CONTASK: Context-Sensitive Task Assistance in the Semantic Desktop

  • Heiko Maus
  • Sven Schwarz
  • Jan Haas
  • Andreas Dengel
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 73)

Abstract

In knowledge work, users are confronted with difficulties in remembering, retrieving, and accessing relevant information and knowledge for their task at hand. In addition, knowledge-intensive, task-oriented work is highly fragmented and, therefore, requires knowledge workers to effectively handle and recover from interruptions.

The Semantic Desktop approach provides an environment to represent, maintain, and work with a user’s personal knowledge space. We present an approach to support knowledge-intensive tasks with a context-sensitive task management system that is integrated in the Nepomuk Semantic Desktop. The context-sensitive assistance is based on the combination of user observation, agile task modelling, automatic task prediction, as well as elicitation and proactive delivery of relevant information items from the knowledge worker’s personal knowledge space.

Keywords

Task management Proactive information delivery Personal knowledge space User observation Agile task modelling Semantic desktop Personal information management 

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References

  1. 1.
    González, V.M., Mark, G.: Managing currents of work: multi-tasking among multiple collaborations. In: ECSCW 2005: 9th European Conference on Computer Supported Cooperative Work, pp. 143–162. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Mark, G., Gudith, D., Klocke, U.: The cost of interrupted work: more speed and stress. In: CHI 2008: SIGCHI Conference on Human Factors in Computing Systems, pp. 107–110. ACM, New York (2008)Google Scholar
  3. 3.
    Abecker, A., Hinkelmann, K., Maus, H., Müller, H.J. (eds.): Geschäftsprozessorientiertes Wissensmanagement. xpert.press. Springer, Heidelberg (2002)Google Scholar
  4. 4.
    Riss, U., Rickayzen, A., Maus, H., van der Aalst, W.: Challenges for Business Process and Task Management. Journal of Universal Knowledge Management (2), 77–100 (2005)Google Scholar
  5. 5.
    van Elst, L., Aschoff, F.R., Bernardi, A., Maus, H., Schwarz, S.: Weakly-structured workflows for knowledge-intensive tasks: An experimental evaluation. In: IEEE WETICE Workshop on Knowledge Management for Distributed Agile Processes (KMDAP 2003), IEEE Computer Society Press, Los Alamitos (2003)Google Scholar
  6. 6.
    Holz, H., Rostanin, O., Dengel, A., Suzuki, T., Maeda, K., Kanasaki, K.: Task-based process know-how reuse and proactive information delivery in TaskNavigator. In: CIKM 2006: ACM Conference on Information and Knowledge Management (2006)Google Scholar
  7. 7.
    Rostanin, O., Maus, H., Zhang, Y., Suzuki, T., Maeda, K.: Lightweight conceptual modeling and concept-based tagging for proactive information delivery. Ricoh technology report 2009, no. 35, Ricoh Co Ltd., Japan (December 2009)Google Scholar
  8. 8.
    González, V.M., Mark, G.: “Constant, constant, multi-tasking craziness”: managing multiple working spheres. In: CHI 2004: SIGCHI Conference on Human Factors in Computing Systems, pp. 113–120. ACM, New York (2004)CrossRefGoogle Scholar
  9. 9.
    Czerwinski, M., Horvitz, E., Wilhite, S.: A diary study of task switching and interruptions. In: CHI 2004: SIGCHI Conference on Human Factors in Computing Systems, pp. 175–182. ACM, New York (2004)CrossRefGoogle Scholar
  10. 10.
    Iqbal, S.T., Horvitz, E.: Disruption and recovery of computing tasks: field study, analysis, and directions. In: CHI 2007: SIGCHI Conference on Human factors in Computing Systems, pp. 677–686. ACM, New York (2007)Google Scholar
  11. 11.
    Mark, G., Gonzalez, V.M., Harris, J.: No task left behind?: examining the nature of fragmented work. In: CHI 2005: SIGCHI Conference on Human Factors in Computing Systems, pp. 321–330. ACM Press, New York (2005)Google Scholar
  12. 12.
    Stumpf, S., Bao, X., Dragunov, A., Dietterich, T.G., Herlocker, J., Johnsrude, K., Li, L., Shen, J.: The TaskTracer system. In: 20th National Conference on Artificial Intelligence, AAAI 2005 (2005)Google Scholar
  13. 13.
    Stumpf, S., Bao, X., Dragunov, A., Dietterich, T.G., Herlocker, J., et al.: Predicting user tasks: I know what you’re doing! In: 20th National Conference on Artificial Intelligence, AAAI 2005 (2005)Google Scholar
  14. 14.
    Lokaiczyk, R., Faatz, A., Beckhaus, A., Goertz, M.: Enhancing Just-in-Time E-Learning Through Machine Learning on Desktop Context Sensors. In: Kokinov, B., Richardson, D.C., Roth-Berghofer, T.R., Vieu, L. (eds.) CONTEXT 2007. LNCS (LNAI), vol. 4635, pp. 330–341. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  15. 15.
    Lepouras, G., Dix, A., Katifori, A.: OntoPIM: From personal information management to task information management. In: SIGIR 2006 Personal Information Management Workshop (2006)Google Scholar
  16. 16.
    Grebner, O., Ong, E., Riss, U.: Kasimir - work process embedded task management leveraging the semantic desktop. In: Multikonferenz Wirtschaftsinformatik, pp. 1715–1726 (2008)Google Scholar
  17. 17.
    Stoitsev, T., Scheidl, S., Flentge, F., Mühlhäuser, M.: From personal task management to end-user driven business process modeling. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 84–99. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  18. 18.
    Grimnes, G.A., Adrian, B., Schwarz, S., Maus, H., Schumacher, K., Sauermann, L.: Semantic desktop for the end-user. i-com 8(3), 25–32 (2009)CrossRefGoogle Scholar
  19. 19.
    Sauermann, L., Bernardi, A., Dengel, A.: Overview and Outlook on the Semantic Desktop. In: 1st Workshop on The Semantic Desktop at ISWC 2005. CEUR Proceedings, vol. 175, pp. 1–19 (November 2005)Google Scholar
  20. 20.
    Adrian, B., Klinkigt, M., Maus, H., Dengel, A.: Using idocument for document categorization in nepomuk social semantic desktop. In: Pellegrini, T. (ed.) i-Semantics: Proceedings of International Conference on Semantic Systems 2009. JUCS (2009)Google Scholar
  21. 21.
    Schwarz, S.: A context model for personal knowledge management applications. In: Roth-Berghofer, T.R., Schulz, S., Leake, D.B. (eds.) MRC 2005. LNCS (LNAI), vol. 3946, pp. 18–33. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  22. 22.
    Schwarz, S.: Context-Awareness and Context-Sensitive Interfaces for Knowledge Work Support. PhD thesis, University of Kaiserslautern (2010)Google Scholar
  23. 23.
    Schwarz, S., Kiesel, M., van Elst, L.: Adapting the multi-desktop paradigm towards a multi-context interface. In: HCP-2008 Proc., Part II, MRC 2008 – 5th Int. Workshop on Modelling and Reasoning in Context, pp. 63–74 TELECOM Bretagne (June 2008)Google Scholar
  24. 24.
    Holz, H., Maus, H., Bernardi, A., Rostanin, O.: From Lightweight, Proactive Information Delivery to Business Process-Oriented Knowledge Management. Journal of Universal Knowledge Management (2), 101–127 (2005)Google Scholar
  25. 25.
    Dellmuth, S., Maus, H., Dengel, A.: Supporting knowledge work by observing paper-based activities on the physical desktop. In: Proceedings of 3rd Int. Workshop on Camera Based Document Analysis and Recognition, CBDAR 2009 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Heiko Maus
    • 1
  • Sven Schwarz
    • 1
  • Jan Haas
    • 2
  • Andreas Dengel
    • 1
    • 2
  1. 1.German Research Center for AI (DFKI GmbH)KaiserslauternGermany
  2. 2.Computer Science DepartmentUniversity of KaiserslauternKaiserslauternGermany

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