Towards Utilizing Open Data for Interactive Knowledge Transfer

摘要

Increasing heterogeneous Open Data is an ongoing trend in the current Social Semantic Web (s2w). Generic concepts and how-tos for higher-layered reuse of the arbitrary information overload for interactive knowledge transfer and learning - mentioning the Internet of Services (IoS) - are not covered very well yet. For further, directed use of distributed services and sources, inquiry, interlinking, analysis, machine- and human-interpretable representation are as essential as lightweight user-oriented interoperation and competency in handling. In the following we introduce the qKAI application framework (qualifying Knowledge Acquisition and Inquiry) - a service-oriented, generic and hybrid approach combining knowledge related offers for convenient reuse and tweaking them with interaction for improved access with rich user experience. qKAI aims at closing some residual gaps between the "sophisticated" Semantic Web and "hands-on" Web 2.0 enabling loose-coupled knowledge and information services focussed on knowledge life cycles, learning aspects  and handy user interaction.