SEM+: tool for discovering concept mapping in Earth science related domain

Abstract

The amount of Earth Science related domain concepts and vocabularies encoded in popular Semantic Web languages such as OWL and SKOS grows rapidly as more and more domain scientists realize the power of Semantic Web Technologies. The interlinking between these concepts will enable the possibility of performing data integration and identity recognition, which is crucial in developing applications that use data from multiple sources. In this paper, we discuss a new tool for performing concept mapping called SEM+. In SEM+, we designed the Information Entropy based Weighted Similarity Model to compute semantic similarity between entity data and suggest possible linking. We also adopted a blocking approach to group possible matching entities into one block and therefore reduce the computation space. We performed evaluations on SEM+ using the Integrated Ocean Observatory System ontology and the Marine Metadata Interoperability ontology and discussed the results and new findings.