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Understanding Inexpressibility of Model−Based ABox Evolution in DL−Lite

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TLDR
The notion of prototypes is introduced that gives an understanding of how to capture evolution for a rich DL-Lite fragment in FO and Decidability of FO gives possibility for approximations.
Abstract
Evolution of Knowledge Bases (KBs) expressed in Description Logics (DLs) proved its importance. Recent studies of evolution in DLs mostly focussed on model-based approaches. They showed that evolution of KBs in tractable DLs, such as DL-Lite, suffers from inexpressibility, i.e., the result of evolution cannot be captured in DL-Lite. What is missing in these studies is understanding: in which DL-Lite fragments evolution can be captured, what causes the inexpressibility, which logics is sufficient to express evolution, and whether one can approximate it in DL-Lite. This paper provides some understanding of these issues for both update and revision. We found what DL-Lite formulas make evolution inexpressible and how to capture evolution in their absence. We introduce the notion of prototypes that gives an understanding of how to capture evolution for a rich DL-Lite fragment in FO[2]. Decidability of FO[2] gives possibility for approximations.

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Journal ArticleDOI

Capturing model-based ontology evolution at the instance level: The case of DL-Lite

TL;DR: What causes inexpressibility is described, and techniques are proposed that help to approximate evolution under the well-known approach by Winslett, which is inexpressible in DL-Lite.
Journal ArticleDOI

Prioritized assertional-based removed sets revision of DL-Lite belief bases

TL;DR: This paper investigates ”Prioritized Removed Sets Revision” (PRSR) for revising stratified DL-Lite knowledge bases when a new sure piece of information, called the input, is added, and rephrase Hansson's postulates for belief bases revision within a DL- lite setting, and gives logical properties of PRSR operators.
Journal ArticleDOI

On expansion and contraction of DL-Lite knowledge bases

TL;DR: This work investigates knowledge expansion and contraction for KBs expressed inDL - Lite, a family of description logics that underlie the tractable fragment OWL 2 QL of the Web Ontology Language OWL-2 and proposes a novel formula-based approach that respects principles and for which evolution is expressible in DL - Lite.
Journal Article

On Prototypes for Winslett's Semantics of DL−Lite ABox Evolution

TL;DR: This work shows which combination of DLLite logical constructs is responsible for the inexpressibility and explains reasons for such a behaviour and presents novel techniques to capture Winslett’s evolution in FO[2] for DL-LiteR.

Assertional-based Removed Set Revision of DL-LiteR Belief Bases.

TL;DR: This paper investigates the so-called “Removed Sets Revision” for revising DL-Lite knowledge bases when a new sure piece of information is added and shows that the removed sets revision can be achieved in polynomial time.
References
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Journal ArticleDOI

Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family

TL;DR: It is shown that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in thesize of the ABox, which is the first result ofPolynomial-time data complexity for query answering over DL knowledge bases.
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Linking data to ontologies

TL;DR: This paper presents a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances and a novel mapping language that is able to deal with the so-called impedance mismatch problem.
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The DL-lite family and relations

TL;DR: This article carries out a thorough and systematic investigation of inference in extensions of the original DL-Lite logics along five axes, by adding the Boolean connectives and number restrictions to concept constructs and adopting or dropping the unique name assumption.
Journal ArticleDOI

On the complexity of propositional knowledge base revision, updates, and counterfactuals

TL;DR: In this paper, the complexity of updating or revising propositional knowledge bases under the principle of Minimal Change was studied, and the complexity results for the following problem were derived: given a knowledge base T, an update p, and a formula q, decide whether q is derivable from T ○ p, the updated (or revised) knowledge base.
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