The Semantic Web is becoming a major platform for disseminating and sharing scientific data and results. Quality of these information is a critical factor in selecting and reusing them. Existing quality assessment approaches in the Semantic Web largely focus on using general quality dimensions (accuracy, relevancy, etc.) to establish quality metrics. However, specific quality assessment tasks may not fit into these dimensions and scientists may find these dimensions too general for expressing their specific needs. Therefore, we present a checklist-based approach, which allows the expression of specific quality requirements, saving users from the constraints of the existing quality dimensions. We demonstrate our approach by two scenarios and share our lessons about different semantic web technologies that were tested during our implementation.
['Jun Zhao', 'Graham Klyne', 'Matthew Gamble', 'Carole Goble']
A checklist-based approach for quality assessment of scientific information