Context-sensitive Team Formation: Towards Model-Based Context Reasoning and Update

Selection problems tend to have two aspects: one that is structural and one that is quantitative in nature. Here we investigate a method that allows decisions on both aspects. The paper considers a typical example, that of selecting members for a team, where decisions are based on context information. We show that graph transformations are providing a solution to the structural selection, while logic scoring of preferences allows qualitative decision making. On an implementation level OWL and SPARQL are used to retrieve and update context data.