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Visualization on Decision Support Systems Models: Literature Overview

  • Carlos Manuel Oliveira Alves
  • Manuel Pérez Cota
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)

Abstract

The information visualization (InfoVis) is defined as “the use of visual, interactive and visual representations supported by computer, to increase cognition”. InfoVis tools and methods help us to accelerate our understanding and action in a world of ever-increasing data volumes. Data visualization improves understanding, particularly with multidimensional data sets. Visual analysis methods allow decision makers to match their human flexibility, creativity and background knowledge with the enormous storage and processing capabilities of today’s computers for information on complex problems. Using advanced visual interfaces, humans can interact directly with data analysis.

In this article, we will review the literature about the subject “Visualization on Decision Support Systems Models”, with a main focus on the architectures used and the approaches to the visualization of the extracted information resulting from the existing data, with main incidence in the last few years.

Keywords

DSS DSSM V-DSSM 

References

  1. 1.
    Liu, T., Pan, Q., Sanchez, J., Sun, S., Wang, N., Yu, H.: Prototype decision support system for black ice detection and road closure control. In: IEEE Intelligent Transportation Systems Magazine (2017)CrossRefGoogle Scholar
  2. 2.
    Müller, H., Reihs, R., Posch, A.E., Kremer, A., Ulrich, D., Zatloukal, K.: Data driven GUI design and visualization for a NGS based clinical decision support system. In: 2016 20th International Conference Information Visualisation (2016)Google Scholar
  3. 3.
    Armstrong, L.J., Nallan, S.A.: Agricultural decision support framework for visualization and prediction of western australian crop production. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom) (2016)Google Scholar
  4. 4.
    Schreder, G., Windhager, F., Smuc, M., Mayr, E.: Supporting cognition in the face of political data and discourse: a mental models perspective on designing information visualization systems. In: 2016 Conference for E-Democracy and Open Government (CeDEM) (2016)Google Scholar
  5. 5.
    Antunes, S.H.M.B.B., Rodrigues, C.S.C., Werner, C.M.L.: Supporting system modeling learning using gestures for visualization control as method of immersion. In: 2016 XVIII Symposium on Virtual and Augmented Reality (2016)Google Scholar
  6. 6.
    Parygin, D., Sadovnikova, N., Kalinkina, M., Potapova, T., Finogeev, A.: Visualization of data about events in the urban environment for the decision support of the city services actions coordination. In: 2016 International Conference System Modeling & Advancement in Research Trends (SMART) (2016)Google Scholar
  7. 7.
    Kozielski, M., Sikora, M., Wróbel, Ł.: DISESOR - decision support system for mining industry. In: Proceedings of the Federated Conference on Computer Science and Information Systems (2015)Google Scholar
  8. 8.
    Nevo, D., Nevo, S., Kumar, N., Braasch, J., Mathews, K.: Enhancing the visualization of big data to support collaborative decision-making. In: 2015 48th Hawaii International Conference on System Sciences (2015)Google Scholar
  9. 9.
    Ellouzj, H., Ltifi, H., Ayed, M.B.: New multi-agent architecture of visual intelligent decision support systems application in the medical field. In: 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA) (2015)Google Scholar
  10. 10.
    Bencsik, G., Bacsárdi, L.: Towards to decision support generalization: the universal decision support system concept. In: 2015 IEEE 19th International Conference on Intelligent Engineering Systems (INES) (2015)Google Scholar
  11. 11.
    Toyoda, S., Niki, N.: Visualization-based medical expenditure analysis support system. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2015)Google Scholar
  12. 12.
    Lim, J., Choi, J., Choi, H., Joo, J., Cha, J.: Expert criteria based probabilistic power system health index model and visualization. In: 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) (2014)Google Scholar
  13. 13.
    Madureira, A., Gomes, S., Cunha, B., Pereira, J.P., Santos, J.M., Pereira, I.: Prototype of an adaptive decision support system for interactive scheduling with metacognition and user modeling experience. In: 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014) (2014)Google Scholar
  14. 14.
    Trase, K., Fink, E.: A model-driven visualization tool for use with model-based systems engineering projects. In: 2014 IEEE Aerospace Conference (2014)Google Scholar
  15. 15.
    Kos, L., et al: Visualization support for code development in EUROfusion integrated modelling. In: MIPRO 2014 (2014)Google Scholar
  16. 16.
    Lee, H.-E., Kang, N.,.Han, J.-J., Kim, J.-Y., Kim, K.H., Kim, J.D.K., Kim, C.Y.: Interactive manipulation and visualization of a deformable 3D organ model for medical diagnostic support. In: The 10th Annual IEEE CCNC Conference- 3D Imaging & Processing & Communication and Display Track (2013)Google Scholar
  17. 17.
    Luhr, R., Reimanis, D., Cross, R., Izurieta, C., Poole, G.C., Helton, A.: Natural science visualization using digital theater software adapting existing planetarium software to model ecological systems. In: 2013 International Conference on Information Science and Applications (ICISA) (2013)Google Scholar
  18. 18.
    Grignard, A., Drogoul, A., Zucker, J.-D.: A model-view/controller approach to support visualization and online data analysis of agent-based simulations. In: 2013 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for the Future (RIVF) (2013)Google Scholar
  19. 19.
    Yan, X., Qiao, M., Li, J., Simpson, T.W., Stump, G.M., Zhang, X.: A work-centered visual analytics model to support engineering design with interactive visualization and data-mining. In: 2012 45th Hawaii International Conference on System Sciences (2012)Google Scholar
  20. 20.
    Groumpos, P.P.: Conceptual modeling and decision making support systems for complex dynamical systems: a critical overview. In: 2016 ELEKTRO (2016)Google Scholar
  21. 21.
    Keen, P.G.W., Morton, M.S.S.: Decision Support System an Organizational Perspective. Addison-Wesley, Massachusetts (1978)Google Scholar
  22. 22.
    Bonczek, R.H., Holsapple, C.W., Whinston, A.B.: Foundation of Decision Support Systems. Academic Press, New York (1981)zbMATHGoogle Scholar
  23. 23.
    Sprague Jr., R.H.: A framework for the development of decision support systems. Manage. Inf. Syst. Q. 4, 1–26 (1980)CrossRefGoogle Scholar
  24. 24.
    Sprague Jr., R.H., Carlson, E.D.: Building Effective Decision Support System. Prentice-Hall, Englewood Cliffs (1982)Google Scholar
  25. 25.
    De Sanctis, G., Gallupe, B.R.: A foundation for the study of group decision support systems. Manage. Sci. 33, 589–609 (1987)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Carlos Manuel Oliveira Alves
    • 1
  • Manuel Pérez Cota
    • 2
  1. 1.Instituto Politécnico de Castelo BrancoCastelo BrancoPortugal
  2. 2.Universidade de VigoVigoSpain

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