A Proof Procedure for Data Dependencies
Journal of the ACM (JACM)
Data-driven understanding and refinement of schema mappings
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Clio: a semi-automatic tool for schema mapping
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Data Exchange: Semantics and Query Answering
ICDT '03 Proceedings of the 9th International Conference on Database Theory
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
Mapping data in peer-to-peer systems: semantics and algorithmic issues
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Constraint-based XML query rewriting for data integration
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Debugging schema mappings with routes
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Leveraging data and structure in ontology integration
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Data sharing through query translation in autonomous sources
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Schema mapping verification: the spicy way
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Muse: Mapping Understanding and deSign by Example
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Clip: a Visual Language for Explicit Schema Mappings
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Clio: Schema Mapping Creation and Data Exchange
Conceptual Modeling: Foundations and Applications
Beauty and the beast: the theory and practice of information integration
ICDT'07 Proceedings of the 11th international conference on Database Theory
Entity resolution with evolving rules
Proceedings of the VLDB Endowment
Metamodel-based information integration at industrial scale
MODELS'10 Proceedings of the 13th international conference on Model driven engineering languages and systems: Part II
Web Semantics: Science, Services and Agents on the World Wide Web
BuildSys '12 Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
Invisible loading: access-driven data transfer from raw files into database systems
Proceedings of the 16th International Conference on Extending Database Technology
Advanced Engineering Informatics
Incremental entity resolution on rules and data
The VLDB Journal — The International Journal on Very Large Data Bases
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To integrate information, data in different formats, from dif- ferent, potentially overlapping sources, must be related and transformed to meet the users' needs. Ten years ago, Clio introduced nonprocedural schema mappings to describe the relationship between data in heteroge- neous schemas. This enabled powerful tools for mapping discovery and integration code generation, greatly simplifying the integration process. However, further progress is needed. We see an opportunity to raise the level of abstraction further, to encompass both data- and schema-centric integration tasks and to isolate applications from the details of how the integration is accomplished. Holistic information integration supports it- eration across the various integration tasks, leveraging information about both schema and data to improve the integrated result. Integration inde- pendence allows applications to be independent of how, when, and where information integration takes place, making materialization and the tim- ing of transformations an optimization decision that is transparent to applications. In this paper, we define these two important goals, and propose leveraging data mappings to create a framework that supports both data- and schema-level integration tasks.