A characteristics framework for Semantic Information Systems Standards

Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard

Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems