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Supporting Analytical Reasoning and Presentation with Analytic Provenance

Registration 29/11/2012. Supporting Analytical Reasoning and Presentation with Analytic Provenance. Phong H. Nguyen p.nguyen@mdx.ac.uk. Agenda. Literature Review Research Questions Plan. Agenda. Literature Review Research Questions Plan. Analytic Provenance. WHAT?

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Supporting Analytical Reasoning and Presentation with Analytic Provenance

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  1. Registration 29/11/2012 Supporting Analytical Reasoning and Presentation with Analytic Provenance Phong H. Nguyen p.nguyen@mdx.ac.uk

  2. Agenda • Literature Review • Research Questions • Plan

  3. Agenda • Literature Review • Research Questions • Plan

  4. Analytic Provenance • WHAT? • Understanding a user’s reasoning process through the study of their interactions with visualisations • WHY? • Recalling the analysis process • Reusing the performed analyses • Facilitating reasoning • Supporting collaboration

  5. Three Stages of Analytic Provenance 4 3 2 1 7 5 6 UTILISE CAPTURE VISUALISE INTERACTION

  6. Three Stages of Analytic Provenance • Capturing • Visualising • Utilising

  7. Capturing • Four-semantic-level model Gotz, D. & Zhou, M.X., 2009. Characterizing users’ visual analytic activity for insight provenance. Information Visualization, 8(1), pp.42–55

  8. Capturing Bottom-Level Events • Keyboard/mouse events • Window events • File open and save events • Copy/paste events • …

  9. Capturing Low-Level Actions • Taxonomy of Actions Gotz, D. & Zhou, M.X., 2009. Characterizing users’ visual analytic activity for insight provenance. Information Visualization, 8(1), pp.42–55

  10. Capturing High-Level Sub-Tasks Automatic derivation Manual capture Gotz, D. & Zhou, M.X., 2009. Characterizing users’ visual analytic activity for insight provenance. Information Visualization, 8(1), pp.42–55 J. Heer, F. B. Viégas, and M. Wattenberg, “Voyagers and Voyeurs: Supporting Asynchronous Collaborative Visualization,” Communications of the ACM, vol. 52, no. 1, pp. 87–97, Jan. 2009.

  11. Capturing Top-Level Tasks • Explicit input • Highly domain-specific • Documenting the reasoning process Y. B. Shrinivasan and J. J. van Wijk, “Supporting the Analytical Reasoning Process in Information Visualization,” in ACM Conference on Human Factors in Computing Systems, 2008, pp. 1237–1246.

  12. Three Stages of Analytic Provenance • Capturing • Visualising • Utilising

  13. Visualising the Captured Information • Events • Actions + States: analysis process • Sub-tasks + Tasks: reasoning process

  14. Visualising States R. R. Hightower, L. T. Ring, J. I. Helfman, B. B. Bederson, and J. D. Hollan, “Graphical Multiscale Web Histories: A Study of PadPrints,” in ACM Symposium on User Interface Software and Technology, 1998, pp. 121–122. S. R. Klemmer, M. Thomsen, E. Phelps-Goodman, R. Lee, and J. A. Landay, “Where do web sites come from? Capturing and Interacting with Design History,” in ACM Conference on Human Factors in Computing Systems, 2002, pp. 1–8. D. Kurlander and S. Feiner, “Editable graphical histories,” in IEEE Workshop on Visual Languages, 1988, pp. 127–134.

  15. Visualising Actions Gotz, D. & Zhou, M.X., 2009. Characterizing users’ visual analytic activity for insight provenance. Information Visualization, 8(1), pp.42–55 K.-L. Ma, “Image graphs - a novel approach to visual data exploration,” in IEEE Conference on Visualization, 1999, pp. 81–88.

  16. Visualising the Analysis Process L. Bavoil, S. P. Callahan, P. J. Crossno, J. Freire, C. E. Scheidegger, C. T. Silva, and H. T. Vo, “VisTrails: Enabling Interactive Multiple-View Visualizations,” in IEEE Symposium on Information Visualization, 2005, pp. 135–142. Y. B. Shrinivasan and J. J. van Wijk, “Supporting the Analytical Reasoning Process in Information Visualization,” in ACM Conference on Human Factors in Computing Systems, 2008, pp. 1237–1246.

  17. Visualising the Reasoning Process Y. B. Shrinivasan and J. J. van Wijk, “Supporting the Analytical Reasoning Process in Information Visualization,” in ACM Conference on Human Factors in Computing Systems, 2008, pp. 1237–1246.

  18. Three Stages of Analytic Provenance • Capturing • Visualising • Utilising

  19. Utilising the Visualised Provenance • Recalling the analysis process • Navigation, search and filter Y. B. Shrinivasan and J. J. van Wijk, “Supporting the Analytical Reasoning Process in Information Visualization,” in ACM Conference on Human Factors in Computing Systems, 2008, pp. 1237–1246.

  20. Utilising the Visualised Provenance • Reusing the performed analyses • Insert/remove/revise/merge past actions • Reapply actions for new datasets M. Derthick and S. F. Roth, “Enhancing data exploration with a branching history of user operations,” Knowledge-Based Systems, vol. 14, no. 1–2, pp. 65–74, 2001.

  21. Utilising the Visualised Provenance • Supporting evidence in constructing the reasoning process Y. B. Shrinivasan and J. J. van Wijk, “Supporting the Analytical Reasoning Process in Information Visualization,” in ACM Conference on Human Factors in Computing Systems, 2008, pp. 1237–1246.

  22. Utilising the Visualised Provenance • Dissemination & Discussion R. Eccles, T. Kapler, R. Harper, and W. Wright, “Stories in GeoTime,” IEEE Symposium on Visual Analytics Science And Technology, vol. 7, no. 1, pp. 19–26, 2007.

  23. Utilising the Visualised Provenance • Presentation: Animation/Latex/Print S. R. Klemmer, M. Thomsen, E. Phelps-Goodman, R. Lee, and J. A. Landay, “Where do web sites come from? Capturing and Interacting with Design History,” in ACM Conference on Human Factors in Computing Systems, 2002, pp. 1–8.

  24. Agenda • Literature Review • Research Questions • Plan

  25. Research Question 1 How to capture the provenance of the analytical reasoning process including both high-level reasoning and its low-level interactions performed? • Challenges • Domain-specific • Thinking inside • Existing research • Automatic derivation • Manual annotation • Reasoning process construction UTILISE CAPTURE VISUALISE

  26. Research Question 1 - Proposal • A seamless integration of the exploration space and the reasoning space • Novel techniques to facilitate the reasoning process construction • A novel annotation mechanism to encourage taking notes and annotating • A heuristic to automatically infer user intentions from continuous and closely related interactions

  27. Research Question 2 How to effectively visualise the captured provenance to address the scalability and the complexitychallenges in visualising analytic provenance? • Challenges • Scalability: a high number of interactions • Complexity: non-linear process • Existing research • Horizontal-vertical tree layout • Collapsible trees • Zoom-able and pan-able interface UTILISE CAPTURE VISUALISE

  28. Research Question 2 - Proposal Task search “A” search “B” merge results “A” and “B” Sub-Tasks • A multi-semantic-level approach • Maps with the four-tier characteristic of visual analytic activities • Supports switching between different levels of semantics • Editable nodes and modifiable tree structure Actions “A” “A” + “B” Events “B” • A heuristic to automatically reorganise user interactions to reflect the user’s logic

  29. Research Question 3 How to build an analytical product that can address the auditability and context-sensitivity challenges in presentation? • Challenges • Auditability: information of source data and analysis process • Context-sensitivity: different forms for different presentation needs • Existing research • Partially auditable: annotate, embed into a story • Not context-sensitive UTILISE CAPTURE VISUALISE

  30. Research Question 3 - Proposal • A multi-provenance-level presentation model PROVENANCE of MODEL 3 TRANSFORMATION / MAPPING INSIGHT DATA DATA COLLECTION INSIGHT SYNTHESISER CONCLUSION MODEL 1 PROVENANCE of DATA PROVENANCE of CONCLUSION DATA INSIGHT VISUALISATION / INTERACTION 4 2 PROVENANCE of VISUALISATION 3

  31. Agenda • Literature Review • Research Questions • Plan

  32. Plan

  33. InfoVis Paper K. Xu, C. Rooney, P. Passmore, D.-H. Ham, and P. H. Nguyen, “A User Study on Curved Edges in Graph Visualization,” IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 12, pp. 2449–2456, Dec. 2012.

  34. VAST Challenge Award S. Choudhury, N. Kodagoda, P. Nguyen, C. Rooney, S. Attfield, K. Xu, Y. Zheng, B. L. W. Wong, R. Chen, G. Mapp, L. Slabbert, M. Aiash, and A. Lasebae, “M-Sieve: A Visualisation Tool for Supporting Network Security Analysts,” in IEEE VAST Challenge, 2012, pp. 165–166.

  35. Questions & Answers

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