Recent works on Business Intelligence do highlight the need of on-time, trustable and sound data access systems. Moreover the application of these systems in a flexible and dynamic environment requires for an approach based on automatic procedures that can provide reliable results. A crucial factor for any automatic data integration system is the matching process. Different categories of matching operators carry different semantics. For this reason combining them in a single algorithm is a non trivial process that have to take into account a variety of options. This paper proposes a solution based on a categorization of matching operators that allow to group similar attributes on a semantic rich form. This way we define all the information need in order to create a mapping. Then Mapping Generation is activated only on those set of elements that can be queried without violating any integrity constraints on data.
ODDI : a framework for semi-automatic data integration / P. Ceravolo, Z. Cui, E. Damiani, A. Gusmini, M. Leida - In: ICEIS 2008 : proceedings of the tenth International conference on enterprise information systems / [a cura di] J. Cordeiro, J. Filipe. - Setúbal : INSTICC, 2008. - ISBN 9789898111364. - pp. 15-24 (( Intervento presentato al 10. convegno International Conference on Enterprise Information Systems (ICEIS) tenutosi a Barcellona nel 2008.
ODDI : a framework for semi-automatic data integration
P. CeravoloPrimo
;E. Damiani;M. LeidaUltimo
2008
Abstract
Recent works on Business Intelligence do highlight the need of on-time, trustable and sound data access systems. Moreover the application of these systems in a flexible and dynamic environment requires for an approach based on automatic procedures that can provide reliable results. A crucial factor for any automatic data integration system is the matching process. Different categories of matching operators carry different semantics. For this reason combining them in a single algorithm is a non trivial process that have to take into account a variety of options. This paper proposes a solution based on a categorization of matching operators that allow to group similar attributes on a semantic rich form. This way we define all the information need in order to create a mapping. Then Mapping Generation is activated only on those set of elements that can be queried without violating any integrity constraints on data.File | Dimensione | Formato | |
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