PhD Thesis: Collaborative Information Visualization in Co-located Environments
I will add some images of thesis projects here when I have time...
Information visualization research has been developing new methods to represent data and interact with graphical displays of information for more than two decades. In many disciplines, however, the size and complexity of datasets are rapidly growing. As a consequence, it is becoming increasingly necessary to join the domain expertise and data analysis skills of several people to inform decisions about the content of a dataset. While the technological possibilities for supporting teamwork are gradually evolving, several obstacles remain for designing information visualizations that can support team members as they collaboratively explore and analyze information. In this dissertation, I examine this problem by identifying and addressing some of the open issues in the design of information visualizations that support small teams of experts in their joint data analysis activities.
Within the general area of collaborative visualization, this research is scoped to focus on a subset of collaborative visualization scenarios that occur in co-located synchronous work environments; where small groups of collaborators share the same physical workspace such as a large digital table or wall display. Specifically, it contributes to a richer understanding of how groups work with each other and with information visualizations in phases of joint and parallel work.
In this dissertation, I show that team members tend to prefer working in parallel on specific types of information analysis tasks and more closely together on others. During phases of parallel work, individual team members take on unique approaches to data analysis. Thus, for the design of collaborative analysis systems, the support of unique analysis approaches and a flexible temporal flow of activities---both in the temporal sequence and co-occurrence of work styles in groups---need to be considered. In addition, the three case studies presented in this dissertation examine possibilities of how this flexibility can be supported. These case studies shed light on issues of parallel and joint work with multiple views in a collaborative system, parallel and joint work with a single shared visualization, as well as awareness support during parallel work. In summary, this dissertation contributes to the evolving understanding of collaborative work practices around information visualizations and introduces several specific design considerations.
- Dr. Sheelagh Carpendale (Supervisor, University of Calgary)
- Dr. Saul Greenberg (University of Calgary)
- Dr. Amy Ashurst Gooch (University of Victoria)
- Dr. Patrick Shiao Tsong Feng (University of Calgary)
- Dr. Colin Ware (University of New Hampshire)
Chapter 1: Introduction
This chapter explains the scope, context, goals, methodological approaches, and contributions of the work. It also gives a definition for collaborative information visualization.
Chapter 2: Research Background
This chapter forms the first part of a literature review on collaborative information visualization. I give an overview of previous collaborative visualization systems for co-located work, including a systematic review of systems featured in the IEEE Vis/InfoVis/ Vast conferences. I highlight their main features and point to open research questions and extensions of this work.
Chapter 3: A First Set of Design Considerations for Collaborative Information Visualization
This chapter forms the second part of my literature review and is part of my first research phase. I discuss work from information visualization design, co-located collaboration, and studies that look directly at collaborative visualization. I examine research from these areas in relation to this dissertation work and derive initial design considerations for the design of co-located collaborative information visualizations systems.
Chapter 4: Collaborative Visual Information Analysis Processes
As part of the first phase of my research, I report on an exploratory study of individuals, pairs, and triples engaged in information analysis tasks using paper-based visualizations. From the study results, eight specific analysis processes are derived that capture the analysis activities of co-located teams and individuals. Comparing these with existing models of the information analysis process suggests that information visualization tools may benefit from providing a flexible temporal flow of analysis actions and that collaborative information visualization systems should support people in fluidly switching between different types of analysis processes. These findings extend the initial design considerations derived in Chapter 3.
Chapter 5: CoTree-A System For Collaborative Tree Comparison
With this chapter I begin the second phase of my research. This second phase contains three new collaborative information visualization systems. Here in this chapter, I present the first of these three new collaborative systems for co-located data analysis, CoTree. It is based on the considerations derived from work in the two previous chapters. In CoTree, I focused on first providing ways to enable parallel work processes and then included more subtle workspace-based mechanisms for team members to switch to more joint work styles. The system was designed to support hierarchical data comparison tasks for co-located collaborative work. It supports dual-touch input, shared and individual views on the hierarchical data visualization, flexible use of representations, and flexible workspace organization. I discuss this initial design and point to further research questions arising from this prototype.
Chapter 6: CoCoNutTrix: Collaborative Retrofitting for Information Visualization
In this chapter, I present a tool and subsequent study in which I explored how a co-located collaborative information visualization and analysis environment can be retrofit from a pre-existing system design for use by a single analyst. This design takes an orthogonal approach to the one used in Chapter 5. I start from a system designed to support only sequential close work and looked at minimal changes necessary to introduce possibilities for parallel work. These changes were based on the results from my previous work and the design considerations developed in Chapter 3. NodeTrix, a social network analysis tool for individual use, was extended to enable parallel interaction in collaborative environments. Details of the retrofitting process and results of a study show the usability of the retrofitted system. The results support the effectiveness of the low-cost collaborative retrofitting for collaborative network analysis and highlight implications for practitioners.
Chapter 7: Cambiera: Collaborative Visual Analytics
In this chapter, I present the design of a tabletop visual analytics tool, Cambiera. Cambiera, supports individual and collaborative information foraging activities in large text document collections. With the design of this system, I take an approach that includes ideas from both Chapters 5 and 6. Similar to CoTree (Chapter 5), I propose a new design specifically tailored towards parallel work but introduce mechanisms to allow people to be more closely aware of each others' activities, a suggestion that came out of the study in Chapter 6. The design of this system focused specifically on the question of how individual and joint analysis activities could be supported with meta-visualizations. `Collaborative brushing and linking' is defined as an awareness mechanism that enables analysts to follow their own hypotheses during collaborative sessions while still remaining aware of the group's activities. With Cambiera, team members are able to collaboratively search through documents, maintaining awareness of each others' work and building on each others' findings.
Chapter 8: In the conclusions, I summarize the research objectives and contributions of this thesis and shed light on future issues in co-located collaborative information visualization.
The thesis itself:
|Petra Isenberg (2009) Collaborative Information Visualization in Co-located Environments. PhD Thesis, University of Calgary, Calgary, AB, Canada, December 2009.|
Publications as part of the thesis and the chapters which contain parts of these publications:
|Petra Isenberg (2007) Information Visualization in Co-located Collaborative Environments. In Proceedings of the Grace Hopper Celebration of Women in Computing, PhD Forum. 2007.|
|Petra Isenberg, Uta Hinrichs, Mark Hancock, and Sheelagh Carpendale (2010) Digital Tables for Collaborative Information Exploration. In Christian Mueller-Tomfelde (ed.): Tabletops—Horizontal Interactive Displays, pages 387–406. Springer Verlag, 2010.|
As must be expected some errors have crept into the thesis. I will list them here as I uncover them:
- Page 165: First column. Group 1(5th last row) should be 10 and Group 10(last row) should be Group 1.
- Page 166: Same error as page 165 but also the picture displayed for both groups is the one for Group 1. The picture for Group 10 is missing but can be found in a later publications. The errors have also been corrected there (link to follow)
- Page 167: It should be "Both participants (in Group 2) worked closely coupled for 90% of the time"