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When Are Description Logic Knowledge Bases Indistinguishable?∗

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When Are Description Logic Knowledge Bases Indistinguishable?∗ When Are Description Logic Knowledge Bases Indistinguishable?∗ E. Botoeva,1 R. Kontchakov,3 V. Ryzhikov,1 F. Wolter2 and M. Zakharyaschev3 1Faculty of Computer Science 2Dept. of Computer Science 3Dept. of Computer Science Free University of Bozen-Bolzano, Italy University of Liverpool, UK Birkbeck, London, UK fbotoeva,[email protected] [email protected] froman,[email protected] Abstract ABox, Aa, in the automotive domain is given by Deciding inseparability of description logic knowl- Hybrid(toyota highlander); edge bases (KBs) with respect to conjunctive Minivan(toyota highlander); Minivan(nissan note): queries is fundamental for many KB engineering Typical applications of KBs in modern information systems and maintenance tasks including versioning, mod- use the semantics of concepts and roles in the TBox to enable ule extraction, knowledge exchange and forget- the user to query the data in the ABox. This is particularly ting. We study the combined and data complex- useful if the data is incomplete or comes from heterogenous ity of this inseparability problem for fragments of data sources which is the case, for example, in linked data Horn-ALCHI, including the description logics un- applications [Polleres et al., 2013] and large scale data inte- derpinning OWL 2 QL and OWL 2 EL. gration projects [Poggi et al., 2008; Giese et al., 2013], or if the data comprises web content gathered by search engines 1 Introduction using semantic markup [Hitzler et al., 2009]. As the data may be incomplete, the open world assumption A description logic (DL) knowledge base (KB) consists of a is made when querying a KB K: a tuple a of individuals from terminological box (TBox) and an assertion box (ABox). The K is a (certain) answer to a query q over K iff q(a) is true in TBox represents conceptual knowledge by providing a vocab- every model I of K. As general first-order queries are unde- ulary for a domain of interest together with axioms that de- cidable under the open-world semantics, the basic and most scribe semantic relationships between the vocabulary items. important querying instrument is conjunctive queries (CQs), To illustrate, the following toy TBox, Ta, defines a vocabu- which are ubiquitous in relational database systems and form lary for the automotive industry: the core of the Semantic Web query language SPARQL. A Minivan v Automobile; Hybrid v Automobile; CQ q(x) is a first-order formula 9y '(x; y), where '(x; y) is a conjunction of atoms of the form A(z ) or P (z ; z ) for Automobile v 9poweredBy:Engine; 1 1 2 a concept name A, a role name P , and variables z1; z2 from Hybrid v 9poweredBy:EEngine u 9poweredBy:ICEngine; x; y.1 For instance, to find minivans powered by electric en- EEngine v Engine; ICEngine v Engine: gines, one can use the following CQ: For example, the first two axioms say that minivans and hy- q(x) = 9y (Minivan(x) ^ poweredBy(x; y) ^ EEngine(y)): brids are automobiles; the third axiom claims that every auto- Then toyota highlander is its only certain answer in (Ta; Aa). mobile is powered by an engine. Thus, the TBox introduces, The problem of answering CQs over KBs has been the among others, concept names (sets) Minivan, Automobile and focus of significant research in the DL community with Engine, states that the concept Minivan is subsumed by the deep complexity results for a large variety of DLs (see be- concept Automobile and uses the role name (binary relation) low), the introduction of new DLs for which query answer- poweredBy to say that automobiles are powered by engines. ing is tractable for data complexity [Hustadt et al., 2005; The last two axioms state that electric and internal combus- Calvanese et al., 2007], the invention of various query an- tion engines are engines. TBoxes are often called ontologies swering techniques [Calvanese et al., 2007; Lutz et al., 2009] and presented in applications in terms of the Web Ontology and the development of powerful implemented systems; see, Language OWL 2, which is underpinned by DLs. e.g., [Kontchakov and Zakharyaschev, 2014] and references The ABox of a KB is a set of facts storing data about the therein. concept and role names introduced in the TBox. An example Apart from developing query answering techniques, a ma- jor research problem is KB engineering and maintenance. In ∗This paper was invited for submission to the Best Papers From Sister Conferences Track, based on a paper that appeared in the 1Since we consider Horn DLs, the results of this paper actually Proc. of the 14th Int. Conf. on Principles of Knowledge Representa- apply to disjunctions (or unions) of CQs (UCQs). For simplicity, tion and Reasoning (KR 2014). however, we concentrate on CQs only. fact, with typically large data and often complex and tangled minimal Σ-query module from a KB using a polynomial-time ontologies, tool support for transforming and comparing KBs algorithm with the Σ-query inseparability check as an oracle. is becoming indispensable for applications. To begin with, To illustrate the notion of Σ-query module, consider the au- KBs are never static entities. Like most software artefacts, tomotive ontology Ka = (Ta; Aa) described above and the they are updated to incorporate new information, and dis- signature Σm = fAutomobile; Engine; poweredByg. Then tinct versions are introduced for different applications. Thus, Km = (Tm; Aa) is a Σm-query module of Ka, where Tm is developing support for KB versioning has become a major Minivan v Automobile; Automobile v 9poweredBy:Engine: research problem [Jimenez-Ruiz´ et al., 2011; Konev et al., 2012]. As dealing with a large and semantically tangled KB Knowledge Exchange. In knowledge exchange, we want can be costly, one may want to extract from it a smaller mod- to transform a KB K1 in a signature Σ1 to a KB K2 ule that is indistinguishable from the whole KB as far as the in a new signature Σ2 connected to Σ1 via a declarative given application is concerned [Stuckenschmidt et al., 2009]. mapping specification given by a TBox T12. Such map- Another technique for extracting relevant information is for- ping specifications between KBs are also known as ontol- getting, where the task is to replace a given KB by a new ogy alignments or ontology matchings and have been stud- KB using only those concept and role names that are needed ied extensively [Shvaiko and Euzenat, 2013]. If, as above, by the application but still providing the same information we are interested in querying data via CQs, then the tar- about those names as the original KB [Konev et al., 2009; get KB K2 should be a sound and complete representa- Koopmann and Schmidt, 2014b]. Finally, the vocabulary of a tion of K1 w.r.t. querying data, and so satisfy the condi- given KB may not be convenient for a new application. In tion K1 [T12 ≡Σ2 K2, in which case it is called a univer- this case, similarly to data exchange in databases [Arenas sal CQ-solution. To illustrate, consider again the ontology et al., 2014]—where data structured under a source schema Ka = (Ta; Aa), and let Tae relate the signature Σa of Ka to is converted to data under a target schema—one may want Σe = fCar; HybridCar; ElectricMotor; Motor; hasMotorg: to transform a KB in a source signature to a KB given in Automobile v Car; Hybrid v HybridCar; a more useful target signature and representing the original Engine v Motor; EEngine v ElectricMotor; knowledge ex- KB in an accurate way. This task is known as poweredBy v hasMotor: change [Arenas et al., 2012; 2013]. In this paper, we investigate a relationship between KBs Then Ke = (Te; Ae) is a universal CQ-solution, where that is fundamental for all such tasks if querying the data via Te = f ElectricMotor v Motor; Car v 9hasMotor:Motor; CQs is the main application. Let Σ be a signature consist- HybridCar v Car u 9hasMotor:ElectricMotor g; ing of a set of concept and role names. We say that KBs K1 A = f HybridCar(toyota highlander); Car(nissan note) g: and K are Σ-query inseparable and write K ≡ K if any e 2 1 Σ 2 0 CQ formulated in Σ has the same answers over K and K . Forgetting. A KB K results from forgetting a signature Σ 1 2 0 0 Note that even for Σ containing all concept and role names in in a KB K if K ≡sig(K)nΣ K and sig(K ) ⊆ sig(K) n Σ, the KBs, Σ-query inseparability does not necessarily imply where sig(K) is the signature of K. Thus, the result of for- logical equivalence: e.g., (;; fA(a)g) is fA; Bg-query insep- getting Σ does not use Σ and gives the same answers to CQs arable from (fB v Ag; fA(a)g) but the two KBs are clearly without symbols in Σ as K. The result of forgetting is also not logically equivalent. Thus, if KBs are used for purposes called a uniform interpolant for K w.r.t. sig(K) n Σ. Forget- other than querying data via CQs, then different notions of ting is of interest for a number of applications. Typically, inseparability are required. We now discuss the applications when reusing an existing KB in a new application, only a of Σ-query inseparability for the tasks above in more detail. small number of its symbols is relevant, and so instead of reusing the whole KB, one can take the potentially smaller Versioning. Version control systems for KBs provide a range KB resulting from forgetting the extraneous symbols.
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