Pay-as-you-go mapping selection in dataspaces

Authors:
Cornelia Hedeler;Khalid Belhajjame;Norman W. Paton;Alvaro A.A. Fernandes;Suzanne M. Embury;Lu Mao;Chenjuan Guo
Affiliations:
The University of Manchester, Manchester, United Kingdom;The University of Manchester, Manchester, United Kingdom;The University of Manchester, Manchester, United Kingdom;The University of Manchester, Manchester, United Kingdom;The University of Manchester, Manchester, United Kingdom;The University of Manchester, Manchester, United Kingdom;The University of Manchester, Manchester, United Kingdom
Venue:
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Year:
2011

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Abstract

The vision of dataspaces proposes an alternative to classical data integration approaches with reduced up-front costs followed by incremental improvement on a pay-as-you-go basis. In this paper, we demonstrate DSToolkit, a system that allows users to provide feedback on results of queries posed over an integration schema. Such feedback is then used to annotate the mappings with their respective precision and recall. The system then allows a user to state the expected levels of precision (or recall) that the query results should exhibit and, in order to produce those results, the system selects those mappings that are predicted to meet the stated constraints.