13,234 research outputs found
On the Data Complexity of Consistent Query Answering over Graph Databases
Areas in which graph databases are applied - such as the semantic web, social networks and scientific databases - are prone to inconsistency, mainly due to interoperability issues. This raises the need for understanding query answering over inconsistent graph databases in a framework that is simple yet general enough to accommodate many of its applications. We follow the well-known approach of consistent query answering (CQA), and study the data complexity of CQA over graph databases for regular path queries (RPQs) and regular path constraints (RPCs), which are frequently used. We concentrate on subset, superset and symmetric difference repairs. Without further restrictions, CQA is undecidable for the semantics based on superset and symmetric difference repairs, and Pi_2^P-complete for subset repairs. However, we provide several tractable restrictions on both RPCs and the structure of graph databases that lead to decidability, and even tractability of CQA. We also compare our results with those obtained for CQA in the context of relational databases
Prioritized Repairing and Consistent Query Answering in Relational Databases
A consistent query answer in an inconsistent database is an answer obtained
in every (minimal) repair. The repairs are obtained by resolving all conflicts
in all possible ways. Often, however, the user is able to provide a preference
on how conflicts should be resolved. We investigate here the framework of
preferred consistent query answers, in which user preferences are used to
narrow down the set of repairs to a set of preferred repairs. We axiomatize
desirable properties of preferred repairs. We present three different families
of preferred repairs and study their mutual relationships. Finally, we
investigate the complexity of preferred repairing and computing preferred
consistent query answers.Comment: Accepted to the special SUM'08 issue of AMA
Ontology-based data access with databases: a short course
Ontology-based data access (OBDA) is regarded as a key ingredient of the new generation of information systems. In the OBDA paradigm, an ontology defines a high-level global schema of (already existing) data sources and provides a vocabulary for user queries. An OBDA system rewrites such queries and ontologies into the vocabulary of the data sources and then delegates the actual query evaluation to a suitable query answering system such as a relational database management system or a datalog engine. In this chapter, we mainly focus on OBDA with the ontology language OWL 2QL, one of the three profiles of the W3C standard Web Ontology Language OWL 2, and relational databases, although other possible languages will also be discussed. We consider different types of conjunctive query rewriting and their succinctness, different architectures of OBDA systems, and give an overview of the OBDA system Ontop
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back
In this work we establish and investigate connections between causes for
query answers in databases, database repairs wrt. denial constraints, and
consistency-based diagnosis. The first two are relatively new research areas in
databases, and the third one is an established subject in knowledge
representation. We show how to obtain database repairs from causes, and the
other way around. Causality problems are formulated as diagnosis problems, and
the diagnoses provide causes and their responsibilities. The vast body of
research on database repairs can be applied to the newer problems of computing
actual causes for query answers and their responsibilities. These connections,
which are interesting per se, allow us, after a transition -inspired by
consistency-based diagnosis- to computational problems on hitting sets and
vertex covers in hypergraphs, to obtain several new algorithmic and complexity
results for database causality.Comment: To appear in Theory of Computing Systems. By invitation to special
issue with extended papers from ICDT 2015 (paper arXiv:1412.4311
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