We describe a new methodology for modeling aggregate data and explicitly connecting them to the individual-level data from which aggregates are generated. The approach makes use of OWL2 ontologies that formalize both the application domain and multidimensional constructs, such as data cubes, measures, dimensions, and hierarchies. This contribution stems from a collaboration among ISTAT, Sapienza University of Rome, and OBDA Systems, within the project INTERSTAT.
Dettaglio pubblicazione
2023, Proceedings of the 31st Symposium of Advanced Database Systems (SEBD 2023), Pages 220-227 (volume: 3478)
Bridging the gap between micro and macro data: Ontologies to the rescue (04b Atto di convegno in volume)
Lembo D., Lenzerini M., Poggi A., Radini R., Riccio M., Santarelli V.
keywords