Incomplete Information in Relational Databases
Journal of the ACM (JACM)
Why and Where: A Characterization of Data Provenance
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Lineage tracing for general data warehouse transformations
The VLDB Journal — The International Journal on Very Large Data Bases
Data exchange: semantics and query answering
Theoretical Computer Science - Database theory
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Update exchange with mappings and provenance
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Databases with uncertainty and lineage
The VLDB Journal — The International Journal on Very Large Data Bases
Data exchange in the presence of arithmetic comparisons
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Answering aggregate queries in data exchange
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data exchange: query answering for incomplete data sources
Proceedings of the 3rd international conference on Scalable information systems
Towards Relational Schema Uncertainty
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
Proceedings of the 13th International Conference on Database Theory
Provenance for aggregate queries
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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We present a data exchange framework that is capable of exchanging uncertain data with lineage and give meaningful certain answers on queries posed on the target schema. The data are stored in a database with uncertainty and lineage (ULDB) which represents a set of possible instances that are databases with lineage (LDBs). Hence we need first to revisit all the notions related to data exchange for the case of LDBs. Producing all possible instances of a ULDB, like the semantics of certain answers would indicate, is exponential. We present a more efficient approach: a u-chase algorithm that extends the known chase procedure of traditional data exchange and show that it can be used to correctly compute certain answers for conjunctive queries in PTIME for a set of weakly acyclic tuple generating dependencies. We further show that if we allow equality generating dependencies in the set of constraints then computing certain answers for conjunctive queries becomes NP-hard.