Jiaqi Li
ABSTRACT
This paper tackles the problem of computing views of OWL ontologies using a forgetting-based approach. In traditional relational databases, a view is a subset of a database, whereas in ontologies, a view is more than a subset; it contains not only axioms contained in the original ontology, but may also contain newly-derived axioms entailed by the original ontology (implicitly contained in the original ontology). Specifically, given an ontology , the signature of is the set of all the names in , and a view of is a new ontology obtained from using only part of ’s signature, namely the target signature, while preserving all logical entailments up to the target signature. Computing views of OWL ontologies is useful for Semantic Web applications such as ontology-based query answering, in a way that the view can be used as a substitute of the original ontology to answer queries formulated with the target signature, and information hiding, in the sense that it restricts users from viewing certain information of an ontology.
Forgetting is a form of non-standard reasoning concerned with eliminating from an ontology a subset of its signature, namely the forgetting signature, in such a way that all logical entailments are preserved up to the target signature. Forgetting can thus be used as a means for computing views of OWL ontologies — the solution of forgetting a set of names from an ontology is the view of for the target signature .
In this paper, we present a forgetting-based method for computing views of OWL ontologies specified in the description logic , the basic extended with role hierarchy, nominals and inverse roles. The method is terminating and sound. Despite the method not being complete, an evaluation with a prototype implementation of the method on a corpus of real-world ontologies has shown very good success rates. This is very useful from the perspective of the Semantic Web, as it provides knowledge engineers with a powerful tool for creating views of OWL ontologies.
- Wilhelm Ackermann. 1935. Untersuchungen Math 366ber das Eliminationsproblem der mathematischen Logik. Math. Ann. 110, 1 (1935), 390–413.Google Scholar
Cross Ref
- Franz Baader, Ian Horrocks, Carsten Lutz, and Ulrike Sattler. 2017. An Introduction to Description Logic. Cambridge University Press.Google Scholar
- Leo Bachmair, Harald Ganzinger, David A. McAllester, and Christopher Lynch. 2001. Resolution Theorem Proving. See Robinson and Voronkov [41], 19–99.Google Scholar
- Jieying Chen, Ghadah Alghamdi, Renate A. Schmidt, Dirk Walther, and Yongsheng Gao. 2019. Ontology Extraction for Large Ontologies via Modularity and Forgetting. In Proc. K-CAP’19, Mayank Kejriwal, Pedro A. Szekely, and Raphaël Troncy (Eds.). ACM, 45–52.Google ScholarDigital Library
- Mathieu d’Aquin. 2012. Modularizing Ontologies. In Ontology Engineering in a Networked World. Springer, 213–233.Google Scholar
- Warren Del-Pinto and Renate A. Schmidt. 2019. ABox Abduction via Forgetting in ALC. In Proc. AAAI’19. 2768–2775.Google ScholarDigital Library
- Patrick Doherty and Andrzej Szalas. 2020. Rough Forgetting. In Proc. IJCRS’20(LNCS, Vol. 12179). Springer, 3–18.Google Scholar
- T. Eiter, G. Ianni, R. Schindlauer, H. Tompits, and K. Wang. 2006. Forgetting in Managing Rules and Ontologies. In Web Intelligence. IEEE Computer Society, 411–419.Google Scholar
- Christian G. Fermüller, Alexander Leitsch, Ullrich Hustadt, and Tanel Tammet. 2001. Resolution Decision Procedures. See Robinson and Voronkov [41], 1791–1849.Google Scholar
- William Gatens, Boris Konev, and Frank Wolter. 2014. Lower and Upper Approximations for Depleting Modules of Description Logic Ontologies. In Proc. ECAI’14(Frontiers in Artificial Intelligence and Applications, Vol. 263). IOS Press, 345–350.Google Scholar
- Erich Grädel and Igor Walukiewicz. 1999. Guarded Fixed Point Logic. In Proc. LICS’99. IEEE Computer Society, 45–54.Google ScholarCross Ref
- Bernardo Cuenca Grau, Ian Horrocks, Yevgeny Kazakov, and Ulrike Sattler. 2008. Modular Reuse of Ontologies: Theory and Practice. J. Artif. Intell. Res. 31 (2008), 273–318.Google ScholarCross Ref
- B. C. Grau and B. Motik. 2012. Reasoning over Ontologies with Hidden Content: The Import-by-Query Approach. J. Artif. Intell. Res. 45 (2012), 197–255.Google ScholarDigital Library
- Pascal Hitzler, Markus Krötzsch, and Sebastian Rudolph. 2010. Foundations of Semantic Web Technologies. Chapman and Hall/CRC Press.Google Scholar
- Michel C. A. Klein and Dieter Fensel. 2001. Ontology versioning on the Semantic Web. In Proc. SWWS’01. 75–91.Google Scholar
- Michel C. A. Klein, Dieter Fensel, Atanas Kiryakov, and Damyan Ognyanov. 2002. Ontology Versioning and Change Detection on the Web. In Proc. EKAW’02(Lecture Notes in Computer Science, Vol. 2473), Asunción Gómez-Pérezand V. Richard Benjamins (Eds.). Springer, 197–212.Google ScholarCross Ref
- Boris Konev, Carsten Lutz, Dirk Walther, and Frank Wolter. 2013. Model-theoretic inseparability and modularity of description logic ontologies. Artif. Intell. 203(2013), 66–103.Google ScholarDigital Library
- Boris Konev, Dirk Walther, and Frank Wolter. 2008. The Logical Difference Problem for Description Logic Terminologies. In IJCAR(Lecture Notes in Computer Science, Vol. 5195). Springer, 259–274.Google Scholar
- Boris Konev, Dirk Walther, and Frank Wolter. 2009. Forgetting and Uniform Interpolation in Large-Scale Description Logic Terminologies. In Proc. IJCAI’09. IJCAI/AAAI Press, 830–835.Google Scholar
- Patrick Koopmann. 2015. Practical Uniform Interpolation for Expressive Description Logics. Ph.D. Dissertation. The University of Manchester, UK.Google Scholar
- Patrick Koopmann and Jieying Chen. 2020. Deductive Module Extraction for Expressive Description Logics. In Proc. IJCAI’20. ijcai.org, 1636–1643.Google ScholarCross Ref
- Patrick Koopmann, Warren Del-Pinto, Sophie Tourret, and Renate A. Schmidt. 2020. Signature-Based Abduction for Expressive Description Logics. In Proc. KR’20. 592–602.Google ScholarCross Ref
- P. Koopmann and R. A. Schmidt. 2013. Forgetting Concept and Role Symbols in Math-Ontologies. In Proc. LPAR’13(Lecture Notes in Computer Science, Vol. 8312). Springer, 552–567.Google Scholar
- Patrick Koopmann and Renate A. Schmidt. 2013. Uniform Interpolation of Math-Ontologies Using Fixpoints. In Proc. FroCos’13(Lecture Notes in Computer Science, Vol. 8152). Springer, 87–102.Google Scholar
- Patrick Koopmann and Renate A. Schmidt. 2014. Count and Forget: Uniform Interpolation of Math-Ontologies. In Proc. IJCAR’14(Lecture Notes in Computer Science, Vol. 8562). Springer, 434–448.Google Scholar
- Patrick Koopmann and Renate A. Schmidt. 2015. Saturated-Based Forgetting in the Description Logic Math. In Proc. DL’15(CEUR Workshop Proceedings, Vol. 1350). CEUR-WS.org.Google Scholar
- Patrick Koopmann and Renate A. Schmidt. 2015. Uniform Interpolation and Forgetting for Math 367-Ontologies with ABoxes. In Proc. AAAI’15. AAAI Press, 175–181.Google Scholar
- Patrick Lambrix and He Tan. 2008. Ontology Alignment and Merging. In Anatomy Ontologies for Bioinformatics, Principles and Practice. Computational Biology, Vol. 6. Springer, 133–149.Google Scholar
- Jérôme Lang, Paolo Liberatore, and Pierre Marquis. 2003. Propositional Independence: Formula-Variable Independence and Forgetting. J. Artif. Intell. Res. 18 (2003), 391–443.Google ScholarDigital Library
- Fangzhen Lin and Ray Reiter. 1994. Forget It!. In Proc. AAAI Fall Symposium on Relevance. AAAI Press, 154–159.Google Scholar
- Michel Ludwig and Boris Konev. 2014. Practical Uniform Interpolation and Forgetting for Math 368 TBoxes with Applications to Logical Difference. In Proc. KR’14. AAAI Press.Google Scholar
- C. Lutz, I. Seylan, and F. Wolter. 2012. An Automata-Theoretic Approach to Uniform Interpolation and Approximation in the Description Logic Math 369. In Proc. KR’12. AAAI Press, 286–297.Google Scholar
- C. Lutz and F. Wolter. 2011. Foundations for Uniform Interpolation and Forgetting in Expressive Description Logics. In Proc. IJCAI’11. IJCAI/AAAI Press, 989–995.Google Scholar
- Nicolas Matentzoglu and Bijan Parsia. 2017. BioPortal Snapshot 30.03.2017. https://doi.org/10.5281/zenodo.439510Google Scholar
- Nadeschda Nikitina and Sebastian Rudolph. 2014. (Non-)Succinctness of uniform interpolants of general terminologies in the description logic Math 370. Artif. Intell. 215(2014), 120–140.Google ScholarDigital Library
- Natalya Fridman Noy and Mark A. Musen. 2000. PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In Proc. AAAI/IAAI’00. AAAI Press/The MIT Press, 450–455.Google Scholar
- Natalya Fridman Noy and Mark A. Musen. 2004. Ontology Versioning in an Ontology Management Framework. IEEE Intelligent Systems 19, 4 (2004), 6–13.Google ScholarDigital Library
- María Poveda-Villalón, Asunción Gómez-Pérez, and Mari Carmen Suárez-Figueroa. 2014. OOPS! (OntOlogy Pitfall Scanner!): An On-line Tool for Ontology Evaluation. Int. J. Semantic Web Inf. Syst. 10, 2 (2014), 7–34.Google ScholarDigital Library
- Guilin Qi, Yimin Wang, Peter Haase, and Pascal Hitzler. 2008. A Forgetting-based Approach for Reasoning with Inconsistent Distributed Ontologies. In Proc. WoMO’08(CEUR Workshop Proceedings, Vol. 348). CEUR-WS.org.Google Scholar
- Márcio Moretto Ribeiro and Renata Wassermann. 2009. Base Revision for Ontology Debugging. J. Log. Comput. 19, 5 (2009), 721–743.Google ScholarDigital Library
- John Alan Robinson and Andrei Voronkov (Eds.). 2001. Handbook of Automated Reasoning (in 2 volumes). Elsevier and MIT Press.Google Scholar
- R. A. Schmidt and D. Tishkovsky. 2014. Using tableau to decide description logics with full role negation and identity. ACM Trans. Comput. Log. 15, 1 (2014), 7:1–7:31.Google ScholarDigital Library
- Dan Schrimpsher, Zhiqiang Wu, Anthony M. Orme, and Letha H. Etzkorn. 2010. Dynamic ontology version control. In Proc. ACMse’10. ACM, 25.Google ScholarDigital Library
- Kent A. Spackman. 2000. SNOMED RT and SNOMED CT. Promise of an international clinical ontology. M.D. Computing 17 (2000).Google Scholar
- Nicolas Troquard, Roberto Confalonieri, Pietro Galliani, Rafael Peñaloza, Daniele Porello, and Oliver Kutz. 2018. Repairing Ontologies via Axiom Weakening. In Proc. AAAI’18. AAAI Press, 1981–1988.Google Scholar
- K. Wang, G. Antoniou, R. W. Topor, and A. Sattar. 2005. Merging and Aligning Ontologies in DL-Programs. In RuleML(Lecture Notes in Computer Science, Vol. 3791). Springer, 160–171.Google Scholar
- Kewen Wang, Zhe Wang, Rodney W. Topor, Jeff Z. Pan, and Grigoris Antoniou. 2014. Eliminating Concepts and Roles from Ontologies in Expressive Descriptive Logics. Computational Intelligence 30, 2 (2014), 205–232.Google ScholarDigital Library
- Zhe Wang, Kewen Wang, Rodney W. Topor, and Jeff Z. Pan. 2010. Forgetting for knowledge bases in DL-Lite. Ann. Math. Artif. Intell. 58, 1-2 (2010), 117–151.Google ScholarDigital Library
- Yan Zhang and Yi Zhou. 2010. Forgetting Revisited. In KR. AAAI Press.Google Scholar
- Yizheng Zhao. 2018. Automated Semantic Forgetting for Expressive Description Logics. Ph.D. Dissertation. The University of Manchester, UK.Google Scholar
- Yizheng Zhao, Ghadah Alghamdi, Renate A. Schmidt, Hao Feng, Giorgos Stoilos, Damir Juric, and Mohammad Khodadadi. 2019. Tracking Logical Difference in Large-Scale Ontologies: A Forgetting-Based Approach. In Proc. AAAI’19. AAAI Press, 3116–3124.Google ScholarDigital Library
- Yizheng Zhao and Renate A. Schmidt. 2015. Concept Forgetting in Math-Ontologies Using An Ackermann Approach. In Proc. ISWC’15(Lecture Notes in Computer Science, Vol. 9366). Springer, 587–602.Google Scholar
- Yizheng Zhao and Renate A. Schmidt. 2016. Forgetting Concept and Role Symbols in Math 371-Ontologies. In Proc. IJCAI’16. IJCAI/AAAI Press, 1345–1352.Google Scholar
- Yizheng Zhao and Renate A. Schmidt. 2017. Role Forgetting for Math 372-Ontologies Using An Ackermann-Based Approach. In Proc. IJCAI’17. IJCAI/AAAI Press, 1354–1361.Google Scholar
- Yizheng Zhao and Renate A. Schmidt. 2018. FAME: An Automated Tool for Semantic Forgetting in Expressive Description Logics. In Proc. IJCAR’18(Lecture Notes in Computer Science, Vol. 10900). Springer, 19–27.Google Scholar
- Yizheng Zhao and Renate A. Schmidt. 2018. On Concept Forgetting in Description Logics with Qualified Number Restrictions. In Proc. IJCAI’18. IJCAI/AAAI Press, 1984–1990.Google Scholar
- Computing Views of OWL Ontologies for the Semantic Web
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