Conjunctive query inseparability of OWL 2 QL TBoxes

The OWL2 profile OWL 2 QL, based on the DL-Lite family of description logics, is emerging as a major language for developing new ontologies and approximating the existing ones. Its main application is ontology based data access, where ontologies are used to provide background knowledge for answering queries over data. We investigate the corresponding notion of query inseparability (or equivalence) for OWL 2 QL ontologies and show that deciding query inseparability is PSpace-hard and in ExpTime. We give polynomial-time (incomplete) algorithms and demonstrate by experiments that they can be used for practical module extraction

Aberdeen University Ontology Reuse Stack

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Lightweight Ontologies

Ontologies are explicit specifications of conceptualizations. They are often thought of as directed graphs whose nodes represent concepts and whose edges represent relations between concepts. The notion of concept is understood as defined in Knowledge Representation, i.e., as a set of objects or individuals. This set is called the concept extension or the concept interpretation. Concepts are often lexically defined, i.e., they have natural language names which are used to describe the concept extensions (e.g., concept mother denotes the set of all female parents). Therefore, when ontologies are visualized, their nodes are often shown with corresponding natural language concept names. The backbone structure of the ontology graph is a taxonomy in which the relations are “is-a”, whereas the remaining structure of the graph supplies auxiliary information about the modeled domain and may include relations like “part-of”, “located-in”, “is-parent-of”, and many others

Tractable approximate deduction for OWL

Acknowledgements This work has been partially supported by the European project Marrying Ontologies and Software Technologies (EU ICT2008-216691), the European project Knowledge Driven Data Exploitation (EU FP7/IAPP2011-286348), the UK EPSRC project WhatIf (EP/J014354/1). The authors thank Prof. Ian Horrocks and Dr. Giorgos Stoilos for their helpful discussion on role subsumptions. The authors thank Rafael S. Gonçalves et al. for providing their hotspots ontologies. The authors also thank BoC-group for providing their ADOxx Metamodelling ontologies.Peer reviewedPostprin

Approximating FOL Ontologies using OWL2

With the amount of data collected everyday ever expanding, techniques which allow com- puters to semantically understand data are growing in importance. Ontologies are a tool to describe the relationships connecting data so that computers can correctly interpret and combine data from many sources. An ontology about water needs to describe what the term river may refer to: An arbitrary river or one usable for navigation; a single tributary or an entire river network; the riverbed or the water itself? Well-designed ontologies can be shared, reused, and extended across multiple applications and facilitate betters integration of different data collections. Common Logic (CL) and the Web Ontology Language (OWL) are two logic based languages of popular interest. However, ontologies developed in either of these languages are not easily consumed by users of the other language. By utilizing the first order properties of Common Logic, an automated approximation routine between CL and OWL is provided. OWL, being less expressive than CL, is capable of being totally represented by logically equivalent CL axioms. Leveraging the logical equivalence, we provide a method of axiom normalization and extraction in order to construct robust OWL ontologies from existing CL sources. This increases CL ontology intelligibility, and allows the automatic construction of OWL versions of existing reference ontologies. Further, the benefits of such a translation are demonstrated by applying previously exclusive OWL tooling and analysis techniques to evaluate the translated ontologies

Hybrid Rules with Well-Founded Semantics

A general framework is proposed for integration of rules and external first order theories. It is based on the well-founded semantics of normal logic programs and inspired by ideas of Constraint Logic Programming (CLP) and constructive negation for logic programs. Hybrid rules are normal clauses extended with constraints in the bodies; constraints are certain formulae in the language of the external theory. A hybrid program is a pair of a set of hybrid rules and an external theory. Instances of the framework are obtained by specifying the class of external theories, and the class of constraints. An example instance is integration of (non-disjunctive) Datalog with ontologies formalized as description logics. The paper defines a declarative semantics of hybrid programs and a goal-driven formal operational semantics. The latter can be seen as a generalization of SLS-resolution. It provides a basis for hybrid implementations combining Prolog with constraint solvers. Soundness of the operational semantics is proven. Sufficient conditions for decidability of the declarative semantics, and for completeness of the operational semantics are given