A metric-driven approach for interlinking assessment of RDF graphs

In recent years the web has evolved from a global information space of linked documents to one where both documents and data are linked. What supports this evolution is a set of best practices in publishing and connecting structured data on the web that is called linked data. The usefulness of linked data relies on how much related concepts are linked together. The aim of this research is to propose a metric-driven approach for interlinking assessment of a single dataset. The proposed metrics are categorized into three groups called internal linking, external linking and link-ability from other datasets. These metrics consider both graph structure (topology) and schema of datasets (semantic information) to evaluate interlinking with appropriate accuracy.