Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-25T20:52:05.621Z Has data issue: false hasContentIssue false
  • English
  • Français

A literature overview of knowledge sharing between Petri nets and ontologies

Published online by Cambridge University Press:  28 July 2016

Haitao Cheng  and
Zongmin Ma
Haitao Cheng
Affiliation:
College of Computer Science & Engineering, Northeastern University, Shenyang 110819, China e-mail: [email protected]
Zongmin Ma
Affiliation:
College of Computer Science & Engineering, Northeastern University, Shenyang 110819, China e-mail: [email protected] College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Knowledge representation is a subarea of artificial intelligence concerned with using formal symbols to represent a set of facts within a knowledge domain. Two popular knowledge representation languages, namely Petri net and ontology, are promising knowledge sharing and reusing methods in knowledge engineering. The combination of Petri net and ontology can facilitate achieving complementary advantages. Currently, many efforts have been done on knowledge sharing between Petri nets and ontologies. To investigate these issues and more importantly serve as identifying the direction of knowledge sharing between Petri nets and ontologies, in this paper we give a comprehensive literature overview of knowledge sharing between Petri net models and ontology models to satisfy the obvious need. In detail, we discuss the knowledge sharing from two aspects: the different knowledge representation approaches of ontology to represent and reason Petri net and issues of constructing Petri net from ontology. In addition, other important issues on applications and directions for future research are discussed in detail.

Type
Articles
Information
The Knowledge Engineering Review , Volume 31 , Issue 3 , June 2016 , pp. 239 - 260
Copyright
© Cambridge University Press, 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Angele, J., Kifer, M. & Lausen, G. 2009. Ontologies in F-Logic. International Handbooks on Information Systems. Springer, 45–70.CrossRefGoogle Scholar
Araujo, M. & Roque, L. 2009. Modeling games with Petri nets. In Proceedings of the 2009 Digital Games Research Association Conference, London UK, September 2009.Google Scholar
Baader, F. D., Calvanese, D., McGuinness, D. L., Nardi, D. & Patel-Schneider, P. F. 2002. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press.Google Scholar
Behrang, Z. J., Pornpit, W. & Farookh, K. H. 2010. Ontologies based approach in knowledge sharing measurement. Journal of Universal Computer Science 16(6), 956–982.Google Scholar
Berners-Lee, T., Hendler, J. & Lassila, O. 2001. The Semantic Web. Scientific American 284(5), 34–43.Google Scholar
Bezivin, J. 1998. Who’s Afraid of Ontologies?. In OOPSLA’98 Workshop: Model Engineering, Method and Tools Integration with CDIF.Google Scholar
Billington, J., Christensen, S. & vanHee, K. 2003. The Petri nets Markup Language Concepts, Technology, and Tools. In Proceedings of the 24th International Conference on Applications and Theory of Petri nets, 483–505. Springer-Verlag.Google Scholar
Bobillo, F. & Delgado, M. 2007. DeLoean. http://webdiis.unizar.es/~fbobillo/delorean.php.Google Scholar
Borst, W. 1997. Construction of Engineering Ontologies. PhD thesis, Institute for Telematica and Information Technology, University of Twente.Google Scholar
Brachman, R. J. & Levesque, H. J. 2004. Knowledge Representation and Reasoning. Morgan Kaufmann Publishers.Google Scholar
Breton, E. & Bezivin, J. 2001. Towards an understanding of model executability. In Proceedings of the International Conference on Formal Ontologies in Information Systems, 70–80.Google Scholar
Brockmans, S., Ehrig, M., Oberweis, A. & Sduder, R. 2006. Semantic alignment of business processes. In Proceedings of the Eighth International Conference on Enterprise Information System, 191–196.Google Scholar
Brogi, A., Corfini, S. & Iardella, S. 2007. From OWL-S descriptions to Petri nets. In Proceedings of ICSOC 2007 Workshops, 427–438.Google Scholar
Bunge, M. A. 1977. Treatise on Basic Philosophy Volume 3: Ontologies I-the Furniture of the World. Kluwer Academic Publishers.Google Scholar
Cardoso, J. 2007. The semantic web version: where are we? IEEE Intelligent System 22(5), 84–88.CrossRefGoogle Scholar
Chuang, L., Chaudhury, A., Whinston, A. B. & Marinescu, D. C. 1993. Logical inference of Horn clauses in Petri net models. Journal of IEEE Transactions on Knowledge and Data Engineering 5(3), 416–425.Google Scholar
Clark, T., Sammut, P. & Willans, J. 2004. Application Modeling: A Foundation for Language Driven Development. http://albini.xactium.com.Google Scholar
Davis, R., Shrobe, H. & Szolovits, P. 1993. What is a knowledge representation? AI Magazine 14, 17–33.Google Scholar
Dean, M., Schreiber, G., Bechhofer, S., van Harmelen, J., Helena, J. & Horrocks, I. 2004. OWL web ontologies language reference. W3C recommendation. http://www.w3.org/TR/owl-ref.Google Scholar
Deng, Y. & Chang, S. K. 1990. A G-net model for knowledge representation and reasoning. IEEE Transaction on Knowledge and Data Engineering 2(3), 295–310.Google Scholar
Feng, X. N., Wang, Z. & Yin, G. S. 2008. Hierarchical Object-Oriented Petri net modeling method based on ontologies. In Proceedings of 2008 International Conference on Internet Computing in Science and Engineering, 553–556.Google Scholar
Feldmann, C. G. 1998. The Practical Guide to Business Process Reengineering Using IDEF0. Dorset House Publishing.Google Scholar
Gomez-Perez, A., Fernandez-Lopez, M. & Corcho, O. 2003. Ontological Engineering. Advanced Information and Knowledge Processing . Springer-Verlag.Google Scholar
Gasevic, D. & Devedzic, V. 2007. Interoperable Petri net models via ontologies. International Journal of Web Engineering and Technology 3(4), 376–396.Google Scholar
Gasevic, D. & Devedzic, V. 2006. Petri net ontology. Knowledge-Based Systems 19, 220–234.CrossRefGoogle Scholar
Guarino, N. 1998. Formal ontologies and information systems. In Proceedings of Formal Ontologies in Information System, 3–15.Google Scholar
Guarino, N. & Giaretta, P. 1995. Ontologies and knowledge bases: towards a terminological clarification. Towards Very Large Knowledge Bases Knowledge. IOS Press, 25–32.Google Scholar
Guo-Yan, H. 2006. Analysis of artificial intelligence based Petri nets approach to intelligent integration of design. In Proceedings of the International Conference on Machine Learning and Cybernetics, 1691–1695.Google Scholar
Grube, T. R. 1993. A translation approach to portable ontologies. Knowledge Acquisition 5(2), 199–220.CrossRefGoogle Scholar
Hansen, K. M. 2001. Towards a colored Petri nets profile for the unified modeling language – issues, definition, and implementation. Internal Center for Object Technology Report COT/2-52, University of Arhus. http://www.daimi.au.dk/~marius/writings/cpn.pdf.Google Scholar
Hustadt, U., Motik, B. & Sattler, U. 2004. Reducing SHIQ description logic to disjunctive datalog programs. In Proceedings of the 9th International Conference on Knowledge Representation and Reasoning, 152–162.Google Scholar
ISO/IEC 15909-1 2002. Software and systems engineering – high-level Petri nets. Part 1: concepts, definitions and graphical notation, Final Draft of the International Standard ISO/IEC 15909-1. ISO.Google Scholar
ISO/IEC 15909-2 2005. Software and systems engineering – high-level Petri nets. Part 2: transfer format, Working Draft of the International Standard ISO/IEC 15909-2. ISO.Google Scholar
Jozefowska, J. 2010. Knowledge representation for automated reasoning. In Proceedings of KES-AMSTA 2010, 6–11.Google Scholar
Jiang, L. X. & Li, H. W. 2009. An improved fault Petri nets for knowledge representation. In Proceedings of the 2009 International Conference on Computational Intelligence and Software Engineering, 1–4.Google Scholar
Kiefer, M., Lausen, G. & Wu, J. 1995. Logical foundations of object-oriented and frame-based languages. Journal of ACM 42, 741–843.Google Scholar
Kogut, P., Cranefield, S. & Hart, L. 2002. UML for ontologies development. The Knowledge Engineering Review 17(1), 61–64.CrossRefGoogle Scholar
Koschmider, A. & Oberweis, A. 2005. Ontologies based business process description. In Proceedings of the Open Interop Workshop on Enterprise Modeling and Ontologies for Interoperability.Google Scholar
Kowalski, R. & Burton, A. 2011. WUENIC – a case study in rule-based knowledge representation and reasoning. In JSAI-isAI Workshop, 112–125.Google Scholar
Kummer, O., Wienberg, F. & Duvigneau, M. 2003. Renew – the reference net workshop. http://renew.de/.Google Scholar
Lam, S. W. & Srihari, S. N. 1991. Frame-based knowledge representation for multi-domain document layout analysis. In Proceedings of the 1991 International Conference on Systems, Man, and Cybernetics. ‘Decision Aiding for Complex Systems’ 1 (3), 1859–1864.Google Scholar
Li, X. & Lara-Rosano, F. 2000. Adaptive fuzzy Petri nets for dynamic knowledge representation and inference. Expert Systems With Applications 19, 235–241.Google Scholar
Li, S. & Wang, S. Q. 2009. Geometry knowledge acquisition and representation on ontologies. In Proceedings of the 2009 International Conference on Computational Intelligence and Software Engineering, 1–4.Google Scholar
Liu, L. W. 1994. High-level Petri net model of logic program with negation. IEEE Trans on Knowledge and Data Engineering 6(3), 382–395.Google Scholar
Liu, W. Y. 2006. Using IDEF0/Petri nets for ontologies-based task knowledge analysis: the case of emergency response for debris-flow. Proceeding of the 39th Hawaii International Conference on System Sciences 4, 76c.Google Scholar
Lovrek, I. 1995. Petri nets based knowledge representation for intelligent networks. In Proceedings of the 1995 IEEE International Symposium on Intelligent Control, 602–607.Google Scholar
Lu, S. F., Sun, C. F. & Ma, X. J. 2007. Using e-connection and description logic for formalizing and analyzing high-level Petri nets. In Proceedings of the 9th International Symposium on Symbolic and Numeri Algorithms for Scientific Computing, 514–517.Google Scholar
Ma, B. X. & Xu, Y. L. 2009a. Integrating PNML with OWL for Petri nets. In Proceedings of the 2nd IEEE International Conference on Computer Science and Information Technology, 228–230.Google Scholar
Ma, B. X. & Xu, Y. L. 2009b. Constructing Petri net model for dynamic description logic actions. Proceedings of the 1st International Workshop on Education Technology and Computer Science 3, 753–756.Google Scholar
Martin, D. 2004. OWL-S: Semantic Markup for Web Service. World Wide Web Consortium (W3C). http://www.w3.org/Submission/OWL-S/.Google Scholar
Moldt, D. & Ortmann, J. 2004. DaGen: a tool for automatic translation from DAML-S to high-level Petri nets. In Proceedings of the 7th International Conference of FASE 2004, 209–213.Google Scholar
Murata, T. 1989. Petri nets: properties, analysis and applications. Proceedings of the IEEE 77, 541–580.Google Scholar
Murata, T. & Zhang, D. 1988. A prediate-transition net model for parallel interpretation of logic program. IEEE Transcations Software Engineer 14, 481–497.Google Scholar
Narayanan, S. & McIlraith, S. 2002. Simulation, verification and automated composition of web service. In Proceedings of WWW’02. ACM, 77–88.Google Scholar
Neches, R., Fikes, R. E. & Finin, T. 1991. Enabling technology for knowledge sharing. AI Magazine 12(3), 36–56.Google Scholar
Nielsen, M. & Sassone, V. 1988. Petri nets and other models of concurrency. In Lectures on Petri nets I: Basic Models, Lecture Notes in Computer Science, 4546, 587–642. Springer.CrossRefGoogle Scholar
O’Leary, D. E. 2007. Knowledge representation of rules: a note. Intelligent System in Accounting Finance and Management 15, 73–84.Google Scholar
Perez, A. G. & Benjamins, V. R. 1999. Overview of knowledge sharing and reuse components: ontologies and problem-solving methods. In Proceedings of the IJCAI-99 Workshop on Ontologies and Problem-Solving Methods.Google Scholar
Peterka, G. & Murata, T. 1989. Proof procedure and answer extraction in Petri net model of logic programs. IEEE Transactions on Software Engineering 15(2), 209–217.Google Scholar
Petri, C. A. 1962. Fundamentals of a theory of asynchronous information flow. In IFIP Congress 62: Information Processing, Popplewell, C. M. (ed.), North-Holland, 386–390.Google Scholar
Puppe, F. 1998. Knowledge reuse among diagnostic problem-solving methods in the shell-kit D3. International Journal of Human-Computer Studies 49(4), 627–649.CrossRefGoogle Scholar
Ranasinghe, R. A. C. & Madurapperuma, A. P. 2003. Enhanced frame-based knowledge representation for an intelligent environment. In Proceedings of International Conference on Integration of Knowledge Intensive Multi-Agent Systems: Modeling, Exploration, and Engineering, 25–30.Google Scholar
Recker, J. & Indulska, M. 2007. An ontology-based evaluation of process modeling with Petri nets. Journal of Interoperability in Business Information System 2, 45–64.Google Scholar
Ribaric, S. & Hrkac, T. 2007. A knowledge representation and reasoning based on Petri nets with spatio-temporal tokens. In Proceedings of International Conference on Computer as a Tool, 793–800.Google Scholar
Ribaric, S. & Hrkac, T. 2012. A fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets. Information Systems 37, 238–256.CrossRefGoogle Scholar
Shanks, G., Tansley, E. & Weber, R. 2003. Using ontologies to validate conceptual models. Communications of ACM 46(10), 85–89.Google Scholar
Soffer, P., Kaner, M. & Wand, Y. 2008. Assigning ontologies-based semantics to process models: the case of Petri nets. In Proceedings of the 20th International Conference on Advanced Information Systems Engineering, Lecture Notes in Computer Science 5074, 16–31.Google Scholar
Staab, S. & Studer, R. 2004. Handbook on Ontologies. International Handbooks on Information Systems. Springer.Google Scholar
Studer, R., Benjamins, V. R. & Fensel, D. 1998. Knowledge and engineering: principles and methods. Data and Knowledge Engineering 25, 161–197.Google Scholar
Strbac, P. 2002. An Approach to Modeling Communication Protocol by Using Upgraded Petri Nets. PhD dissertation, Military Academy.Google Scholar
Shen, V. R. L. 2006. Knowledge representation using high-level fuzzy Petri nets. IEEE Transactions on Systems, Man, and Cybernetics – Part A 36(6), 1220–1227.Google Scholar
Shi, Z. Z., Dong, M. K., Jiang, Y. C. & Zhang, H. J. 2005. A logical foundation for the semantic web. Science in China Series F-Information Sciences 48(2), 161–178.CrossRefGoogle Scholar
Takai-Igarashi, T. 2005. Ontologies based standardization of Petri net modeling for signaling pathways. Silico Biology 5, 0047.Google ScholarPubMed
Tan, X. 2010. SCOPE: a Situation Calculus Ontologies of Petri nets. In Proceedings of the Sixth International Conference on Formal Ontologies in Information Systems, 227–240.Google Scholar
Thomas, P., Yessad, A. & Labat, J. M. 2011. Petri nets and ontologies: tools for the ‘learning player’ assessment in serious games. In Proceedings of the 11th IEEE International Conference on Advanced Learning Technologies, 415–419.Google Scholar
Vidal, J. C., Lama, M. & Bugarin, A. 2006. A high-level Petri net ontology compatible with PNML. Petri Nets Newsletter 71, 11–23.Google Scholar
Vidal, J. C., Lama, M. & Bugarin, A. 2007. Petri nets semantics for OWL-S service choreography. In Proceedings of the International Workshop on Formal Aspects of Business Processes and Web Service, 7–20.Google Scholar
Vidal, J. C. & Lama, M. 2009. OPENET LD: an ontology-based Petri nets engine to execute IMS LD units of learning. In Proceedings of the Ninth IEEE International Conference on Advanced Learning Technologies, 499–503.Google Scholar
Vidal, J. C., Lama, M. & Bugarin, A. 2010. OPENET: ontologies-based engine for high-level Petri nets. International Journal on Expert Systems with Applications 1(37), 6493–6509.Google Scholar
Wang, X. L. & Wu, X. L. 2012. A novel knowledge representation method based on ontologies for natural disaster decision-making. In Proceedings of the 2012 IEEE International Conference on Computer Science and Automation Engineering, 241–245.Google Scholar
Wang, Y. & Weber, R. 1993. On the ontological expressiveness of information systems analysis and design grammars. Journal of Information Systems 3(4), 217–237.Google Scholar
Wang, Y., Bai, X., Li, J. & Huang, R. 2007. Ontologies-based test case generation for testing web services. In Proceedings of the Eighth International Symposium on Autonomous Decentralized Systems, 43–50.Google Scholar
Weber, M. & Kindler, E. 2003. The Petri nets markup language. In Advances in Petri nets. Petri nets technology for communication based systems. Lecture Notes in Computer Science 2472, 124–144. Springer-Verlag.Google Scholar
Yang, G., Kifer, M. & Zhao, C. 2003. FLORA-2: a rule-based knowledge representation and inference infrastructure for the semantic web. In On the Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE, Lecture Notes in Computer Science 2888, 671–688. Springer.Google Scholar
Yang, X. P. & Zhou, X. B. 2009. Ontologies-oriented Petri net model of semantics service composition. In Proceedings of the 2nd International Workshop on Knowledge Discovery and Data Mining, 932–936.Google Scholar
Yen, H. C. 2006. Introduction to Petri nets theory. Recent Advances in Formal Languages and Applications 25, 343–373.Google Scholar
Yi, X. & Kochut, K. J. 2004. A CP-nets-based design and verification framework for web services composition. In Proceedings of the IEEE International Conference on Web Services, 756–760.Google Scholar
Yim, J., Joo, J. & Lee, G. 2011. Petri nets representation of ontologies for indoor location-based services. GDC 2011, CCIS 261, 423–430. Springer-Verlag.Google Scholar
Yu, S. K., Hsu, W. & Pung, H. K. 1998. KPN: a Petri net model for general knowledge representation and reasoning. In Proceedings of 1998 IEEE International Conference on Systems, Man, and Cybernetics, 184–189.Google Scholar
Zhang, F., Ma, Z. M. & Ribaric, S. 2011. Representation of Petri nets with OWL DL ontologies. In Proceedings of the 8th International Conference on Fuzzy Systems and Knowledge Discovery 3, 1396–1400.Google Scholar
Zhang, F., Ma, Z. M. & Yan, L. 2012. A fuzzy ontologies approach for representing fuzzy Petri nets. In Proceedings of WCCI 2012 IEEE International Conference on Computational Intelligence, 10–15.Google Scholar
Zhang, G., Meng, F., Jiang, C. & Pang, J. 2006. Using Petri nets to reason with rule and owl. In Proceeding of the 6th IEEE International Conference on Computer and Information Technology.CrossRefGoogle Scholar
Zhang, X., Chen, X. Y., Guo, S. Y. & Zhan, Z. Q. 2010. Ontologies-based ITSM knowledge representation research. In Proceedings of the 2010 International Conference on Advanced Intelligence and Awareness Internet, 230–235.Google Scholar