Knowledge Spring Process: Towards Discovering and Reusing Knowledge within Linked Open Data Foundations

摘要

Data is everywhere, and non-expert users must be able to exploit it in order to extract knowledge, get insights and make well-informed decisions. The value of the discovered knowledge could be of greater value if it is available for later consumption and reusing. In this paper, we present the first version of the Knowledge Spring Process, an infrastructure that allows non-expert users to (i) apply user-friendly data mining techniques on open data sources, and (ii) share results as Linked Open Data (LOD). The main contribution of this paper is the concept of reusing the knowledge gained from data mining processes after being semantically annotated as LOD, then obtaining Linked Open Knowledge. Our Knowledge Spring Process is based on a model-driven viewpoint in order to easier deal with the wide diversity of open data formats.