Design of a Framework for Knowledge Analytics
Pallavi Karanth · 2016
With access to Internet and Open Data initiatives, large amounts of data are available for analysis. Data Analytics has grown over the years delivering insights from data in a variety of forms ranging from structured to highly unstructured data. With the development of Semantic Web, many applications generate semantic data in significant amounts. Semantic data exist in the form of Resource Description Framework (RDF) triples, Ontologies and Simple Knowledge Organization System (SKOS). Semantic data are knowledge structures in the form of graphs with well defined hierarchies of both concepts and relations in ontology of the domain. Analyzing such knowledge structures requires different methods as they are fundamentally different from a regular graph and regular analytical operations on knowledge structures may misinterpret the actual data. We define new analytical operators which consider the semantic constraints on data to deliver meaningful insights. In this paper, we present the design of an analytical framework for knowledge structures.