Abstract
One of the hard problems in information integration projects (harmonizing data from various legacy sources into one or more targets) is the appropriate alignment of reference data values across systems. Without this alignment, the process of loading records into the target systems might fail because the target might reject any record with an unknown reference data value or different underlying data semantics. Today, detecting reference data tables and determining the relative alignment between a source and a target is largely manual, cumbersome, error-prone and costly. We propose a novel ontology-guided approach to detect reference data tables and their relative alignment across source/target systems to enable semi-automated creation of translation tables.
Recommended Citation
Pandit, Sushain; Oberhofer, Martin; and Milman, Ivan, "Ontology-guided Reference Data Alignment in Information Integration Projects" (2012). AMCIS 2012 Proceedings. 7.
https://aisel.aisnet.org/amcis2012/proceedings/DataInfoQuality/7
Ontology-guided Reference Data Alignment in Information Integration Projects
One of the hard problems in information integration projects (harmonizing data from various legacy sources into one or more targets) is the appropriate alignment of reference data values across systems. Without this alignment, the process of loading records into the target systems might fail because the target might reject any record with an unknown reference data value or different underlying data semantics. Today, detecting reference data tables and determining the relative alignment between a source and a target is largely manual, cumbersome, error-prone and costly. We propose a novel ontology-guided approach to detect reference data tables and their relative alignment across source/target systems to enable semi-automated creation of translation tables.