The problem of exchanging data, even considering incomplete and heterogeneous data, has been deeply investigated in the last years. The approaches proposed so far are quite rigid as they refer to fixed schema and/or are based on a deductive approach consisting in the use of a fixed set of (mapping) rules. In this paper we describe a smart data exchange framework integrating deductive and inductive techniques to obtain new knowledge. The use of graph-based representation of source and target data, together with the midway relational database and the extraction of new knowledge allow us to manage dynamic databases where also features of data may change over the time.
Smart Data Exchange
Greco S.;Ianni M.;Sacca D.;Trubitsyna I.
2020-01-01
Abstract
The problem of exchanging data, even considering incomplete and heterogeneous data, has been deeply investigated in the last years. The approaches proposed so far are quite rigid as they refer to fixed schema and/or are based on a deductive approach consisting in the use of a fixed set of (mapping) rules. In this paper we describe a smart data exchange framework integrating deductive and inductive techniques to obtain new knowledge. The use of graph-based representation of source and target data, together with the midway relational database and the extraction of new knowledge allow us to manage dynamic databases where also features of data may change over the time.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
