A Temporal QoS Ontology for ERTMS/ETCS

Authors: Marc Sango, Olimpia Hoinaru, Christophe Gransart, Laurence Duchien

Abstract:

Ontologies offer a means for representing and sharing information in many domains, particularly in complex domains. For example, it can be used for representing and sharing information of System Requirement Specification (SRS) of complex systems like the SRS of ERTMS/ETCS written in natural language. Since this system is a real-time and critical system, generic ontologies, such as OWL and generic ERTMS ontologies provide minimal support for modeling temporal information omnipresent in these SRS documents. To support the modeling of temporal information, one of the challenges is to enable representation of dynamic features evolving in time within a generic ontology with a minimal redesign of it. The separation of temporal information from other information can help to predict system runtime operation and to properly design and implement them. In addition, it is helpful to provide a reasoning and querying techniques to reason and query temporal information represented in the ontology in order to detect potential temporal inconsistencies. To address this challenge, we propose a lightweight 3-layer temporal Quality of Service (QoS) ontology for representing, reasoning and querying over temporal and non-temporal information in a complex domain ontology. Representing QoS entities in separated layers can clarify the distinction between the non QoS entities and the QoS entities in an ontology. The upper generic layer of the proposed ontology provides an intuitive knowledge of domain components, specially ERTMS/ETCS components. The separation of the intermediate QoS layer from the lower QoS layer allows us to focus on specific QoS Characteristics, such as temporal or integrity characteristics. In this paper, we focus on temporal information that can be used to predict system runtime operation. To evaluate our approach, an example of the proposed domain ontology for handover operation, as well as a reasoning rule over temporal relations in this domain-specific ontology, are presented.

Keywords: System Requirement Specification, ERTMS/ETCS, Temporal Ontologies, Domain Ontologies.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1337815

References:

[1] M. Feld and C. M¨uller, “The automotive ontology: Managing knowledge inside the vehicle and sharing it between cars,” in Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications, ser. AutomotiveUI ’11, 2011, pp. 79–86.
[2] S. Farfeleder, T. Moser, A. Krall, T. Stlhane, H. Zojer, and C. Panis, “Dodt: Increasing requirements formalism using domain ontologies for improved embedded systems development,” in Design and Diagnostics of Electronic Circuits Systems, April 2011, pp. 271–274.
[3] OBO, “The open biological and biomedical ontologies,” http://www. obofoundry.org/.
[4] S. Verstichel, F. Ongenae, L. Loeve, F. Vermeulen, P. Dings, B. Dhoedt, T. Dhaene, and F. D. Turck, “Efficient data integration in the railway domain through an ontology-based methodology,” Transport. Research Part C: Emerging Technologies, vol. 19, no. 4, pp. 617 – 643, 2011.
[5] G. Bonifacio, P. Marmo, A. Orazzo, I. Petrone, L. Velardi, and A. Venticinque, “Improvement of processes and methods in testing activities for safety-critical embedded systems,” in Computer Safety, Reliability, and Security, 2011, vol. 6894, pp. 369–382.
[6] O. Hoinaru, C. Gransart, G. Mariano, and E. Lemaire, “An ontology for the ERTMS/ETCS,” in Transport Research Arena, Paris, 2014, p. 10p.
[7] ERTMS/ETCS, http://www.era.europa.eu/Document-Register/Pages/ SystemRequirementsSpecification(Recommendation).aspx.
[8] M. Sango, C. Gransart, and L. Duchien, “Safety component-based approach and its application to ERTMS/ETCS on-board train control system,” in Transport Research Arena, Paris, Apr. 2014, p. 10.
[9] J. L. Bresina and P. H. Morris, “Explanations and recommendations for temporal inconsistencies,” Proc. Int. Work. on Planning and Scheduling for Space, 2006.
[10] D. L. McGuinness and F. van Harmelen, “The semantic web activity.”
[11] W3C, “Owl web ontology language overview - w3c recommendation.”
[12] F. Baader, D. Calvanese, D. L. McGuinness, D. Nardi, and P. F. Patel-Schneider, Eds., The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, 2003.
[13] G. Antoniou and F. v. Harmelen, A Semantic Web Primer, 2Nd Edition (Cooperative Information Systems), 2nd ed. The MIT Press, 2008.
[14] JESS, http://www.jessrules.com/.
[15] KAON2, http://kaon2.semanticweb.org.
[16] E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur, and Y. Katz, “Pellet: A practical owl-dl reasoner,” Web Semant., vol. 5, no. 2, pp. 51–53, Jun. 2007.
[17] SWRL, “Swrl: A semantic web rule language combining owl and ruleml - w3c member submission 21 may 2004.”
[18] M. J. O’Connor and A. K. Das, “Sqwrl: A query language for owl.” in OWLED, ser. CEUR Workshop Proceedings, R. Hoekstra and P. F. Patel-Schneider, Eds., vol. 529, 2008.
[19] W3C, “Time ontology in owl - w3c working draft 27 september 2006.”
[20] OWL-S, “Daml services,” http://www.daml.org/services/owl-s/.
[21] J. F. Allen, “Maintaining knowledge about temporal intervals,” Commun. ACM, vol. 26, no. 11, pp. 832–843, Nov. 1983.
[22] S.-K. Kim, M.-Y. Song, C. Kim, S.-J. Yea, H. C. Jang, and K.-C. Lee, “Temporal ontology language for representing and reasoning interval-based temporal knowledge,” in Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web, 2008, pp. 31–45.
[23] C. Welty and R. Fikes, “A reusable ontology for fluents in owl,” in Proceedings of the 2006 Conference on Formal Ontology in Information Systems. IOS Press, 2006, pp. 226–236.
[24] H.-U. Krieger, “Where temporal description logics fail: Representing temporally-changing relationships,” in KI 2008: Advances in Artificial Intelligence, ser. Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2008, vol. 5243, pp. 249–257.
[25] V. Milea, F. Frasincar, and U. Kaymak, “towl: A temporal web ontology language,” IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 42, no. 1, pp. 268–281, 2012.
[26] S. Batsakis, K. Stravoskoufos, and E. G. M. Petrakis, “Temporal reasoning for supporting temporal queries in OWL 2.0,” in Knowledge-Based and Intelligent Information and Engineering Systems, 2011, pp. 558–567.
[27] C. Lutz, “Description logics with concrete domains-a survey,” in Fourth conference onAdvances in Modal logic, 2002, pp. 265–296.
[28] F. Weichert, C. Mertens, L. Walczak, G. Kern-Isberner, and M. Wagner, “A novel approach for connecting temporal-ontologies with blood flow simulations.” Journal of Biomedical Informatics, vol. 46, no. 3, pp. 470–479, 2013.
[29] P. Grenon, B. Smith, and L. Goldberg, “Biodynamic ontology: Applying bfo in the biomedical domain,” in Stud. Health Technol. Inform. IOS Press, 2004, pp. 20–38.
[30] B. Smith, W. Ceusters, B. Klagges, J. Khler, A. Kumar, J. Lomax, C. Mungall, F. Neuhaus, A. Rector, and C. Rosse, “Relations in biomedical ontologies,” Genome Biology, vol. 6, no. 5, 2005.
[31] M. OConnor and A. Das, “A method for representing and querying temporal information in owl,” in Biomedical Engineering Systems and Technologies, ser. Communications in Computer and Information Science, A. Fred, J. Filipe, and H. Gamboa, Eds. Springer Berlin Heidelberg, 2011, vol. 127, pp. 97–110.
[32] W3C, “Defining n-ary relations on the semantic web - w3c working group note 12 april 2006.”
[33] O. Hoinaru, G. Mariano, and C. Gransart, “Ontology for complex railway systems application to ERTMS/ETCS system,” in FM-RAIL-BOK Workshop in SEFM2013 11th International Conference on Software Engineering and Formal Methods, Espagne, Jan. 2013, p. 6p.
[34] ITU-T, X.641: Information Technology - Quality of Service Frameworks.
[35] E. Exposito, “Methodology, models and paradigms for a next generation transport layer design,” Ph.D. dissertation, INPT - France, 2010.
[36] F. Singhoff, A. Plantec, P. Dissaux, and J. Legrand, “Investigating the usability of real-time scheduling theory with the cheddar project,” Real-Time Syst., vol. 43, no. 3, pp. 259–295, Nov. 2009.
[37] M. Fisher, D. Gabbay, and L. Vila, Handbook of Temporal Reasoning in Artificial Intelligence (Foundations of Artificial Intelligence (Elsevier)). New York, NY, USA: Elsevier Science Inc., 2005.
[38] M. Sango, L. Duchien, and C. Gransart, “Component-Based Modeling and Observer-Based Verification for Railway Safety-Critical Applications,” in The 11th International Symp. on FACS, Italie, Sep. 2014, p. 18.
[39] L. Khoudour, M. Ghazel, F. Boukour, M. Heddebaut, and E.-M. El-Koursi, “Towards safer level crossings: existing recommendations, new applicable technologies and a proposed simulation model,” European Transport Research Review, vol. 1, no. 1, pp. 35–45, 2009.