Valid-time indeterminacy is “don’t know when” indeterminacy, coping with cases in which one does not exactly know when a fact holds in the modeled reality. In this paper, we first propose a reference representation (data model and algebra) in which all possible temporal scenarios induced by valid-time indeterminacy can be extensionally modeled. We then specify a family of sixteen more compact representational data models. We demonstrate their correctness with respect to the reference representation and analyze several properties, including their data expressiveness. Then, we compare these compact models along several relevant dimensions. Finally, we also extend the reference representation and a representative of compact representations to cope with probabilities.

Valid-Time Indeterminacy in Temporal Relational Databases: Semantics and Representations

ANSELMA, LUCA;
2013

Abstract

Valid-time indeterminacy is “don’t know when” indeterminacy, coping with cases in which one does not exactly know when a fact holds in the modeled reality. In this paper, we first propose a reference representation (data model and algebra) in which all possible temporal scenarios induced by valid-time indeterminacy can be extensionally modeled. We then specify a family of sixteen more compact representational data models. We demonstrate their correctness with respect to the reference representation and analyze several properties, including their data expressiveness. Then, we compare these compact models along several relevant dimensions. Finally, we also extend the reference representation and a representative of compact representations to cope with probabilities.
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http://doi.ieeecomputersociety.org/10.1109/TKDE.2012.199
Temporal databases; Artificial Intelligence; Database design; modeling and management; Knowledge Representation Formalisms and Methods
Luca Anselma; Paolo Terenziani; Richard T. Snodgrass
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/143137
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