Integrity = validity + completeness
ACM Transactions on Database Systems (TODS)
Obtaining Complete Answers from Incomplete Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Relative information completeness
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Capturing missing tuples and missing values
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Complete approximations of incomplete queries
Proceedings of the VLDB Endowment
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MAGIK demonstrates how to use meta-information about the completeness of a database to assess the quality of the answers returned by a query. The system holds so-called table-completeness (TC) statements, by which one can express that a table is partially complete, that is, it contains all facts about some aspect of the domain. Given a query, MAGIK determines from such meta-information whether the database contains sufficient data for the query answer to be complete. If, according to the TC statements, the database content is not sufficient for a complete answer, MAGIK explains which further TC statements are needed to guarantee completeness. MAGIK extends and complements theoretical work on modeling and reasoning about data completeness by providing the first implementation of a reasoner. The reasoner operates by translating completeness reasoning tasks into logic programs, which are executed by an answer set engine.