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.
Specific Topics
- Distributed reasoning with modular ontologies
- Ontology modularization and data partitioning for scalable information management and reasoning
- Ontology alignment methods
- Ontology engineering and management
Recent Publications
2021 |
Big Data Analytics for Time Critical Mobility Forecasting: From raw data to trajectory-oriented mobility analytics in the aviation and maritime domains Book Forthcoming Springer, Forthcoming. |
Parallel and scalable processing of spatio-temporal RDF queries using spark Journal Article Forthcoming GEOINFORMATICA, Forthcoming. |
2020 |
Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations Journal Article The Knowledge Engineering Review, 35 , 2020. |
The delta big data architecture for mobility analytics Conference 2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService), IEEE IEEE, Oxford, UK, 2020. |
2019 |
Journal Of Data Semantics, 8 , 2019. |