Understanding and supporting users in visual network exploration
dc.contributor.advisor
Bach, Benjamin
dc.contributor.advisor
Hinrichs, Uta
dc.contributor.advisor
Gasevic, Dragan
dc.contributor.author
AlKadi, Mashael Hamad
dc.date.accessioned
2024-09-19T09:55:12Z
dc.date.available
2024-09-19T09:55:12Z
dc.date.issued
2024-09-19
dc.description.abstract
Network visualization tools are used in numerous domains to explore data. Various network visualizations have been designed to explore data from different perspectives. However, few resources investigate how analysts create and interact with the visualizations to explore networks in the wild. By analysts, we denote users varying in their background and level of expertise. Being in the wild signifies that analysts work outside controlled settings where no pre-designed tasks are set. This thesis focuses on studying how to understand and support analysts in the process of network visual exploration. In such a process, analysts need to learn about the concepts, the tool(s), the processes, the visualization(s) and interactions, and the workflow. They also need to ensure that they can apply what they have learned accumulatively on their data toward their goal(s). Thus, to understand and support analysts, we have applied and collected data through mixed methods: interaction logging, mini-questionnaire, and visualization's state annotation, running an intensive 6-week course, designing an analytical dashboard, and implementing a coaching program. We ran our studies using the Vistorian a web-based tool that offers 4 types of interactive network visualizations.
This multimethod research led to the following contributions. Interaction logging allowed identifying 4 types of users based on their tool usage and advancement in the visual exploration process: demo users, data strugglers, single-session and multi-session explorers. To examine user types further, we designed a utility to capture and annotate visualizations' states, which we call bookmarks. We identified eight barriers that might cause analysts to struggle through the visual exploration process. We designed an analytical dashboard by specifying Key Performance Indicators (KPIs) and analyzing interaction logs accordingly. Those KPIs informed the assessment of the tool, the visualizations, the help resources, and the users' exploration. To support analysts, we designed a self-regulated guide for network visual exploration, which we call a roadmap. The roadmap describes step-by-step the processes of network visual exploration and associated activities. We also described 16 exploration strategies analysts follow, classified into three categories. We found 4 distinguished analyst groups based on how they aim to explore whether with/without research goals and/or data, which we call roadmap pathways. We evaluated the roadmap through a coaching program and found that it plays a crucial role in teaching networks visual exploration. Those findings have implications for the network's visual exploration through enhancing the design of its tools and associated educational efforts, mitigating barriers within, and supporting various user types.
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dc.identifier.uri
https://hdl.handle.net/1842/42195
dc.identifier.uri
http://dx.doi.org/10.7488/era/4916
dc.language.iso
en
en
dc.publisher
The University of Edinburgh
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dc.relation.hasversion
Jinrui Wang, Mashael AlKadi, and Benjamin Bach (VIS 2023) ”Show Me My Users: A Dashboard Visualizing User Interaction Logs”, IEEE Transactions on Visualization and Computer Graphics
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dc.relation.hasversion
Mashael AlKadi, Vanessa Serrano, James Scott-Brown, Catherine Plaisant, Jean-Daniel Fekete, Uta Hinrichs, and Benjamin Bach (VIS 2022) ”Understanding Barriers to Network Exploration with Visualization: A Report from the Trenches”, IEEE Transactions on Visualization and Computer Graphics, vol 20, 907-917
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dc.relation.hasversion
Mashael AlKadi, Magdalena Boucher, Wolfgang Aigner, Uta Hinrichs, and Benjamin Bach ”Roadmaps, Pathways, and Activities: Helping Analysts Understand, Plan, and Personalize their Visual Network Exploration”, IEEE Transactions on Visualization and Computer Graphics (Under Submission)
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dc.relation.hasversion
Magdalena Boucher, Mashael AlKadi, Benjamin Bach, and Wolfgang Aigner “Exploring Instructional Comics for Data Visualization Education”, IEEE Transactions on Visualization and Computer Graphics (Under Submission)
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dc.relation.hasversion
B. Bach, M. AlKadi, J.-D. Fekete, C. Plaisant, V. Serrano, N. H. Riche, and N. Dufournaud. The vistorian. https://vistorian.github.io/. Accessed on July, 1st, 2022
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dc.relation.hasversion
B. Bach, M. AlKadi, U. Hinrichs, and J. Scott-Brown. Free 6-Weeks Online Course on Interactive Visual Network Exploration. https://vistorian.github.io/courses. html. Accessed on July, 1st, 2022
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dc.relation.hasversion
B. Bach, M. AlKadi, U. Hinrichs, and J. Scott-Brown. Vistorian Data Formats Course. https://vistorian.github.io/formattingdata.html. Accessed on July, 1st, 2022
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dc.relation.hasversion
B. Bach, M. Keck, F. Rajabiyazdi, T. Losev, I. Meirelles, J. Dykes, R. S. Laramee, M. AlKadi, C. Stoiber, S. Huron, C. Perin, L. Morais, W. Aigner, D. Kosminsky, M. Boucher, S. Knudsen, A. Manataki, J. Aerts, U. Hinrichs, J. C. Roberts, and S. Carpendale. Challenges and Opportunities in Data Visualization Education: A Call to Action. In IEEE TVCG, Proc VIS 2023. IEEE, 2024
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dc.subject
visual exploration
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dc.subject
network visualizations
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dc.subject
network visual exploration roadmap
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dc.title
Understanding and supporting users in visual network exploration
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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