Research problems in data warehousing
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Data Exchange: Semantics and Query Answering
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family
Journal of Automated Reasoning
The Complexity of Conjunctive Query Answering in Expressive Description Logics
IJCAR '08 Proceedings of the 4th international joint conference on Automated Reasoning
Journal on data semantics X
Datalog+/-: A Family of Logical Knowledge Representation and Query Languages for New Applications
LICS '10 Proceedings of the 2010 25th Annual IEEE Symposium on Logic in Computer Science
On rules with existential variables: Walking the decidability line
Artificial Intelligence
Ontological queries: Rewriting and optimization
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Optimized query rewriting for OWL 2 QL
CADE'11 Proceedings of the 23rd international conference on Automated deduction
Repairing ontologies for incomplete reasoners
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Categorising logical differences between OWL ontologies
Proceedings of the 20th ACM international conference on Information and knowledge management
Completeness guarantees for incomplete ontology reasoners: theory and practice
Journal of Artificial Intelligence Research
Query rewriting under query refinements
Knowledge-Based Systems
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Conjunctive query (CQ) answering is a key reasoning service for ontology-based data access. One of the most prominent approaches to conjunctive query answering is query rewriting where a wide variety of systems has been proposed the last years. All of them accept as input a fixed CQ q and ontology ${\mathcal O}$ and produce a rewriting for $q, {\mathcal O}$. However, in many real world applications ontologies are very often dynamic--that is, new axioms can be added or existing ones removed frequently. In this paper we study the problem of computing a rewriting for a CQ over an ontology that has been contracted (i.e., some of its axioms have been removed) given a rewriting for the input CQ and ontology. Our goal is to compute a rewriting directly from the input rewriting and avoid computing one from scratch. We study the problem theoretically and provide sufficient conditions under which this process is possible. Moreover, we present a practical algorithm which we implemented and evaluated against other state-of-the-art systems obtaining encouraging results. Finally, axiom removal can also be relevant to ontology design. For each test ontology we study how much the removal of an axiom affects the size of the rewriting and the performance of systems. If the removal of a single axiom causes a significant decrease either in the size or in the computation time then this part of the ontology can be re-modelled.