Exploiting Alternative Knowledge Visualizations and Reasoning Mechanisms to Enhance Collaborative Decision Making

  • Spyros Christodoulou
  • Nikos Karacapilidis
  • Manolis Tzagarakis
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 42)


Collaborative decision making in today’s knowledge intensive and multi-disciplinary environments is a challenging task. The diversity of these environments and the associated plurality of decision makers’ perceptions of the issue under consideration require the exploitation of a variety of meaningful knowledge visualizations and reasoning mechanisms to effectively support the overall stakeholders’ collaboration towards making a decision. This chapter reports on an innovative approach that offers a number of interrelated visualizations of the knowledge exchanged and shared during a collaborative decision making process. These visualizations incorporate suitable reasoning mechanisms that exploit human and machine understandable knowledge to facilitate the underlying what-if analysis and aid stakeholders towards reaching consensus and, ultimately, making a collective decision.


Collaboration Multi-criteria decision making Group decision making Computer-supported cooperative work 


  1. 1.
    Jelassi, M.T., Kersten, G., Zionts, S.: An introduction to group decision and negotiation support, In: Bana e Costa, C.A. (ed.) Readings in Multiple Criteria Decision Aid. Springer, Berlin (1990)Google Scholar
  2. 2.
    Ness, J., Hoffman, C.: Putting Sense into Consensus: Solving the Puzzle of Making Team Decisions, Tacoma. VISTA Associates, Wash (1998)Google Scholar
  3. 3.
    Bogetoft, P., Pruzan, P.: Planning with Multiple Criteria: Investigation, Communication, Choice. North Holland, Amsterdam (1991)Google Scholar
  4. 4.
    Challenges and Opportunities with Big Data, White Paper, Computing Community Consortium, Spring (2012)Google Scholar
  5. 5.
    Hwang, C.L., Ling, M.J.: Group Decision Making Under Multiple Criteria. Lecture Notes in Economics and Mathematical Systems, vol. 281. Springer, Berlin (1987)Google Scholar
  6. 6.
    Figueira, J., Greco, S., Ehrogott, M.: Multiple Criteria Decision Analysis: State of the Art Surveys. International Series in Operations Research & Management Science, vol. 78, (2005)Google Scholar
  7. 7.
    Bui, T.X., Jarke, M.: Communications design for Co-oP: a group decision support system. ACM Trans. Off. Inf. Syst. 4, 2 (1986)CrossRefGoogle Scholar
  8. 8.
    Vincke, P.: Multi-criteria Decision-Aid. Wiley, Chichester (1992)Google Scholar
  9. 9.
    Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980)MATHGoogle Scholar
  10. 10.
    Roy, B.: The outranking approach and the foundations of ELECTRE methods. Theory and Decision 31, 49–73 (1991)CrossRefMathSciNetGoogle Scholar
  11. 11.
    Brans, J.P., Mareschal, B., Vincke, Ph.: PROMETHEE: a new family of outranking methods in multicriteria analysis. In: Brans, J.P. (ed.) Operational Research, IFORS 84, pp. 477–490. North Holland, Amsterdam (1984)Google Scholar
  12. 12.
    Karacapilidis, N., Rüping, S., Tzagarakis, M., Poigné, A., Christodoulou, S.: Building on the synergy of machine and human reasoning to tackle data-intensive collaboration and decision making. In: Proceedings of IDT 2011, pp. 113–122. Piraeus, Greece (2011)Google Scholar
  13. 13.
    de la Calle, G., Alonso-Martínez, E., Tzagarakis, M., Karacapilidis, N.: The dicode workbench: a flexible framework for the integration of information and web services. In: Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services (iiWAS2012), pp. 16–25. Bali, Indonesia, 3–5 Dec 2012Google Scholar
  14. 14.
    Swick, R.R., Ackerman, M.S.: The X toolkit: more bricks for building user interfaces, or widgets for hire. In: Usenix Winter 1988 Conference, pp. 221–228 (1988)Google Scholar
  15. 15.
    Pautasso, C., Zimmermann, O., Leymann, F.: Restful web services vs. “big” web services: making the right architectural decision. In: Proceeding of the 17th International Conference on World Wide Web, pp. 805–814. ACM, New York, NY, USA (2008)Google Scholar
  16. 16.
    Thakker, D., Yang-Turner, F., Lau, L., Dimitrova, V.: Socio-technical ontology development for modelling sensemaking in heterogeneous domains. In: Proceedings of OCAS 2011 Workshop at the 10th International Semantic Web Conference, pp. 60–71. Bonn, Germany, (Oct 2011)Google Scholar
  17. 17.
    Kunz, W., Rittel, H.W.J.: Issues as elements of information systems. Working paper, 1–9. University of California at Berkeley (1970)Google Scholar
  18. 18.
    Marshall, C.C., Shipman, F.M.: III: Spatial hypertext and the practice of information triage, In: Proceedings of the 8th ACM Conference on Hypertext, pp. 124–133. Southampton, United Kingdom, 06–11 (April 1997)Google Scholar
  19. 19.
    Karacapilidis, N., Papadias, D.: Computer supported argumentation and collaborative decision making: the HERMES system. Inf. Syst. 26(4), 259–277 (2001)CrossRefMATHGoogle Scholar
  20. 20.
    Triantaphyllou, E., Sanchez, A.: A sensitivity analysis approach for some deterministic MCDM methods. Decis. Sci. 28(1), 151–194 (1997)CrossRefGoogle Scholar
  21. 21.
    Scheuer, O., Loll, F., Pinkwart, N., McLaren, B.M.: Computer-supported argumentation: a review of the state of the art. Int. J. Comput. Support. Collaborative Learn. 5(1), 43–102 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Spyros Christodoulou
    • 1
  • Nikos Karacapilidis
    • 1
  • Manolis Tzagarakis
    • 1
  1. 1.Computer Technology Institute & Press “Diophantus” and University of PatrasRio PatrasGreece

Personalised recommendations