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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:68706", author = "Marc Sango and Olimpia Hoinaru and Christophe Gransart and Laurence Duchien", title = "A Temporal QoS Ontology for ERTMS/ETCS", 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.", volume = "9", number = "1", pages = "95-7", }
