Linking Knowledge for Simulation Learning

  • Irene Celino
  • Daniele Dell’Aglio
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7117)

Abstract

Simulation Learning is a frequent practice to conduct near-real, immersive and engaging training sessions. AI Planning and Scheduling systems are used to automatically create and supervise learning sessions; to this end, they need to manage a large amount of knowledge about the simulated situation, the learning objectives, the participants’ behaviour, etc.

In this paper, we explain how Linked Data and Semantic Web technologies can help the creation and management of knowledge bases for Simulation Learning. We also present our experience in building such a knowledge base in the context of Crisis Management Training.

Keywords

Linked Data Simulation Learning Planning Provenance Semantic Web 

References

  1. 1.
    Aldrich, C.: Simulations and the Future of Learning: An Innovative (and Perhaps Revolutionary) Approach to e-Learning, Pfeiffer (September 2003)Google Scholar
  2. 2.
    Berners-Lee, T.: Linked Data – W3C Design Issues, Architectural and philosophical points (2006), http://www.w3.org/DesignIssues/LinkedData.html
  3. 3.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked Data – The Story So Far. International Journal on Semantic Web and Information Systems 5, 1–22 (2009)Google Scholar
  4. 4.
    Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: Dbpedia – a crystallization point for the web of data. Journal of Web Semantics: Science, Services and Agents on the World Wide Web 7, 154–165 (2009)CrossRefGoogle Scholar
  5. 5.
    Brase, J., Nejdl, W.: Ontologies and Metadata for eLearning. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies International Handbooks on Information Systems, pp. 555–574. Springer, Heidelberg (2004)Google Scholar
  6. 6.
    Caird-Daley, A., Harris, D., Bessell, K., Lowe, M.: Training Decision Making using Serious Games. Tech. rep. Human Factors Integration Defence Technology Centre (2007)Google Scholar
  7. 7.
    Carroll, J.J., Bizer, C., Hayes, P., Stickler, P.: Named graphs, provenance and trust. In: WWW 2005: Proceedings of the 14th International Conference on World Wide Web, pp. 613–622. ACM (2005)Google Scholar
  8. 8.
    Celino, I., Dell’Aglio, D., De Benedictis, R., Grilli, S., Cesta, A.: Ontologies, rules and linked data to support Crisis Managers Training. IEEE Learning Technology Newsletter, Special Issue Semantic Web Technologies for Technology Enhanced Learning 13(1) (2011)Google Scholar
  9. 9.
    Cesta, A., Cortellessa, G., Fratini, S., Oddi, A.: Developing an End-to-End Planning Application from a Timeline Representation Framework. In: 21st Applications of Artificial Intelligence Conference (2009)Google Scholar
  10. 10.
    Cesta, A., Fratini, S.: The Timeline Representation Framework as a Planning and Scheduling Software Development Environment. In: 27th Workshop of the UK Planning and Scheduling SIG (2008)Google Scholar
  11. 11.
    Gerevini, A., Long, D.: Plan Constraints and Preferences in PDDL3. Tech. rep. R.T. 2005-08-47, Dipartimento di Elettronica per l’Automazione, Università degli Studi di Brescia (2005)Google Scholar
  12. 12.
    Gil, Y., Blythe, J.: Planet: A sharable and reusable ontology for representing plans. In: The AAAI - Workshop on Representational Issues for Real-World Planning Systems, pp. 28–33 (2000)Google Scholar
  13. 13.
    Harris, S., Seaborne, A.: SPARQL 1.1 Query Language. W3C Working Draft (2011), http://www.w3.org/TR/sparql11-query/
  14. 14.
    Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space. In: Synthesis Lectures on the Semantic Web: Theory and Technology, 1st edn., vol. 1. Morgan & Claypool (2011)Google Scholar
  15. 15.
    Hodgins, W., Duval, E.: Draft standard for learning technology - Learning Object Metadata. Tech. rep., Learning Technology Standards Committee of the IEEE. IEEE Standards Department, New York (July 2002)Google Scholar
  16. 16.
    Knublauch, H.: SPIN Modeling Vocabulary (October 20, 2009), http://spinrdf.org/spin.html
  17. 17.
    Lehto, M., Nah, F.: Decision-making Models and Decision Support. In: Handbook of Human Factors and Ergonomics, John Wiley & Sons, Inc., NY (2006)Google Scholar
  18. 18.
    Moreau, L., Clifford, B., Freire, J., Futrelle, J., Gil, Y., Groth, P., Kwasnikowska, N., Miles, S., Missier, P., Myers, J., Plale, B., Simmhan, Y., Stephan, E., den Bussche, J.V.: The Open Provenance Model core specification (v1.1). Future Generation Computer Systems (2010)Google Scholar
  19. 19.
    Rajpathak, D., Motta, E.: An ontological formalization of the planning task. In: International Conference on Formal Ontology in Information Systems (FOIS 2004), pp. 305–316 (2004)Google Scholar
  20. 20.
    Sniezek, J., Wilkins, D., Wadlington, P., Baumann, M.: Training for Crisis Decision-Making: Psychological Issues and Computer-Based Solutions. Journal of Management Information Systems 18(4), 147–168 (2002)CrossRefGoogle Scholar
  21. 21.
    Steinmetz, R., Seeberg, C.: Meta-information for Multimedia eLearning. In: Computer Science in Perspective, pp. 293–303 (2003)Google Scholar
  22. 22.
    Stern, E., Sundelius, B.: Crisis Management Europe: An Integrated Regional Research and Training Program. International Studies Perspective 3(1), 71–88 (2002)CrossRefGoogle Scholar
  23. 23.
    Stojanovic, L., Staab, S., Studer, R.: eLearning based on the Semantic Web. In: WebNet 2001 - World Conference on the WWW and Internet, pp. 23–27 (2001)Google Scholar
  24. 24.
    Tiropanis, T., Davis, H.C., Millard, D.E., Weal, M.J.: Semantic Technologies for Learning and Teaching in the Web 2.0 Era. IEEE Intelligent Systems 24(6), 49–53 (2009)CrossRefGoogle Scholar
  25. 25.
    Zhao, J.: Open Provenance Model Vocabulary Specification (October 2010), http://purl.org/net/opmv/ns

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Irene Celino
    • 1
  • Daniele Dell’Aglio
    • 1
  1. 1.CEFRIEL – ICT InstitutePolitecnico of MilanoMilanoItaly

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