQ properties, we allow scientists to define the quality characteristics that are of importance to them in their particular domain. For example, 'accuracy' may be defined in terms of the conformance of experimental data to a particular standard. User-scientists specify their IQ preferences against a formal ontology, so that the definitions are machine-manipulable, allowing the environment to classify and organize domain-specific quality characteristics within an overall quality management framework. As an illustration of our approach, we present an example Web service that computes IQ annotations for experiment datasets in transcriptomics.