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.
Bridging the gap between micro and macro data: Ontologies to the rescue / Lembo, D.; Lenzerini, M.; Poggi, A.; Radini, R.; Riccio, M.; Santarelli, V.. - 3478:(2023), pp. 220-227. (Intervento presentato al convegno 31st Symposium of Advanced Database Systems tenutosi a Galzingano Terme; Italy).
Bridging the gap between micro and macro data: Ontologies to the rescue
Lembo D.
;Lenzerini M.
;Poggi A.
;Santarelli V.
2023
Abstract
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.| File | Dimensione | Formato | |
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Lembo_Bridging_2023.pdf
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Note: https://ceur-ws.org/Vol-3478/paper66.pdf
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