Incomplete Information in Relational Databases
Journal of the ACM (JACM)
Integrity = validity + completeness
ACM Transactions on Database Systems (TODS)
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Obtaining Complete Answers from Incomplete Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Views and queries: determinacy and rewriting
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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
Checking query completeness over incomplete data
Proceedings of the 4th International Workshop on Logic in Databases
Containment of conjunctive queries over databases with null values
ICDT'07 Proceedings of the 11th international conference on Database Theory
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Data completeness is an essential aspect of data quality as in many scenarios it is crucial to guarantee the completeness of query answers. Data might be incomplete in two ways: records may be missing as a whole, or attribute values of a record may be absent, indicated by a null. We extend previous work by two of the authors [10] that dealt only with the first aspect, to cover both missing records and missing attribute values. To this end, we refine the formalization of incomplete databases and identify the important special case where values of key attributes are always known. We show that in the presence of nulls, completeness of queries can be defined in several ways.We also generalize a previous approach stating completeness of parts of a database, using so-called table completeness statements. With this formalization in place, we define the main inferences for completeness reasoning over incomplete databases and present first results.