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Ontologies of engineering knowledge: general structure and the case of Software Engineering

Published online by Cambridge University Press:  01 September 2009

Miguel-Angel Sicilia ,
Elena García-Barriocanal ,
Salvador Sánchez-Alonso  and
Daniel Rodríguez-García
Miguel-Angel Sicilia
Affiliation:
Computer Science Department, University of Alcalá, Carretera Madrid-Barcelona, km. 33.6, 28871 Alcalá de Henares, Madrid, Spain; e-mails: [email protected], [email protected], [email protected], [email protected]
Elena García-Barriocanal
Affiliation:
Computer Science Department, University of Alcalá, Carretera Madrid-Barcelona, km. 33.6, 28871 Alcalá de Henares, Madrid, Spain; e-mails: [email protected], [email protected], [email protected], [email protected]
Salvador Sánchez-Alonso
Affiliation:
Computer Science Department, University of Alcalá, Carretera Madrid-Barcelona, km. 33.6, 28871 Alcalá de Henares, Madrid, Spain; e-mails: [email protected], [email protected], [email protected], [email protected]
Daniel Rodríguez-García
Affiliation:
Computer Science Department, University of Alcalá, Carretera Madrid-Barcelona, km. 33.6, 28871 Alcalá de Henares, Madrid, Spain; e-mails: [email protected], [email protected], [email protected], [email protected]
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Abstract

Engineering knowledge is a specific kind of knowledge that is oriented to the production of particular classes of artifacts, is typically related to disciplined design methods, and takes place in tool-intensive contexts. As a consequence, representing engineering knowledge requires the elaboration of complex models that combine functional and structural representations of the resulting artifacts with process and methodological knowledge. The different categories used in the engineering domain vary in their status and in the way they should be manipulated when building applications that support engineering processes. These categories include artifacts, activities, methods and models. This paper surveys existing models of engineering knowledge and discusses an upper ontology that abstracts the categories that crosscut different engineering domains. Such an upper model can be reused for particular engineering disciplines. The process of creating such elaborations is reported on the particular case study of Software Engineering as a concrete application example.

Type
Original Article
Information
The Knowledge Engineering Review , Volume 24 , Special Issue 3: Software and system engineering – part 2 , September 2009 , pp. 309 - 326
Copyright
Copyright © Cambridge University Press 2009

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References

Abels, S., Ahlemann, F., Hahn, A., Hausmann, K., Strickmann, J. 2006. PROMONT—A project management ontology as a reference for virtual project organizations. OTM Workshops, Lecture Notes in Computer Science, 4277, 813–823. Springer.CrossRefGoogle Scholar
Abran, A., Cuadrado-Gallego, J. J., García-Barriocanal, E., Mendes, O., Sánchez-Alonso, S., Sicilia, M. A. 2006. Engineering the ontology for the SWEBOK: issues and techniques. In Ontologies for Software Engineering and Software Technology, Calero, C., Ruiz, F. & Piattini, M. (eds), Springer, 103–122.CrossRefGoogle Scholar
Ahmed, S., Kim, S., Wallace, K. M. 2007. A methodology for creating ontologies for engineering design. Journal of Computing and Information Science in Engineering 7(2), 132–140.CrossRefGoogle Scholar
Auyang, S. 2004. Engineering—An Endless Frontier. Harvard University Press.CrossRefGoogle Scholar
Batres, R., West, M., Leal, D., Price, D., Masaki, K., Shimada, Y., Fuchino, T., Naka, Y. 2007. An upper ontology based on ISO 15926. Computers & Chemical Engineering 31(5–6), 519–534.CrossRefGoogle Scholar
Bittner, K., Spence, I. 2002. Use Case Modeling. Addison Wesley Professional.Google Scholar
Blomqvist, E., Ohgren, A. 2008. Constructing an enterprise ontology for an automotive supplier. Engineering Applications of Artificial Intelligence 21(3), 386–397.CrossRefGoogle Scholar
Brooks, F. 1987. No silver bullet: essence and accidents of software engineering. IEEE Computer 20(4), 10–19.CrossRefGoogle Scholar
Colburn, T. 2000. Philosophy and Computer Science. M.E. Sharpe.Google Scholar
Colombo, G., Mosca, A., Sartori, F. 2007. Towards the design of intelligent CAD systems: an ontological approach. Advanced Engineering Informatics 21(2), 153–168.CrossRefGoogle Scholar
Coral, C., Ruiz, F., Piatinni, M. 2006. Ontologies for Software Engineering and Software Technology. Springer-Verlag.Google Scholar
Darlington, M. J., Culley, S. J. 2008. Investigating ontology development for engineering design support. Advanced Engineering Informatics 22(1), 112–134.CrossRefGoogle Scholar
Dias, W. P. S. 2007. Philosophical grounding and computational formalization for practice based engineering knowledge. Knowledge-Based Systems 20(4), 382–387.CrossRefGoogle Scholar
Fenton, N. 1991. Software Metrics: A Rigorous Approach. Chapman & Hall.Google Scholar
Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., Schneider, L. 2002. Sweetening ontologies with DOLCE. In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management: Ontologies and the Semantic Web, 166–181.Google Scholar
Gruber, T., Olsen, G. 1994. An ontology for engineering mathematics. In Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, Gustav Stresemann Institut, Bonn, Germany, Doyle, J., Sandewall, E. & Torasso, P. (eds). Morgan Kaufmann, 258–269.Google Scholar
Gruninger, M., Fox, M. S. 1995. Methodology for the design and evaluation of ontologies. In Proceedings of the Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI-95, Montreal.Google Scholar
Hargadon, A. B. 2002. Brokering knowledge: linking learning and innovation. Research in Organizational Behaviour, volume 24. Elsevier, 41–85.CrossRefGoogle Scholar
Hoekstra, R., Breuker, J., Di Bello, M., Boer, A. 2007. The LKIF Core ontology of basic legal concepts. In Proceedings of the Workshop on Legal Ontologies and Artificial Intelligence Techniques (LOAIT’07), Casanovas, P., Biasiotti, M. A., Francesconi, E. & Sagri, M. T. (eds). http://www.ittig.cnr.it/loait/LOAIT07-Proceedings.pdfGoogle Scholar
Katranuschkov, P., Gehre, A., Scherer, R. J. 2002. An engineering ontology framework as advanced user gateway to IFC model data. In Proceedings of ECPPM 2002—eWork and eBusiness in Architecture, Engineering and Construction, Turk Z. & Scherer R. J. (eds). A.A. Balkema, 269–276.Google Scholar
Kim, H., Sengupta, A., Fox, M., Dalkilic, M. 2005. A measurement ontology generalizable for emerging domain. Journal of Database Management 18(1), 20–42.CrossRefGoogle Scholar
Lenat, D. 1995. Cyc: a large-scale investment in knowledge infrastructure. Communications of the ACM 38(11), 33–38.CrossRefGoogle Scholar
Lin, K., Harding, J. A. 2007. A manufacturing system engineering ontology model on the semantic web for inter-enterprise collaboration. Computers in Industry 58(5), 428–437.CrossRefGoogle Scholar
Lin, J., Fox, M., Bilgic, T. 1996. A requirement ontology for engineering design. Concurrent Engineering: Research and Applications 4(4), 279–291.Google Scholar
Monceaux, A., Naeve, A., Sicilia, M. A., García-Barriocanal, E., Arroyo, S., Guss, J. 2007. Targeting learning resources in competency-based organizations. In The Semantic Web: Real-World Applications from Industry, Cardoso, J., Hepp, M. & Lytras, M. (eds). Springer, 143–167.Google Scholar
Niles, I., Pease, A. 2001. Towards a Standard Upper Ontology. In Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001), Welty, C. & Smith, B. (eds), Ogunquit, Maine, October 17–19.Google Scholar
Parnas, D. L. 1998. Software engineering programmes are not computer science programmes. Annals of Software Engineering 6, 19–37.CrossRefGoogle Scholar
Peachavanish, R., Karimi, H. A., Akinci, B., Boukamp, F. 2006. An ontological engineering approach for integrating CAD and GIS in support of infrastructure management. Advanced Engineering Informatics 20(1), 71–88.Google Scholar
Polanyi, M. 1966. The Tacit Dimension. Doubleday.Google Scholar
Quine, W. V. 1948. On what there is. Review of Metaphysics 2, 21–38.Google Scholar
Schmidt, D. C. 2006. Model-driven engineering. IEEE Computer 39(2), 25–31.CrossRefGoogle Scholar
Sicilia, M. A., Lytras, M. 2005. The semantic learning organization. The Learning Organization 12(5), 402–410.CrossRefGoogle Scholar
Sicilia, M. A., Lytras, M., Rodríguez, E., García-Barriocanal, E. 2006. Integrating descriptions of knowledge management learning activities into large ontological structures: a case study. Data and Knowledge Engineering 57(2), 111–121.CrossRefGoogle Scholar
Sowa, J. 2000. Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks/Cole.Google Scholar
Stahovich, T. F., Davis, R., Shrobe, H. 1993. An ontology for mechanical devices. In Proceedings of the AAAI-93 Workshop on Reasoning About Function, Washington, DC, 137–140.Google Scholar
Top, J., Akkermans, H. 1994. Tasks and ontologies in engineering modeling. International Journal of Human–Computer Studies 41(4), 585–617.CrossRefGoogle Scholar
Vincenti, W. G. 1993. What Engineers Know and How They Know It: Analytical Studies from Aeronautical History. Johns Hopkins University Press.CrossRefGoogle Scholar
Welty, C., Guarino, N. 2001. Supporting ontological analysis of taxonomic relationships. Data and Knowledge Engineering 39(1), 51–74.CrossRefGoogle Scholar
Yoshioka, M., Umeda, Y., Takeda, H., Shimomura, Y., Nomaguchi, Y., Tomiyama, T. 2004. Physical concept ontology for the knowledge intensive engineering framework. Advanced Engineering Informatics 18(2), 95–113.CrossRefGoogle Scholar