Linked Open Data mining for democratization of big data

Abstract

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 from big data could be of greater value if it is available for later consumption and reusing. In this paper, we present an infrastructure that allows non-expert users to (i) apply user-friendly data mining techniques on big data sources, and (ii) share results as Linked Open Data (LOD). The main contribution of this paper is an approach for democratizing big data through reusing the knowledge gained from data mining processes after being semantically annotated as LOD, then obtaining Linked Open Knowledge. Our work is based on a model-driven viewpoint in order to easily deal with the wide diversity of open data formats.