Visual Analytics: Data, Analytical and Reasoning Provenance

  • Margaret VargaEmail author
  • Caroline Varga
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)


Analysts and decision makers are increasingly overloaded with vast amounts of data/information which are often dynamic, complex, disparate, conflicting, incomplete and, at times, uncertain. Furthermore, problems and tasks that require their attention can be ambiguous, i.e. they are ill-defined. In order to make sense of complex data and situations and make informed decisions, they utilize their intuition, knowledge and experience. Provenance is fundamental for the user to capture and exploit effectively the explicit data and implicit knowledge within the decision making process. Provenance can usefully be considered at three conceptual levels, namely: data (what), analytical (how) and reasoning (why). This paper explores visual analytics in the exploitation of provenance within the decision making process.


Analytical provenance Data provenance Hypothesis Reasoning provenance Visual analytics Visualization 


  1. 1.
    Attfield, S.J., Hara, S.K., Wong, B.L.W.: Sensemaking in visual analytics: processes and challenges. In: Kohlhammer, J., Keim, D. (eds.) EuroVAST 2010: International Symposium on VAST, pp. 1–6. Eurographics Association, Bordeaux, France (2010)Google Scholar
  2. 2.
    Gotz, D., Zhou, M.X.: Characterizing users’ visual analytic activity for insight provenance. Inf. Vis. 8(1), 42–55 (2009)CrossRefGoogle Scholar
  3. 3.
    Jankun-Kelly, T.J.: The Case for Visual Analysis Provenance Cases, Workshop on Analytic Provenance: Process + Interaction + Insight, CHI. (2011)Google Scholar
  4. 4.
    Venters, C.C., Austin, J., Dibsdale, C.E., Dimitrova, V., Djemame, K., Fletcher, M., Fores, S., Hobson, S., Lau, L., McAvoy, J., Marshall, A., Townend, P., Taylor, N., Viduto, V., Webster, D.E., Xu, J.: To trust or not to trust? Developing trusted digital spaces through timely reliable and personalized provenance. In: Provenance for Sensemaking. Paris, France (10th November 2014)Google Scholar
  5. 5.
    Roberts, J.C., Keim, D., Hanratty, T., Rowlingson, R., Hall, M., Jacobson, Z., Lavigne, V., Rooney, C., Varga, M.: From Ill-defined Problems to Informed Decisions. EuroVis Workshop on Visual Analytics, UK (2014)Google Scholar
  6. 6.
    Silva, C.T., Freire, J., Callahan, S.: Provenance for visualizations: reproducibility and beyond. Comput. Sci. Eng. 9(5), 82–90 (2007)CrossRefGoogle Scholar
  7. 7.
    Groth, D., Streefkerk, K.: Provenance and annotation for visual exploration systems. IEEE Trans. Vis. Comput. Graph. 12(6), 1500–1510 (2006)CrossRefGoogle Scholar
  8. 8.
    Boren, T., Ramey, J.: Thinking aloud: reconciling theory and practice. IEEE Trans. Prof. Commun. 43(3), 261–278 (2000)CrossRefGoogle Scholar
  9. 9.
    Hertzum, M., Hansen, K.D., Andersen, H.H.K.: Scrutinising usability evaluation: does thinking aloud affect behavior and mental workload? Behav. Inf. Technol. 28(2), 165–181 (2009)CrossRefGoogle Scholar
  10. 10.
    Schacter, D.: Psychology, 2nd edn. Worth Publishers, NY (2009)Google Scholar
  11. 11.
    Thomas, J.J., Cook, K.A.: Illuminating the Path: The Research and Development Agenda for Visual Analytics. National Visualization and Analytics Centre (2005)Google Scholar
  12. 12.
    Keim, D.A., Kohlhammer, J., Ellis, G., Mansmann, F.: Mastering the Information Age-Solving Problems with Visual Analytics. Florian Mansmann (2010)Google Scholar
  13. 13.
    Keim, D.A., Mansmann, F., Thomas, J.: Visual analytics: how much visualization and how much analytics? SIGKDD Explor. 11(2), 5–8 (2009)CrossRefGoogle Scholar
  14. 14.
    Thomas, J.J.: Taxonomy for Visual Analytics: Seeking Feedback. VAC Views (May 2009)Google Scholar
  15. 15.
    FM 2-22.3 (FM 34-52) Human Intelligence Collector Operations, US Department of the Army (September 2006)Google Scholar
  16. 16.
    Johnson, R.: Analytics Culture in the U.S. Intelligence Community: An Ethnographic Study, Centre for the Study of Intelligence. Central Intelligence Agency, Washington (2005)Google Scholar
  17. 17.
    Moore, D.T.: Critical Thinking and Intelligence Analysis, Occasional Paper Number 14. National Defense Intelligence College, Washington (March 2007)Google Scholar
  18. 18.
    Varga, M.J., Adams, K.: Interactive hypothesis visualization. In: NATO Workshop on Visualising Networks: Coping with Change and Uncertainty (October 2010)Google Scholar
  19. 19.
    Anderson, T., Schum, D., Twining, W.: Analysis of Evidence, 2nd edn. Cambridge University Press (2005)Google Scholar
  20. 20.
    Toulmin, S.E.: The Uses of Argument - Updated Edition. Cambridge University Press, Cambridge (2003)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Seetru LtdBristolUK
  2. 2.University of OxfordOxfordUK

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