Modeling Scientometric Indicators Using A SDMX Ontology

Abstract Scientometrics is the field of study and evaluation of scientific measures such as impact of research papers and academic journals. It is an important field because nowadays different rankings use key indicators for university rankings and universities themselves use them as Key Performance Indicators (KPI). The purpose of this work is to propose a semantic modeling of scientometric indicators using the ontology Satistical Data and Metadata Exchange (SDMX). We develop a case study at Tecnologico de Monterrey following the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. We evaluate the benefits of storing and querying in a Graph Database (Neo4j) the linked data produced by our approach.