On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
A relational model of data for large shared data banks
Communications of the ACM
Universality of data retrieval languages
POPL '79 Proceedings of the 6th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Knowledge systems: Principles and practice
IBM Journal of Research and Development
Ontology-Driven Induction of Decision Trees at Multiple Levels of Abstraction
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
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A person in the higher levels of a hierarchical organization may wish not to use a fully detailed data base, but rather an abstracted data base, perhaps dropping into detail in only a few areas. We compare answers from queries put to an abstracted data base with answers obtained by querying a full data base and then abstracting the result of the query. We show that, for some common relational retrievals, querying an abstracted data base always yields the correct information, plus, in some cases, some incorrect information, and we give simple conditions on the abstraction which ensure that only the correct information is fetched. For the cases in which the conditions may not hold, we suggest an ordering, called succinctness, for comparing the quality of different abstractions.