Controlled Query Evaluation for Datalog and OWL 2 Profile Ontologies

Authors: Bernardo Cuenca Grau, Evgeny Kharlamov, Egor V. Kostylev, Dmitriy Zheleznyakov

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We study CQE for ontologies expressed in the rule language Datalog as well as in the lightweight description logics (DLs) underpinning the profiles of OWL 2... We formally characterise this duality, and show that their capabilities are incomparable. In Section 5 we investigate the limitations of view censors and show that checking existence of a view realising an optimal censor is undecidable for Datalog ontologies. Theorem 12. The problem of checking whether a Datalog CQE instance admits an optimal view is undecidable.
Researcher Affiliation Academia Bernardo Cuenca Grau, Evgeny Kharlamov, Egor V. Kostylev, Dmitriy Zheleznyakov Department of Computer Science, University of Oxford, UK
Pseudocode No The paper does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets No The paper refers to 'datasets' in a theoretical context (e.g., 'A dataset is a finite set of facts') and provides small illustrative examples (e.g., 'Dex = { Fr Of (John, Bob), Fr Of (Bob, Mary), Crime(Seven), Suspense(Seven), Likes(John, Seven), Likes(Bob, Seven) }'), but it does not provide concrete access information for a publicly available or open dataset used for training or evaluation.
Dataset Splits No The paper does not provide specific dataset split information for validation.
Hardware Specification No The paper is theoretical and does not describe any hardware used for running experiments.
Software Dependencies No The paper is theoretical and does not specify any software dependencies with version numbers needed to replicate the work. It mentions 'off-the-shelf reasoning infrastructure' but no specific versions.
Experiment Setup No The paper is theoretical and does not describe any specific experimental setup details like hyperparameters or training configurations.