Combining ontologies by discovering semantic associations at any level of abstraction, or decomposing large ontologies in modules w.r.t. logical properties either for re-usability of specifications, efficiency in ontology management, or efficiecy in reasoning, are goals that we need to pursue, especially when we deal with real-world heterogeneous and disparate data sources.
These tasks are especially important towards data-driven ontology engineering methods.
Expert Systems With Applications, 2017.
Specification of Semantic Trajectories Supporting Data Transformations for Analytics: The datAcron Ontology Proceeding
Accessing and Reasoning with Data from Disparate Data Sources Using Modular Ontologies and OBDA Conference
SEMANTiCS 2015, Vienna, 2015.
IJAIT, 24 , 2015.
KAIS, OnLine , 2014, ISSN: 0219-3116.