Most real databases contain data whose correctness is uncertain. In order to work with such data, there is a need to quantify the integrity of the data. This is achieved by using probabilistic databases.
A probabilistic database is an uncertain database in which the possible worlds have associated probabilities. Probabilistic database management systems are currently an active area of research. "While there are currently no commercial probabilistic database systems, several research prototypes exist..."[1]
Probabilistic databases distinguish between the logical data model and the physical representation of the data much like relational databases do in the ANSI-SPARC Architecture.
In probabilistic databases this is even more crucial since such databases have to represent very large numbers of possible worlds, often exponential in the size of one world (a classical database), succinctly.[2][3]
^Vinod Muthusamy, Haifeng Liu, Hans-Arno Jacobsen: Predictive Publish/Subscribe Matching. University of Toronto.
^Nilesh N. Dalvi, Dan Suciu: Efficient query evaluation on probabilistic databases. VLDB J. 16(4): 523–544 (2007)
^Lyublena Antova, Christoph Koch, Dan Olteanu: 10^(10^6) Worlds and Beyond: Efficient Representation and Processing of Incomplete Information. ICDE 2007: 606–615
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