01274nas a2200217 4500008004100000245008200041210006900123260008800192520052900280653001200809653002200821653003100843653001000874653001700884653002600901100002100927700002100948700002700969700002000996856004001016 2011 eng d00aA Better Uncle For OWL - Nominal Schemas for Integrating Rules and Ontologies0 aBetter Uncle For OWL Nominal Schemas for Integrating Rules and O aNew YorkbProceedings of the 20th International World Wide Web Conference (WWW2011)3 aWe propose a description-logic style extension of OWL 2 with nominal schemas which can be used like 'variable nominal classes' within axioms. This feature allows ontology languages to express arbitrary DL-safe rules (as expressible in SWRL or RIF) in their native syntax. We show that adding nominal schemas to OWL 2 does not increase the worst-case reasoning complexity, and we identify a novel tractable language SROELV_3(⊓, X) that is versatile enough to capture the lightweight languages OWL EL and OWL RL.10aDatalog10aDescription Logic10aSemantic Web Rule Language10aSROIQ10atractability10aWeb Ontology Language1 aKrotzsch, Markus1 aMaier, Frederick1 aKrisnadhi, Adila, Alfa1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/109100851nas a2200133 4500008004100000245006500041210006500106520041700171100002100588700002100609700002700630700002000657856004000677 2011 eng d00aNominal Schemas for Integrating Rules and Description Logics0 aNominal Schemas for Integrating Rules and Description Logics3 aWe propose an extension of SROIQ with nominal schemas which can be used like Âvariable nominal conceptsÂ within axioms. This feature allows us to express arbitrary DL-safe rules in description logic syntax. We show that adding nominal schemas to SROIQ does not increase its worst-case reasoning complexity, and we identify a family of tractable DLs SROELVn that allow for restricted use of nominal schemas.1 aKrotzsch, Markus1 aMaier, Frederick1 aKrisnadhi, Adila, Alfa1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/183600446nam a2200133 4500008004100000245004500041210004500086653003200131653004500163100002000208700002100228700002300249856004000272 2010 eng d00aFoundations of Semantic Web Technologies0 aFoundations of Semantic Web Technologies10afoundations of semantic web10afoundations of semantic web technologies1 aHitzler, Pascal1 aKrotzsch, Markus1 aRudolph, Sebastian uhttp://knoesis.wright.edu/node/210400345nam a2200109 4500008004100000245004500041210004500086100002300131700002100154700002000175856004000195 2009 eng d00aFoundations of Semantic Web Technologies0 aFoundations of Semantic Web Technologies1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/209801355nas a2200133 4500008004100000245005200041210005200093520094500145100002301090700002101113700002701134700002001161856004001181 2008 eng d00aApproximate OWL Instance Retrieval with Screech0 aApproximate OWL Instance Retrieval with Screech3 aWith the increasing interest in expressive ontologies for the Semantic Web, it is critical to develop scalable and efficient ontology reasoning techniques that can properly cope with very high data volumes. For certain application domains, approximate reasoning solutions, which trade soundness or completeness for increased reasoning speed, will help to deal with the high computational complexities which state of the art ontology reasoning tools have to face. In this paper, we present a comprehensive overview of the SCREECH approach to approximate instance retrieval with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on experiments which show that the gain in efficiency outweighs the number of introduced mistakes in the reasoning process.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aTserendorj, Tuvshintur1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/118201274nas a2200157 4500008004100000245004300041210004200084260007400126300001200200520077300212100002300985700002101008700002701029700002001056856004001076 2008 eng d00aApproximate OWL-Reasoning with Screech0 aApproximate OWLReasoning with Screech aKarlsruhe, GermanybSecond International Conference, RR 2008c10/2008 a165-1803 aApplications of expressive ontology reasoning for the Semantic Web require scalable algorithms for deducing implicit knowledge from explicitly given knowledge bases. Besides the development of more efficient such algorithms, awareness is rising that approximate reasoning solutions will be helpful and needed for certain application domains. In this paper, we present a comprehensive overview of the Screech approach to approximate reasoning with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity.We present three different instantiations of the Screech approach, and report on experiments which show that a significant gain in efficiency can be achieved.
1 aRudolph, Sebastian1 aKrotzsch, Markus1 aTserendorj, Tuvshintur1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/125101114nas a2200145 4500008004100000245005900041210005900100260003000159300001200189520066300201100002300864700002100887700002000908856004000928 2008 eng d00aCheap Boolean Role Constructors for Description Logics0 aCheap Boolean Role Constructors for Description Logics aDresden, Germanyc09/2008 a362-3743 aWe investigate the possibility of incorporating Boolean role constructors on simple roles into some of today's most popular description logics, focussing on cases where those extensions do not increase complexity of reasoning. We show that the expressive DLs SHOIQ and SROIQ, serving as the logical underpinning of OWL and the forthcoming OWL 2, can accommodate arbitrary Boolean expressions. The prominent OWL-fragment SHIQ can be safely extended by safe role expressions, and the tractable fragments EL++ and DLP retain tractability if extended by conjunction on roles, where in the case of DLP the restriction on role simplicity can even be discarded.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/125501086nas a2200145 4500008004100000245009400041210006900135260009600204300001200300520052400312100002300836700002100859700002000880856004000900 2008 eng d00aDescription Logic Reasoning with Decision Diagrams: Compiling SHIQ to Disjunctive Datalog0 aDescription Logic Reasoning with Decision Diagrams Compiling SHI aKarlsruhe, GermanybThe Semantic Web - ISWC 2008, 7th International Semantic Web Conference a435-4503 aWe propose a novel method for reasoning in the description logic SHIQ. After a satisfiability preserving transformation from SHIQ to the description logic ALCIb, the obtained ALCIb Tbox T is converted into an ordered binary decision diagram (OBDD) which represents a canonical model for T. This OBDD is turned into a disjunctive datalog program that can be used for Abox reasoning. The algorithm is worst-case optimal w.r.t. data complexity, and admits easy extensions with DL-safe rules and ground conjunctive queries.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/124801221nas a2200145 4500008004100000245002800041210002800069260002800097300001000125520083600135100002300971700002100994700002001015856004001035 2008 eng d00aDescription Logic Rules0 aDescription Logic Rules aPatras, Greecec07/2008 a80-843 aWe introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ - the basis for the ongoing standardisation of OWL 2 - can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ is highly intractable, it turns out that DL rules can be introduced to various lightweight DLs without increasing their worst-case complexity. In particular, DL rules enable us to significantly extend the tractable DLs EL++ and DLP.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/125701162nas a2200121 4500008004100000245003500041210003400076520082600110100002100936700002300957700002000980856004001000 2008 eng d00aELP: Tractable Rules for OWL 20 aELP Tractable Rules for OWL 23 aWe introduce ELP as a decidable fragment of the Semantic Web Rule Language (SWRL) that admits reasoning in polynomial time. ELP is based on the tractable description logic EL++, and encompasses an extended notion of the recently proposed DL rules for that logic. Thus ELP extends EL++ with a number of features introduced by the forthcoming OWL 2, such as disjoint roles, local reflexivity, certain range restrictions, and the universal role.We present a reasoning algorithm based on a translation of ELP to Datalog, and this translation also enables the seamless integration of DL-safe rules into ELP.While reasoning with DL-safe rules as such is already highly intractable, we show that DL-safe rules based on the Description Logic Programming (DLP) fragment of OWL 2 can be admitted in ELP without losing tractability.1 aKrotzsch, Markus1 aRudolph, Sebastian1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/125301164nas a2200121 4500008004100000245003500041210003400076520082800110100002300938700002100961700002000982856004001002 2008 eng d00aELP: Tractable Rules for OWL 20 aELP Tractable Rules for OWL 23 aWe introduce ELP as a decidable fragment of the Semantic Web Rule Language (SWRL) that admits reasoning in polynomial time. ELP is based on the tractable description logic EL++, and encompasses an extended notion of the recently proposed DL rules for that logic. Thus ELP extends EL++ with a number of features introduced by the forthcoming OWL 2, such as disjoint roles, local reflexivity, certain range restrictions, and the universal role. We present a reasoning algorithm based on a translation of ELP to Datalog, and this translation also enables the seamless integration of DL-safe rules into ELP. While reasoning with DL-safe rules as such is already highly intractable, we show that DL-safe rules based on the Description Logic Programming (DLP) fragment of OWL 2 can be admitted in ELP without losing tractability.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/125201162nas a2200121 4500008004100000245003500041210003400076520082600110100002100936700002300957700002000980856004001000 2008 eng d00aELP: Tractable Rules for OWL 20 aELP Tractable Rules for OWL 23 aWe introduce ELP as a decidable fragment of the Semantic Web Rule Language (SWRL) that admits reasoning in polynomial time. ELP is based on the tractable description logic EL++, and encompasses an extended notion of the recently proposed DL rules for that logic. Thus ELP extends EL++ with a number of features introduced by the forthcoming OWL 2, such as disjoint roles, local reflexivity, certain range restrictions, and the universal role.We present a reasoning algorithm based on a translation of ELP to Datalog, and this translation also enables the seamless integration of DL-safe rules into ELP.While reasoning with DL-safe rules as such is already highly intractable, we show that DL-safe rules based on the Description Logic Programming (DLP) fragment of OWL 2 can be admitted in ELP without losing tractability.1 aKrotzsch, Markus1 aRudolph, Sebastian1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/193501233nas a2200121 4500008004100000245006500041210006500106520083600171100002301007700002101030700002001051856004001071 2008 eng d00aExpressive Tractable Description Logics based on SROIQ Rules0 aExpressive Tractable Description Logics based on SROIQ Rules3 aWe introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ - the basis for the ongoing standardisation of OWL 2 - can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ is highly intractable, it turns out that DL rules can be introduced to various lightweight DLs without increasing their worst-case complexity. In particular, DL rules enable us to significantly extend the tractable DLs EL++ and DLP.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/193300339nam a2200121 4500008004100000245002900041210002800070100002300098700001500121700002100136700002000157856004000177 2008 eng d00aSemantic Web. Grundlagen0 aSemantic Web Grundlagen1 aRudolph, Sebastian1 aSure, York1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/210500898nas a2200121 4500008004100000245007500041210006900116520048700185100002300672700002100695700002000716856004000736 2008 eng d00aTerminological Reasoning in SHIQ with Ordered Binary Decision Diagrams0 aTerminological Reasoning in SHIQ with Ordered Binary Decision Di3 aWe present a new algorithm for reasoning in the description logic SHIQ, which is the most prominent fragment of the Web Ontology Language OWL. The algorithm is based on ordered binary decision diagrams (OBDDs) as a data structure for storing and operating on large model representations. We thus draw on the success and the proven scalability of OBDD-based systems. To the best of our knowledge, we present the very first algorithm for using OBDDs for reasoning with general Tboxes.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/125400898nas a2200121 4500008004100000245007500041210006900116520048700185100002300672700002100695700002000716856004000736 2008 eng d00aTerminological Reasoning in SHIQ with Ordered Binary Decision Diagrams0 aTerminological Reasoning in SHIQ with Ordered Binary Decision Di3 aWe present a new algorithm for reasoning in the description logic SHIQ, which is the most prominent fragment of the Web Ontology Language OWL. The algorithm is based on ordered binary decision diagrams (OBDDs) as a data structure for storing and operating on large model representations. We thus draw on the success and the proven scalability of OBDD-based systems. To the best of our knowledge, we present the very first algorithm for using OBDDs for reasoning with general Tboxes.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/193201111nas a2200133 4500008004100000245005400041210005400095260004000149520068400189100002300873700002100896700002000917856004000937 2007 eng d00aComplexity Boundaries for Horn Description Logics0 aComplexity Boundaries for Horn Description Logics aVancouver, British Columbia, Canada3 aHorn description logics (Horn-DLs) have recently started to attract attention due to the fact that their (worst-case) data complexities are in general lower than their overall (i.e. combined) complexities, which makes them attractive for reasoning with large ABoxes. However, the natural question whether Horn-DLs also provide advantages for TBox reasoning has hardly been addressed so far. In this paper, we therefore provide a thorough and comprehensive analysis of the combined complexities of Horn-DLs. While the combined complexity for many Horn-DLs turns out to be the same as for their non-Horn counterparts, we identify subboolean DLs where Hornness simplifies reasoning.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/121701035nas a2200121 4500008004100000245004200041210004200083520068400125100002300809700002100832700002000853856004000873 2007 eng d00aComplexity of Horn Description Logics0 aComplexity of Horn Description Logics3 aHorn description logics (Horn-DLs) have recently started to attract attention due to the fact that their (worst-case) data complexities are in general lower than their overall (i.e. combined) complexities, which makes them attractive for reasoning with large ABoxes. However, the natural question whether Horn-DLs also provide advantages for TBox reasoning has hardly been addressed so far. In this paper, we therefore provide a thorough and comprehensive analysis of the combined complexities of Horn-DLs. While the combined complexity for many Horn-DLs turns out to be the same as for their non-Horn counterparts, we identify subboolean DLs where Hornness simplifies reasoning.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/193101132nas a2200145 4500008004100000245006000041210005900101260014000160300001200300520057000312100002300882700002100905700002000926856004000946 2007 eng d00aConjunctive Queries for a Tractable Fragment of OWL 1.10 aConjunctive Queries for a Tractable Fragment of OWL 11 aBusan, KoreabThe Semantic Web, 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWCc11/2007 a310-3233 aDespite the success of the Web Ontology Language OWL, the development of expressive means for querying OWL knowledge bases is still an open issue. In this paper, we investigate how a very natural and desirable form of queries-namely conjunctive ones-can be used in conjunction with OWL such that one of the major design criteria of the latter-namely decidability-can be retained. More precisely, we show that querying the tractable fragment EL++ of OWL 1.1 is decidable. We also provide a complexity analysis and show that querying unrestricted EL++ is undecidable.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/126201103nas a2200169 4500008004100000245006200041210006000103260002300163300001200186520059000198100002300788700002100811700002000832700002100852700002000873856004000893 2007 eng d00aEfficient OWL Reasoning with Logic Programs - Evaluations0 aEfficient OWL Reasoning with Logic Programs Evaluations aInnsbruck, Austria a370-3733 aWe report on efficiency evaluations concerning two different approaches to using logic programming for OWL [1] reasoning and show, how the two approaches can be combined. Introduction. Scalability of reasoning remains one of the major obstacles in leveraging the full power of the Web Ontology Language OWL [1] for practical applications. Among the many possible approaches to address scalability, one of them concerns the use of logic programming for this purpose. It was recently shown that reasoning in Horn-SHIQ [2-4] can be realised by invoking Prolog systems on the output of the1 aRudolph, Sebastian1 aKrotzsch, Markus1 aSintek, Michael1 aVrandecic, Denny1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/120500902nas a2200133 4500008004100000245008600041210006900127260001800196520045000214100002300664700002100687700002000708856004000728 2007 eng d00aQuo Vadis, CS? - On the (non)-impact of Conceptual Structures on the Semantic Web0 aQuo Vadis CS On the nonimpact of Conceptual Structures on the Se aSheffield, UK3 aConceptual Structures is a field of research which shares abstract concepts and interests with recent work on knowledge representation for the Semantic Web. However, while the latter is an area of research and development which is rapidly expanding in recent years, the former fails to participate in these developments on a large scale. In this paper, we attempt to stimulate the Conceptual Structures community to catch the Semantic Web train.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/121801397nas a2200133 4500008004100000245004900041210004200090260006400132520096300196100002301159700002101182700002001203856004001223 2006 eng d00aOn the Complexity of Horn Description Logics0 aComplexity of Horn Description Logics bSecond Workshop OWL - Experiences and Directions, OWLED20063 aHorn-*SHIQ* has been identified as a fragment of the description logic *SHIQ* for which inferencing is in PT_{IME} with respect to the size of the ABox. This enables reasoning with larger ABoxes in situations where the TBox is static, and represents one approach towards tractable description logic reasoning. In this paper, we show that reasoning in Horn-*SHIQ*, in spite of its low datacomplexity, is E_{xp}T_{IME}-hard with respect to the overall size of the knowledge base. While this result is not unexpected, the proof is not a mere modification of existing reductions since it has to account for the restrictions of Hornness. We establish the result for Horn-*FLE*, showing that Hornness does not simplify TBox reasoning even for very restricted description logics. Moreover, we derive a context-free grammar that defines Horn-*SHIQ* in a simpler and more intuitive way than existing characterisations.1 aRudolph, Sebastian1 aKrotzsch, Markus1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/184101385nas a2200157 4500008004100000245005700041210005700098260002000155300001000175520093200185100001701117700001801134700001501152700002001167856004001187 2006 eng d00aHow to Reason with OWL in a Logic Programming System0 aHow to Reason with OWL in a Logic Programming System aAthens, Georgia a17-263 aLogic programming has always been a major ontology modeling paradigm, and is frequently being used in large research projects and industrial applications, e.g., by means of the F-Logic reasoning engine OntoBroker or the TRIPLE query, inference, and transformation language and system. At the same time, the Web Ontology Language OWL has been recommended by the W3C for modeling ontologies for the web. Naturally, it is desirable to investigate the interoperability between both paradigms. In this paper, we do so by studying an expressive fragement of OWL DL for which reasoning can be reduced to the evaluation of Horn logic programs. Building on the KAON2 algorithms for transforming OWL DL into disjunctive Datalog, we give a detailed account of how and to what extent OWL DL can be employed in standard logic programming systems. En route, we derive a novel, simplified characterization of the supported fragment of OWL DL.1 aKrotzsch, M.1 aVrandecic, D.1 aSintek, M.1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/121100996nas a2200133 4500008004100000245005400041210005400095260002100149300001200170520060300182100001700785700002000802856004000822 2006 eng d00aQuerying Formal Contexts with Answer Set Programs0 aQuerying Formal Contexts with Answer Set Programs aAalborg, Denmark a260-2733 aRecent studies showed how a seamless integration of formal concept analysis (FCA), logic of domains, and answer set programming (ASP) can be achieved. Based on these results for combining hierarchical knowledge with classical rule-based formalisms, we introduce an expressive common-sense query language for formal contexts. Although this approach is conceptually based on order-theoretic paradigms, we show how it can be implemented on top of standard ASP systems. Advanced features, such as default negation and disjunctive rules, thus become practically available for processing contextual data.1 aKrotzsch, M.1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/121001422nas a2200121 4500008004100000245008200041210006900123520101600192100002101208700001601229700001501245856004001260 2005 eng d00aCategory Theory in Ontology Research: Concrete Gain from an Abstract Approach0 aCategory Theory in Ontology Research Concrete Gain from an Abstr3 aThe focus of research on representing and reasoning with knowledge traditionally has been on single speciÃ¯Â¬Âcations and appropriate inference paradigms to draw conclusions from such data. Accordingly, this is also an essential aspect of ontology research which has received much attention in recent years. But ontologies introduce another new challenge based on the distributed nature of most of their applications, which requires to relate heterogeneous ontological speciÃ¯Â¬Âcations and to integrate information from multiple sources. These problems have of course been recognized, but many current approaches still lack the deep formal backgrounds on which todays reasoning paradigms are already founded. Here we propose category theory as a well-explored and very extensive mathematical foundation for modelling distributed knowledge. A particular prospect is to derive conclusions from the structure of those distributed knowledge bases, as it is for example needed when merging ontologies.1 aKrotzsch, Markus1 aEhrig, Marc1 aSure, York uhttp://knoesis.wright.edu/node/192200618nas a2200145 4500008004100000245003500041210003200076520023400108100001500342700001700357700002100374700001700395700002000412856004000432 2005 eng d00aDLP Isn't So Bad After All0 aDLP Isn39t So Bad After All3 aWe discuss some of the recent controversies concerning the DLP fragment of OWL. We argue that it is a meaningful fragment and can serve as a basic interoperability layer between OWL and logic programming-based ontology languages.1 aSure, York1 aStuder, Rudi1 aKrotzsch, Markus1 aHaase, Peter1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/184000366nas a2200133 4500008004100000245003100041210003000072100002000102700001500122700001700137700002100154700001700175856004000192 2005 eng d00aDLP Isn't So Bad After All0 aDLP Isnt So Bad After All1 aHitzler, Pascal1 aSure, York1 aStuder, Rudi1 aKrotzsch, Markus1 aHaase, Peter uhttp://knoesis.wright.edu/node/232101229nas a2200145 4500008004100000245002500041210002500066260002000091300001200111520085800123100002100981700002101002700002001023856004001043 2005 eng d00aMorphisms in Context0 aMorphisms in Context aKassel, Germany a223-2373 aMorphisms constitute a general tool for modelling complex relationships between mathematical objects in a disciplined fashion. In Formal Concept Analysis (FCA), morphisms can be used for the study of structural properties of knowledge represented in formal contexts, with applications to data transformation and merging. In this paper we present a comprehensive treatment of some of the most important morphisms in FCA and their relationships, including dual bonds, scale measures, infomorphisms, and their respective relations to Galois connections. We summarize our results in a concept lattice that cumulates the relationships among the considered morphisms. The purpose of this work is to lay a foundation for applications of FCA in ontology research and similar areas, where morphisms help formalize the interplay among distributed knowledge bases.1 aKrotzsch, Markus1 aZhang, Guo-Qiang1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/119902380nas a2200145 4500008004100000245008200041210006900123260006500192520186500257100001502122700002102137700001602158700002002174856004002194 2005 eng d00aWhat Is Ontology Merging? - A Category-Theoretical Perspective Using Pushouts0 aWhat Is Ontology Merging A CategoryTheoretical Perspective Using b20th National Conference on Artificial Intelligence, AAAI-053 aIn this paper we explain how merging of ontologies is captured by the pushout construction from category theory, and argue that this is a very natural approach to the problem. We study this independent of a specific choice of ontology representation language, and thus provide a sort of blueprint for the development of algorithms applicable in practice. For this purpose, we view category theory as a universal 'meta specification language' that enables us to specify properties of ontological relationships and constructions in a way that does not depend on any particular implementation. This can be achieved since the basic objects of study in category theory are the relationships between multiple ontological specifications, not the internal structure of a single knowledge representation. Categorical pushouts are already considered in some approaches to ontology research (Jannink et al. 1998; Schorlemmer, Potter, & Robertson 2002; Goguen 2005; Kent 2005) and we do not claim our treatment to be entirely original. Still we have the impression that the potential of category theoretic approaches is by far not exhausted in todays ontology research. For our particular case the treatment will focus on the ontology merging, for which we will give both intuitive explanations and precise definitions. This reflects our belief that, at the current stage of research, it is not desirable to fade out the mathematical details of the categorical approach completely, since the interfaces to current techniques in ontology research are not yet available to their full extent. We will also keep this treatment rather general, not narrowing the discussion to specific formalisms - this added generality is one of the strengths of category theory. A long version of this paper with a tutorial character is available from the first author's homepage.1 aSure, York1 aKrotzsch, Markus1 aEhrig, Marc1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/1806