Designing Visual Decision Making Support with the Help of Eye Tracking

Data visualizations are helpful tools to cognitively access large amounts of data and make complex relationships in data understandable. This paper shows how results from neuro-physiological measurements, more specically eye-tracking, can support justied design decisions about improving existing data visualizations for exploring process execution data. This is achieved by gaining insight into how visualizations are used for decision-making. The presented examination is embedded in the domain of process modeling behavior analysis, and the analyses are performed on the background of representative analytical questions from the domain of process model behavior analysis. We present initial ndings on one out of three visualization types we have examined, which is the Rhythm-Eye visualization.

More info: https://andrea.burattin.net/publications/2017-bpmds

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1. Designing Visual Decision Making Support with the Help of Eye Tracking Barbara Weber1,2, Jens Gulden3, Andrea Burattin1 1 University of Innsbruck, Austria 2 Technical University of Denmark, Denmark 3 University of Duisburg-Essen, Germany This research is supported by Austrian Science Fund (FWF): P26609.
2. Table of contents • Preliminaries • What is the process of process modeling (PPM) • What is rhythm-eye visualization • How to apply rhythm-eye visualizations to PPM • Assessment of the effectiveness of such application • Conclusions and future work Designing Visual Decision Making Support with the Help of Eye Tracking 2
3. Process of Process Modeling • In this work we focus on data generated from the interactions with a process modeling tool • The creation of a process model is performed in steps • We used the Cheetah Experimental Platform • Tool to model a process model • Records all model interactions • Allows replaying the process modeling step-by-step Designing Visual Decision Making Support with the Help of Eye Tracking 3 … Cheetah Experimental Platform (CEP) Traditional Research: Resulting Process Model
4. Modeling Phase Diagram (MPD) • A typical modeling session is characterized by the repetition of three phases • Modeling: creation of the actual mode • Reconciliation: enhancement of the model (moving or renaming nodes and edges) • Comprehension: identification of requirements (no interaction) Designing Visual Decision Making Support with the Help of Eye Tracking 4
5. Modeling Phase Diagram (MPD) • A typical modeling session is characterized by the repetition of three phases • Modeling: creation of the actual mode • Reconciliation: enhancement of the model (moving or renaming nodes and edges) • Comprehension: identification of requirements (no interaction) • Analysis of the interactions to create the modeling phase diagram Designing Visual Decision Making Support with the Help of Eye Tracking 4 Example 2 Example 1 0 10 20 30 40 50 60 70 0 500 1000 1500 2000 2500 3000 Number of Elements Time [s] COMPREHENSION MODELING RECONCILIATION
6. The Rhythm-Eye Visualization • Visualization alternative to timeline projections (piano rolls) • Features of rhythm-eye visualizations • Circular structure, based on the “clock metaphor” • Markers can indicate events or time frame • Always relative time Designing Visual Decision Making Support with the Help of Eye Tracking 5
7. The Rhythm-Eye Visualization • Visualization alternative to timeline projections (piano rolls) • Features of rhythm-eye visualizations • Circular structure, based on the “clock metaphor” • Markers can indicate events or time frame • Always relative time • Main advantages wrt typical linear projections • Provides immediate overview of the activities via peripheral vision • Easy to “nest” several circles Designing Visual Decision Making Support with the Help of Eye Tracking 5
8. The Rhythm-Eye Visualization • Visualization alternative to timeline projections (piano rolls) • Features of rhythm-eye visualizations • Circular structure, based on the “clock metaphor” • Markers can indicate events or time frame • Always relative time • Main advantages wrt typical linear projections • Provides immediate overview of the activities via peripheral vision • Easy to “nest” several circles Designing Visual Decision Making Support with the Help of Eye Tracking 5
9. Rhythm-eye visualization for PPM data • We used rhythm-eye visualization to display PPM data (instead of Modeling Phase Diagram) Designing Visual Decision Making Support with the Help of Eye Tracking 6
10. Rhythm-eye visualization for PPM data • We used rhythm-eye visualization to display PPM data (instead of Modeling Phase Diagram) Designing Visual Decision Making Support with the Help of Eye Tracking 6 “Configuration 1”
11. Rhythm-eye visualization for PPM data • We used rhythm-eye visualization to display PPM data (instead of Modeling Phase Diagram) Designing Visual Decision Making Support with the Help of Eye Tracking 6 “Configuration 2” “Configuration 1”
12. Inter/intra-subjects visualizations • The same visualization can be used to plot inter-subjects PPMs Designing Visual Decision Making Support with the Help of Eye Tracking 7 Reconciliation phases Comprehension phases
13. Effectiveness of rhythm-eye via pilot study and eye-tracking • Analytical Questions • Q1 Is there a long reconciliation phase at the end of the process? • Q2 Is the modeling done in rather short or large chunks throughout the process? • Q3 Is the comprehension behavior of the subject changing over time? Designing Visual Decision Making Support with the Help of Eye Tracking 8
14. Effectiveness of rhythm-eye via pilot study and eye-tracking • Analytical Questions • Q1 Is there a long reconciliation phase at the end of the process? • Q2 Is the modeling done in rather short or large chunks throughout the process? • Q3 Is the comprehension behavior of the subject changing over time? • We asked our subjects to answer the questions in front of an eye-tracker Designing Visual Decision Making Support with the Help of Eye Tracking 8
15. Effectiveness of rhythm-eye via pilot study and eye-tracking • Analytical Questions • Q1 Is there a long reconciliation phase at the end of the process? • Q2 Is the modeling done in rather short or large chunks throughout the process? • Q3 Is the comprehension behavior of the subject changing over time? • We asked our subjects to answer the questions in front of an eye-tracker • Stimuli • For each analytical question, we presented 6 visualizations • Each visualization refers to 1 modeling session • 3 for “Configuration 1” + 3 for “Configuration 2” • In total 18 measurements per subject Designing Visual Decision Making Support with the Help of Eye Tracking 8
16. Effectiveness of rhythm-eye via pilot study and eye-tracking • Analytical Questions • Q1 Is there a long reconciliation phase at the end of the process? • Q2 Is the modeling done in rather short or large chunks throughout the process? • Q3 Is the comprehension behavior of the subject changing over time? • We asked our subjects to answer the questions in front of an eye-tracker • Stimuli • For each analytical question, we presented 6 visualizations • Each visualization refers to 1 modeling session • 3 for “Configuration 1” + 3 for “Configuration 2” • In total 18 measurements per subject • Subjects of the pilot study • 2 DTU master students • Familiar with process modeling and instructed about modeling phases Designing Visual Decision Making Support with the Help of Eye Tracking 8
17. Initial findings • RQ1: Does the Rhythm-Eye visualization support to focus the user’s attention on the parts of the visualization that are relevant for answering the questions? Designing Visual Decision Making Support with the Help of Eye Tracking 9
18. Initial findings • RQ1: Does the Rhythm-Eye visualization support to focus the user’s attention on the parts of the visualization that are relevant for answering the questions? • We collected fixation data and then created heatmaps showing the distribution of fixations of both participants in integrated manner Designing Visual Decision Making Support with the Help of Eye Tracking 9
19. Initial findings • RQ1: Does the Rhythm-Eye visualization support to focus the user’s attention on the parts of the visualization that are relevant for answering the questions? • We collected fixation data and then created heatmaps showing the distribution of fixations of both participants in integrated manner Designing Visual Decision Making Support with the Help of Eye Tracking 9 Sum fixations answering Q1 Sum fixations answering Q2 Sum fixations answering Q3
20. Initial findings • RQ1: Does the Rhythm-Eye visualization support to focus the user’s attention on the parts of the visualization that are relevant for answering the questions? • We collected fixation data and then created heatmaps showing the distribution of fixations of both participants in integrated manner • Conclusion: visualizations seem to be effective (similar results for both configurations) Designing Visual Decision Making Support with the Help of Eye Tracking 9 Sum fixations answering Q1 Sum fixations answering Q2 Sum fixations answering Q3
21. Initial findings (cont.) • RQ2: Does configuration 2 provide better initial orientation for their user in finding the starting point when compared to configuration 1? Designing Visual Decision Making Support with the Help of Eye Tracking 10
22. Initial findings (cont.) • RQ2: Does configuration 2 provide better initial orientation for their user in finding the starting point when compared to configuration 1? Designing Visual Decision Making Support with the Help of Eye Tracking 10 “Configuration 1” “Configuration 2”
23. Initial findings (cont.) • RQ2: Does configuration 2 provide better initial orientation for their user in finding the starting point when compared to configuration 1? • Conclusion: configuration 2 better guides the understanding of the visualization wrt its reading direction (similar results for all questions) Designing Visual Decision Making Support with the Help of Eye Tracking 10 “Configuration 1” “Configuration 2”
24. Conclusions and future work • Presented a novel way of presenting PPM information using rhythm-eyes • We analyzed the effectiveness of the rhythm-eyes for process modeling behavior analysis • Rhythm-eyes are indeed effective • Different configurations of rhythm-eyes serve to different purposes Designing Visual Decision Making Support with the Help of Eye Tracking 11
25. Conclusions and future work • Presented a novel way of presenting PPM information using rhythm-eyes • We analyzed the effectiveness of the rhythm-eyes for process modeling behavior analysis • Rhythm-eyes are indeed effective • Different configurations of rhythm-eyes serve to different purposes • Future work • Perform an actual experiment (not just a pilot study, as presented here) • Compare the effectiveness of rhythm-eye views with other representation, such as Modeling Phase Diagrams • Investigate several typical business-related questions • Consider settings where interactions among phase types are needed Designing Visual Decision Making Support with the Help of Eye Tracking 11