Incomplete Information in Relational Databases
Journal of the ACM (JACM)
A sound and sometimes complete query evaluation algorithm for relational databases with null values
Journal of the ACM (JACM)
Integrity = validity + completeness
ACM Transactions on Database Systems (TODS)
On the representation and querying of sets of possible worlds
Selected papers of the workshop on Deductive database theory
Logical approaches to incomplete information: a survey
Logics for databases and information systems
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Data Exchange: Semantics and Query Answering
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Obtaining Complete Answers from Incomplete Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Optimal implementation of conjunctive queries in relational data bases
STOC '77 Proceedings of the ninth annual ACM symposium on Theory of computing
Completeness of integrated information sources
Information Systems - Special issue: Data quality in cooperative information systems
Views and queries: determinacy and rewriting
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data Quality: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications)
Data Quality: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications)
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
Containment of conjunctive queries over databases with null values
ICDT'07 Proceedings of the 11th international conference on Database Theory
Assessing the completeness of geographical data
BNCOD'13 Proceedings of the 29th British National conference on Big Data
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Data completeness is an important aspect of data quality. We consider a setting, where databases can be incomplete in two ways: records may be missing and records may contain null values. We (i) formalize when the answer set of a query is complete in spite of such incompleteness, and (ii) we introduce table completeness statements, by which one can express that certain parts of a database are complete. We then study how to deduce from a set of table-completeness statements that a query can be answered completely. Null values as used in SQL are ambiguous. They can indicate either that no attribute value exists or that a value exists, but is unknown. We study completeness reasoning for the different interpretations. We show that in the combined case it is necessary to syntactically distinguish between different kinds of null values and present an encoding for doing that in standard SQL databases. With this technique, any SQL DBMS evaluates complete queries correctly with respect to the different meanings that nulls can carry. We study the complexity of completeness reasoning and provide algorithms that in most cases agree with the worst-case lower bounds.