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A User Interface for Semantic Competence Profiles

  • Martin Hochmeister
  • Johannes Daxböck
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6787)

Abstract

Competence management systems are increasingly based on ontologies representing competences within a certain domain. Most of these systems represent a user’s competence profile by means of an ontological structure. Such semantic competence profiles, often structured as a hierarchy of competences, are difficult to navigate for self-assessment purposes. The more competences a user profile holds, the more challenging the comprehensive presentation of profile data is. In this paper, we present an integrated user interface that supports users during competence self-assessment and facilitates a clear presentation of their semantic competence profiles. For evaluation, we conducted a usability study with 19 students at university. The results show that users were mostly satisfied with the usability of the interface that also represents a promising approach for efficient competence self-assessment.

Keywords

User Interface User Profile Semantic Competence Profile Profile Editing Ontology 

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References

  1. 1.
    Bakalov, F., König-Ries, B., Nauerz, A., Welsch, M.: Introspectiveviews: An interface for scrutinizing semantic user models. User Modeling, Adaptation, and Personalization, 219–230 (2010)Google Scholar
  2. 2.
    Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. The Adaptive Web, 3–53 (2007)Google Scholar
  3. 3.
    Bull, S., Kay, J.: Open learner models. Advances in Intelligent Tutoring Systems, 301–322 (2010)Google Scholar
  4. 4.
    Colucci, S., Di Noia, T., Di Sciascio, E., Donini, F., Ragone, A.: Measuring core competencies in a clustered network of knowledge. In: Knowledge Management: Innovation, Technology and Cultures: Proceedings of the 2007 International Conference on Knowledge Management, Vienna, Austria, August 27-28, p. 279. World Scientific Pub. Co. Inc., Singapore (2007)Google Scholar
  5. 5.
    Crowder, R., Wilson, M.L., Fowler, D., Shadbolt, N., Wills, G., Wong, S.: Navigation over a large ontology for industrial web applications. In: International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. DETC2009-86544 (2009), http://eprints.ecs.soton.ac.uk/17918/
  6. 6.
    d’Entremont, T., Storey, M.A.: Using a degree of interest model to facilitate ontology navigation. In: IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2009, pp. 127–131 (2009)Google Scholar
  7. 7.
    Dorn, J., Hochmeister, M.: Techscreen: Mining competencies in social software. In: The 3rd International Conference on Knowledge Generation, Communication and Management, Orlando, FLA, pp. 115–126 (2009)Google Scholar
  8. 8.
    Draganidis, F., Mentzas, G.: Competency based management: a review of systems and approaches. Information Management & Computer Security 14(1), 51–64 (2006)CrossRefGoogle Scholar
  9. 9.
    Ernst, N., Storey, M., Allen, P.: Cognitive support for ontology modeling. International Journal of Human-Computer Studies 62(5), 553–577 (2005)CrossRefGoogle Scholar
  10. 10.
    Few, S.: Information dashboard design: the effective visual communication of data. O’Reilly Media, Inc., Sebastopol (2006)Google Scholar
  11. 11.
    Katifori, A., Halatsis, C., Lepouras, G., Vassilakis, C., Giannopoulou, E.: Ontology visualization methods—a survey. ACM Computing Surveys 39(4), 10 (2007)CrossRefGoogle Scholar
  12. 12.
    Liao, M., Hinkelmann, K., Abecker, A., Sintek, M.: A competence knowledge base system as part of the organizational memory. In: Puppe, F. (ed.) XPS 1999. LNCS (LNAI), vol. 1570, pp. 125–137. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  13. 13.
    Lindgren, R., Henfridsson, O., Schultze, U.: Design principles for competence management systems: a synthesis of an action research study. MIS Quarterly 28(3), 435–472 (2004)Google Scholar
  14. 14.
    Pirolli, P.: Information foraging theory: Adaptive interaction with information. Oxford University Press, USA (2007)CrossRefGoogle Scholar
  15. 15.
    Shneiderman, B.: The eyes have it: A task by data type taxonomy for information visualizations. In: Proceedings of the IEEE Symposium on Visual Languages, 1996, pp. 336–343. IEEE, Los Alamitos (2002)Google Scholar
  16. 16.
    Sieg, A., Mobasher, B., Burke, R.: Web search personalization with ontological user profiles. In: Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, pp. 525–534. ACM, New York (2007)CrossRefGoogle Scholar
  17. 17.
    Storey, M., Musen, M., Silva, J., Best, C., Ernst, N., Fergerson, R., Noy, N.: Jambalaya: Interactive visualization to enhance ontology authoring and knowledge acquisition in protégé. In: Workshop on Interactive Tools for Knowledge Capture (K-CAP 2001), Citeseer (2001)Google Scholar
  18. 18.
    Tarasov, V., Sandkuhl, K., Henoch, B.: Using ontologies for representation of individual and enterprise competence models. In: 2006 International Conference on Research, Innovation and Vision for the Future, Ho Chi Minh City, Vietnam, February 12-16. IEEE Operations Center, Piscataway (2006)Google Scholar
  19. 19.
    Willett, W., Heer, J., Agrawala, M.: Scented widgets: Improving navigation cues with embedded visualizations. IEEE Transactions on Visualization and Computer Graphics, 1129–1136 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Martin Hochmeister
    • 1
  • Johannes Daxböck
    • 1
  1. 1.Electronic Commerce GroupVienna University of TechnologyViennaAustria

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