MINIMUM: MergINg logIcal scheMas Using Mapping constraints
Merging multiple logical data schemas using schema mappings in the form of data dependencies.
Integrating data sources on the level of metadata (i.e., schemas) is a long standing problem in databases. The application domains range from database design, data integration, to schema evolution. In this work, we aim at merging logical schemas, relational or nested relational, interrelated via schema mappings in a logical mapping language such as tuple-generating dependencies.
The goal of the project is to investigate various fundamental aspects of schema merging including:
- semantics: information capacity, logical characterization of merge requirements
- functional/operational properties: query capability, updatability, incremental maintainability
- algorithmic aspects: feasible algorithms for schema merging
- expressiveness and efficiency: mapping languages and complexities
We have developed a prototype MINIMUM capable of merging relational schemas using a finitely chaseable set of data dependencies in the format of tuple-generating dependencies and equality generating dependencies. The backend is implemented using Java and Prolog to perform reasoning using the chase procedure, while the frontend is developed using Eclipse RCP to present a Graphical User Interface.
Merging Relational Views: A Minimization Approach
Published in Proc. of the 30th Int. Conference on Conceptual Modeling (ER 2011), 2011.
Automatic Mediated Schema Generation Through Reasoning Over Data Dependencies
Published in Proceedings of the 27th International Conference on Data Engineering, ICDE 2011, April 11-16, 2011, Hannover, Germany.
Towards a Unified Framework for Schema Merging
Published in VLDB 2010 PhD Workshop. Singapore, September 13-17, 2010.
Automatic Schema Merging Using Mapping Constraints Among Incomplete Sources
Published in Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM'10), October 26-30, 2010, Toronto, ON, Canada.