Pragmatic Aspects of Collaborative Problem Solving: Towards a Framework for Conceptualizing Dynamic Knowledge

  • Rodrigo Bonacin
  • Heiko Hornung
  • Julio Cesar Dos Reis
  • Roberto Pereira
  • M. Cecília C. Baranauskas
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 141)

Abstract

Knowledge production in the Social Web can be understood as a dynamic socio-cultural process. Mechanisms that support users to explore this knowledge in an effective and efficient way may bring various benefits. However, the construction of these interaction mechanisms depends on further research on multidisciplinary fields. The interpretation of the content by users is influenced by meanings and intentions, as well as by the understanding of the evolution of these aspects over time. This paper analyses the evolution of meaning and intentions in collaborative problem solving. The analysis is informed by Semiotics and Speech Act theories. From this analysis, the paper proposes a conceptual framework for multidisciplinary research in three interconnected perspectives: interactive, conceptual and technical.

Keywords

Pragmatic web Social network systems Organizational semiotics Knowledge evolution Knowledge visualization 

Notes

Acknowledgements

This work is partially funded by CNPq (#560044/2010-0, #141058/2010-2), by Proesp/CAPES (#23038.01457/2009-11) and CAPES (#01-P-08503/2008). The authors also thank colleagues from InterHAD for insightful discussions.

References

  1. 1.
    Austin, J.L.: How to Do Things With Words. Oxford University Press, Oxford (1962)Google Scholar
  2. 2.
    Avery, J., Yearwood, J.: Dowl: A dynamic ontology language. In: Proceedings of the IADIS International Conference WWW/Internet 2003, Algarve, Portugal (2003)Google Scholar
  3. 3.
    Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Sci. Am. 284(5), 34–43 (2001)CrossRefGoogle Scholar
  4. 4.
    Bonacin, R., Dos Reis, J.C., Hornung, H., Baranauskas, M.C.C.: An ontological model for representing pragmatic aspects on collaborative problem solving. In: WETICE’12: Proceedings of the IEEE 21st International WETICE, Washington, DC, USA, pp. 444−449. IEEE Computer Society (2012)Google Scholar
  5. 5.
    Burkhard, R.: Learning from architects: The difference between knowledge visualization and information visualization. In: Eight International Conference on Information Visualization (IV04), London, July (2004)Google Scholar
  6. 6.
    Hornung, H., Baranauskas, M.C.C.: Towards a Conceptual Framework for Interaction Design for the Pragmatic Web. In: Jacko, J.A. (ed.) Human-Computer Interaction, Part I, HCII 2011. LNCS, vol. 6761, pp. 72–81. Springer, Heidelberg (2011)Google Scholar
  7. 7.
    Cordeiro, J., Filipe, J.: Language action perspective, organizational semiotics and the theory of organized activity – a comparison. In: Proceedings of the Workshop DEMO. Tilburg, The Netherlands (2003)Google Scholar
  8. 8.
    de Moor, A., van den Heuvel, W.-J.: Web service selection in virtual communities. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences, Washington, DC, USA, 10 p. IEEE Computer Society (2004)Google Scholar
  9. 9.
    Eppler, M., Burkhard R.: Knowledge visualization. Towards a new discipline and its fields of application. Working Paper of Net Academy on Knowledge Media, St. Gallen (2004)Google Scholar
  10. 10.
    Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G.: Ontology change: Classification and survey. Knowl. Eng. Rev. 23(2), 117–152 (2007)Google Scholar
  11. 11.
    Gibson, J.J.: The Ecological Approach to Visual Perception. Houghton Miffin Company, Boston (1968)Google Scholar
  12. 12.
    Goldkuhl, G., Lyytinen, K.: A language action view of information systems. In: Proceedings of the 3rd International Conference on Information Systems, Ann Arbor, MI, pp. 13−29 (1982)Google Scholar
  13. 13.
    Gruber, T.: Collective knowledge systems: Where the social web meets the semantic web. J. Web Seman. 6(1), 4–13 (2008)CrossRefGoogle Scholar
  14. 14.
    Hendler, J., Berners-Lee, T.: From the semantic web to social machines: A research challenge for AI on the World Wide Web. Artif. Intell. 174, 156–161 (2010). ElsevierCrossRefGoogle Scholar
  15. 15.
    Hoetzlein, R.: The Organization of Human Knowledge: Systems for Interdisciplinary Research. Master’s Thesis, University of California Santa Barbara, USA (2007)Google Scholar
  16. 16.
    Keller, T., Tergan, S.-O.: Visualizing Knowledge and Information: An Introduction. In: Tergan, S.-O., Keller, T. (eds.) Knowledge and Information Visualization. LNCS, vol. 3426, pp. 1–23. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  17. 17.
    Klein, M., Fensel, D.: Ontology versioning for the semantic web. In: Proceedings of the International Semantic Web Working Symposium (SWWS), Stanford University, California, USA (2001)Google Scholar
  18. 18.
    Kuß, A., Prohaska, S., Rybak, J.: Using ontologies for the visualization of hierarchical neuroanatomical structures. In: 2nd INCF Congress of Neuroinformatics (2009)Google Scholar
  19. 19.
    De Leenheer, P., Meersman, R.: Towards Community-Based Evolution of Knowledge-Intensive Systems. In: Meersman, R., Tari, Z. (eds.) OTM 2007, Part I. LNCS, vol. 4803, pp. 989–1006. Springer, Heidelberg (2007)Google Scholar
  20. 20.
    Liu, K.: Semiotics in Information Systems Engineering. Cambridge University Press, New York (2000)CrossRefGoogle Scholar
  21. 21.
    Liu, K.: Pragmatic Computing – A Semiotic Perspective to Web Services. In: Filipe, J., Obaidat, M.S. (eds.) ICETE 2007, Part I. CCIS, vol. 23, pp. 3–15. Springer, Heidelberg (2008)Google Scholar
  22. 22.
    Maseri, W., Mohamad, W., Embong, A., Mohd Zain, J.: Improve knowledge visualization through an interactive graph-based dashboard system with key performance indicator: A case study of university dashboard for higher education. In: National Conference on Software Engineering & Computer Systems 2007 (NaCES 2007), Legend Resort Kuantan (2007)Google Scholar
  23. 23.
    Morris, C.W.: Foundations of the Theory of Signs. International Encyclopedia of Unified Science, vol. 1, p. 2. University of Chicago Press, Chicago (1938)Google Scholar
  24. 24.
    Pampalk, E., Goebl, W., Widmer, G.: Visualizing Changes in the Structure of Data for Exploratory Feature Selection. In: SIGKDD’03, Washington, DC, USA (2003)Google Scholar
  25. 25.
    Paschke, A., Boley, H., Kozlenkov, A., Craig, B.: Rule Responder: RuleML-Based Agents for Distributed Collaboration on the Pragmatic Web. In: ICPW’07: Proceedings of the 2nd International Conference on Pragmatic Web, pp. 17–28. ACM, New York (2007)Google Scholar
  26. 26.
    Schoop, M., de Moor, A., Dietz, J.L.G.: The pragmatic web: A manifesto. Commun. ACM 49(5), 75–76 (2006)CrossRefGoogle Scholar
  27. 27.
    Searle, J.R.: A classification of illocutionary acts. Lang. Soc. 5(1), 1–23 (1976)CrossRefGoogle Scholar
  28. 28.
    Singh, M.P.: The pragmatic web. IEEE Internet Comput. 6(3), 4–5 (2002)CrossRefGoogle Scholar
  29. 29.
    Stamper, R.: Signs, information and systems. In: Holmqnist, B., et al. (eds.) Signs of Work Semiotics Information Processing in Organisations, Walter de Gruyter, New York (1996)Google Scholar
  30. 30.
    Stojanovic, L.: Methods and tools for ontology evolution. PhD. Thesis. University of Karlsruhe, Universitat Karlsruhe (TH), Institut AIFB, D-76128 Karlsruhe (2004)Google Scholar
  31. 31.
    Winograd, T., Flores, F.: Understanding Computers and Cognition: A New Foundation for Design. Addison-Wesley Longman Publishing Co., Inc., Boston (1987)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rodrigo Bonacin
    • 1
  • Heiko Hornung
    • 2
  • Julio Cesar Dos Reis
    • 3
  • Roberto Pereira
    • 2
  • M. Cecília C. Baranauskas
    • 2
  1. 1.FACCAMP and CTI Renato ArcherCampinas–SPBrazil
  2. 2.Institute of ComputingUNICAMPCampinas–SPBrazil
  3. 3.CR SANTECPublic Research Centre Henri TudorLuxembourgLuxembourg

Personalised recommendations