Abstract
We propose a framework for querying probabilistic instance data in the presence of an OWL2 QL ontology, arguing that the interplay of probabilities and ontologies is fruitful in many applications such as managing data that was extracted from the web. The prime inference problem is computing answer probabilities, and it can be implemented using standard probabilistic database systems. We establish a PTime vs. #P dichotomy for the data complexity of this problem by lifting a corresponding result from probabilistic databases. We also demonstrate that query rewriting (backwards chaining) is an important tool for our framework, show that non-existence of a rewriting into first-order logic implies #P-hardness, and briefly discuss approximation of answer probabilities.
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Jung, J.C., Lutz, C. (2012). Ontology-Based Access to Probabilistic Data with OWL QL . In: Cudré-Mauroux, P., et al. The Semantic Web – ISWC 2012. ISWC 2012. Lecture Notes in Computer Science, vol 7649. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35176-1_12
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