A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Conceptual-model-based data extraction from multiple-record Web pages
Data & Knowledge Engineering
Data-driven understanding and refinement of schema mappings
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Information Retrieval
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Schema Mapping as Query Discovery
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
A survey on the use of relevance feedback for information access systems
The Knowledge Engineering Review
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Integrating Data from Disparate Sources: A Mass Collaboration Approach
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Mapping maintenance for data integration systems
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Data exchange: semantics and query answering
Theoretical Computer Science - Database theory
Principles of dataspace systems
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Debugging schema mappings with routes
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Why is schema matching tough and what can we do about it?
ACM SIGMOD Record
A composite approach to automating direct and indirect schema mappings
Information Systems
Communications of the ACM - ACM at sixty: a look back in time
Schema mapping verification: the spicy way
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Pay-as-you-go user feedback for dataspace systems
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Learning to create data-integrating queries
Proceedings of the VLDB Endowment
Data integration with uncertainty
The VLDB Journal — The International Journal on Very Large Data Bases
Muse: Mapping Understanding and deSign by Example
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Data access and integration in the ISPIDER proteomics grid
DILS'06 Proceedings of the Third international conference on Data Integration in the Life Sciences
Flexible Dataspace Management Through Model Management
Proceedings of the 2010 EDBT/ICDT Workshops
Pay-as-you-go mapping selection in dataspaces
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Search Computing
DSToolkit: an architecture for flexible dataspace management
Transactions on Large-Scale Data- and Knowledge-Centered Systems V
Pay-as-you-go data integration for linked data: opportunities, challenges and architectures
SWIM '12 Proceedings of the 4th International Workshop on Semantic Web Information Management
Feedback-based data set recommendation for building linked data applications
Proceedings of the 8th International Conference on Semantic Systems
Pay-as-You-Go ranking of schema mappings using query logs
DILS'12 Proceedings of the 8th international conference on Data Integration in the Life Sciences
Incrementally improving dataspaces based on user feedback
Information Systems
A framework for query refinement with user feedback
Journal of Systems and Software
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The specification of schema mappings has proved to be time and resource consuming, and has been recognized as a critical bottleneck to the large scale deployment of data integration systems. In an attempt to address this issue, dataspaces have been proposed as a data management abstraction that aims to reduce the up-front cost required to setup a data integration system by gradually specifying schema mappings through interaction with end users in a pay-as-you-go fashion. As a step in this direction, we explore an approach for incrementally annotating schema mappings using feedback obtained from end users. In doing so, we do not expect users to examine mapping specifications; rather, they comment on results to queries evaluated using the mappings. Using annotations computed on the basis of user feedback, we present a method for selecting from the set of candidate mappings, those to be used for query evaluation considering user requirements in terms of precision and recall. In doing so, we cast mapping selection as an optimization problem. Mapping annotations may reveal that the quality of schema mappings is poor. We also show how feedback can be used to support the derivation of better quality mappings from existing mappings through refinement. An evolutionary algorithm is used to efficiently and effectively explore the large space of mappings that can be obtained through refinement. The results of evaluation exercises show the effectiveness of our solution for annotating, selecting and refining schema mappings.