Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
The entity-relationship model—toward a unified view of data
ACM Transactions on Database Systems (TODS) - Special issue: papers from the international conference on very large data bases: September 22–24, 1975, Framingham, MA
A Distance-Based Approach to Entity Reconciliation in Heterogeneous Databases
IEEE Transactions on Knowledge and Data Engineering
Flexible Relation: An Approach for Integrating Data from Multiple, Possibly Inconsistent Databases
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Index Selection in Relational Databases
ICCI '93 Proceedings of the Fifth International Conference on Computing and Information
Integrating heterogeneous multidimensional databases
SSDBM'2005 Proceedings of the 17th international conference on Scientific and statistical database management
Design and implementation of a forecasting tool of justice chains
LawTech '07 Proceedings of the Fifth IASTED International Conference on Law and Technology
Crime statistics online: potentials and challenges
Proceedings of the 11th Annual International Digital Government Research Conference on Public Administration Online: Challenges and Opportunities
Public safety mashups to support policy makers
EGOVIS'10 Proceedings of the First international conference on Electronic government and the information systems perspective
Proceedings of the 13th Annual International Conference on Digital Government Research
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In many organizations different databases contain different kind of data concerning the same entity. This may have several good reasons. However, to have an integral and unified view of an entity, data reconciliation is of crucial importance. In this paper, we present an approach for data reconciliation that is based on available schemata of data sources and the content of the sources. The different schemata of data sources are used to determine what parts of the schemata pertain to the same entity type. The content of the sources is used to determine the association between different attributes stored in different sources. In establishing the relationships between different attributes, we have exploited the knowledge of domain experts as well. On the basis of the collected information with regard to a set of attributes, we assign a similarity measure to these attributes. Once we have identified the set of attributes that is similar, we reconcile two entities on the basis of the similarity measure. We illustrate the effectiveness of our approach by means of a real-life case in the field of police and justice.