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GEOVISUALIZATION AND EPIDEMIOLOGY A GENERAL DESIGN FRAMEWORK

GEOVISUALIZATION AND EPIDEMIOLOGY A GENERAL DESIGN FRAMEWORK
GEOVISUALIZATION AND EPIDEMIOLOGY A GENERAL DESIGN FRAMEWORK

GEOVISUALIZATION AND EPIDEMIOLOGY: A

GENERAL DESIGN FRAMEWORK

Anthony C. Robinson

GeoVISTA Center, Department of Geography, The Pennsylvania State University

This paper describes the creation of a general design framework for a geovisualization toolkit to support epidemiological work. The framework is based on the iterative, user-centered design and development of ESTAT, the exploratory spatio-temporal analysis toolkit. Specifically, this framework is informed by a series of knowledge elicitation and tool assessment sessions with practicing epidemiologists from the National Cancer Institute and the Penn State Hershey Medical School. Users have provided input through focus groups, verbal protocol analysis sessions, and collaboration through an in-depth case study. The framework presented provides a general structure by which evaluation activities can be organized so that all aspects of geovisualization use can be addressed. The general aspects of the framework are also potentially applicable to the user-centered design and development of other geographic analysis methods and tools. INTRODUCTION

Geovisualization tools are born from a desire to build maps that people can interact with and explore in a real-time, dynamic manner. As analysts are faced with ever-increasing amounts of spatial data, we need to provide maps and other visualizations that facilitate exploration. This is a crucial challenge facing designers and developers of geovisualization tools, and it is a major motivation for the research reported here. At the same time, it is important to facilitate exploration for a reason – to create tools that reflect the specific needs of a particular audience.

To address these two concerns, I have focused attention on evaluating and exploring use of a geovisualization toolkit designed for epidemiologists. The Exploratory Spatio-Temporal Analysis Toolkit (ESTAT) is designed to provide cancer researchers with visual tools to explore multivariate spatio-temporal data. ESTAT features four display forms (Figure 1); a scatterplot, bivariate mapping tool, parallel coordinate plot (PCP), and time series graph. These tools are dynamically linked, so that mouse movements cause corresponding observations to highlight in each display, and selections can be made in one tool so that it can be studied in the others. The ESTAT application is based on the open-source GeoVISTA Studio platform (Takatsuka and Gahegan 2002), a Java-based visual programming environment designed to support the construction of geovisualization toolkits.

The scatter plot (reviewed recently by Gahegan 1998) and bivariate map (Eyton 1984; Olson 1981) are common methods for geovisualization that have a long history in cartography and information visualization. The PCP and its cousin, the time series plot, are also common methods of information visualization, though ESTAT presents a unique combination of these tools in a unified application. The PCP is a method for visualizing many variables at once. In a PCP, each observation is drawn as a string passing through parallel axes, which represent data categories (Inselberg 1985). ESTAT handles temporal data through its time series graph. This graph is a customized x-y graph designed to display a particular variable across time. ESTAT’s internal linkages allow users to explore temporal data and see how they relate to other variables in the map, scatterplot, and PCP.

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Figure 1: The ESTAT Geovisualization Toolkit. The top left quadrant is the bivariate scatterplot. At bottom left is a bivariate map tool. The top right shows a time series graph, and at bottom right is the parallel coordinate plot. This capture shows colon cancer incidence rates and associated socioeconomic variables.

PURPOSE

Many authors have outlined the potential utility of geovisual methods for exploratory tasks in health research. This potential prompts a focus on how multiple tools can be combined effectively. It is not enough to craft innovative individual methods – they must be incorporated together in a manner that enables experts to easily adopt these new approaches into their daily workflow. This ‘recipe’ is the heart of the research reported here. The primary ‘ingredients’ for this recipe include answers to the following fundamental questions:

1.What are the features and interactions necessary for geovisualization tools that support exploratory

health analysis?

2.What are the features and interactions necessary for geovisualization applications (sets of

integrated tools) that support exploratory health analysis?

3.How are geovisualization tools situated in epidemiological work today?

This paper focuses on assessing the use and usability of the ESTAT toolkit in order to develop a general design framework that addresses these questions among a wide array of related concerns. This design framework outlines the key areas of consideration for the development of a geovisualization toolkit tailored for the exploratory tasks of epidemiology. These elements will then serve as building blocks for the next generation of geovisual evaluation activities.

The purpose of this work is twofold: First, its results will impact the development of tools to support spatial epidemiology. The epidemiologists who participated in this research will receive an improved version of ESTAT based on their input. Second, the lessons learned from evaluating ESTAT will provide deeper insight into an effective user-centered design methodology for developing geovisualization tools. These insights will help geographers build interactive tools that have a real-world purpose from their inception – rather than ‘tacking-on’ an application after everything has been designed and built. BACKGROUND

User issues and interface design are common themes in current geovisualization research. Enabling the efficient and intuitive usage of geovisual representations as interfaces to data remains a crucial challenge to developers of these tools. It is not enough to provide a visual method alone – rather we must develop design principles and evaluation techniques such that geovisualization becomes accessible to users whose expertise exists outside the realm of GIScience. This research addresses challenges related to interfaces and cognitive/usability evaluation outlined by MacEachren and Kraak (2001), particularly their call, “…to develop a comprehensive user-centered design approach to geovisualization usability.”

The assessment approach reported here is motivated by a number of recent evaluation efforts in geovisualization research (Andrienko et al. 2002; Edsall 2003; Haklay and Tobon 2003; Montello et al. 2003; Slocum et al. 2003; Suchan 2002), and many of the methods described herein are inspired by aspects of this body of work. An essential aspect of nearly all of these studies is a reliance on multiple convergent methods. Work by MacEachren et al. (1998) is a early example of convergent methods in geovisualization usability research, and the research reported here relies on a broad range of convergent techniques.

User-Centered Design

The central theme that drives this research is a desire to fit geovisualization tools more precisely to the users that (may) need them. The efforts to assess ESTAT that are reported herein are part of a design process (Figure 2) that incorporates end-users in each stage. User input and knowledge about their work domain are built into this process in a variety of ways.

Figure 2: The user-centered design process.

The first stage, work domain analysis, is characterized by communication of ideas and requirements between the client (in this case, NCI) and developers (GeoVISTA) as well as research on the development side into the work of epidemiology. Conceptual development refers to the complete plan of features that is the result of work domain analysis. During this stage, layouts, tools, and the architecture are discussed and graphical concept prototypes are created. This stage iterates through multiple designs, and each benefits from stakeholder feedback. After conceptual development, prototyping begins. In this stage, initial working versions of the application are created. Next, Interaction/usability assessment activities are developed and executed. These are crucial to understanding the pieces of an application that work well, as well as those

that need further re-design. Implementation follows assessment activities, and typically results in additional design suggestions. The final stage is debugging. In this portion of the process the application is adjusted to enhance stability, compatibility, and performance.

This paper focuses on the interaction and usability assessment stage. Assessments are valuable because they often uncover features that need to be added or scenarios in which tools might be employed for which they were not originally designed. In this paper, the term ‘assessment’ refers to formal and informal evaluation of both the usability of tools as well as the interactions that they enable. Formal assessments may take place in a laboratory where audio and video is captured while users work with an application. They may also include interviews and focus groups to solicit reactions to the application. Informal assessment occurs as end-users try prototypes and provide comments, questions, and ideas. Informal assessment activities can also occur on the development side as the application is internally critiqued. Formal and informal methods have been used during the design of ESTAT.

Assessment Methods

Four approaches to tool assessment have been used to assess ESTAT, including; card sorting, verbal protocol analysis, focus groups, and ethnographic case studies. These methods were chosen in order to elicit a diverse range of user input. Combining methods such as these can reveal much about the complicated nature of toolkit usage from the individual interface features all the way up to the situation in which toolkits will be applied in the real work environment.

Card sorting (Nielsen 1993) is a simple method for assessing the structure of an interface. Users are given 3 x 5 note cards labeled with individual functions, which they arrange in categories according to their preferences.

Verbal protocol analysis (VPA) captures user experiences during work as they ‘think aloud’ (Ericsson and Simon 1993). It is valuable for understanding the critical needs of an application as well as the expectations a user may have. Typically, users are given a task to achieve using an application, and they are encouraged to verbalize their thought processes as they work. The VPA techniques used in this research were augmented with video captures of user interaction. Video is an important source of information for coding VPA results during software use, as mouse gestures and other actions are not typically verbalized by users. For this research, I relied on simple observation of task performance as I transcribed each participant’s verbal reports. This kind of video analysis uses video as an indirect representation; to provide clarification to other forms of analysis (McNeese 2004).

Focus groups (Morgan et al. 1998) solicit ideas and feedback through group discussions. They are moderated by a discussion leader who asks questions and prompts for elaboration as described in advance by those who are sponsoring the session. I used focus groups to capture experiences with ESTAT and as a forum for issues that situate the potential usefulness of geovisualizations for epidemiology. Ethnographic case studies combine a real-world application of methods with participant-observation practices (Yin 1994). Case studies are often undertaken as proof-of-concept exercises to demonstrate the utility of a particular tool or method. Ethnographic case studies are different in the sense that they are undertaken not only to evaluate tool utility, but also so that researchers may observe how work takes place around these tools. Data from such studies are usually collected ad hoc, in notes, through informal and formal communication with subjects, and from direct observation. While ethnographic case studies require a significant time commitment they typically provide deep knowledge of the situated work experience. The Assessment Process

Since October of 2003, a number of assessments have focused on evaluating ESTAT. Initially we focused on rapid prototyping and quick assessments using GIScience students. This was followed by task analysis sessions and focus groups with actual end-users at NCI in February of 2004. After these activities, a long-term case study collaboration with an epidemiologist took place. Each of these evaluations provided

valuable input into the continued design of the ESTAT toolkit. The details of these activities and their results have been presented elsewhere (Robinson et al. 2005).

In December of 2004, task analysis and focus group sessions took place at NCI headquarters, in their state-of-the-art User Centered Informatics Research Lab. The VPA technique was applied with five epidemiologists using ESTAT to accomplish two epidemiological tasks. Following VPA sessions, users were asked to discuss their experiences with ESTAT in a focus group. During both of these activities video logs were captured showing the user’s screen as well as an inset of their upper body.

Transcriptions of these videos were created, and subsequently coded for analysis. A detailed report on the content and results of this evaluation activity is forthcoming (Robinson, In Progress) A sample coded transcript, as well as task analysis and focus group questions are available at

https://www.doczj.com/doc/6d12305211.html,/acr181/appendices.doc .

A GENERAL DESIGN FRAMEWORK

The results of ESTAT evaluation activities have unveiled a general approach to toolkit design and development. This general design framework provides a structure for evaluations to follow. The framework uses an increasingly large scale (in the vernacular definition) to describe its critical elements. At the smallest scale, evaluations must focus on individual tools. Next, the applications, that wrap together and coordinate individual tools, should be evaluated. Moving further upward, the framework calls for evaluations to examine geovisual analysis strategies. Finally, at the largest scale, evaluations must consider the range of externalities that impact the situation in which a geovisualization toolkit is (or will be) utilized. The following sections describe a selected set of preliminary details about each of these key areas of consideration (a more comprehensive analysis is in preparation (Robinson, In Progress).

Individual Tools

At the smallest scale, individual tools require close attention to interface details and interactivity. ESTAT evaluations have shown that every icon and button must be carefully scrutinized for clarity in purpose and usage. Users expect rollover descriptions to make sense immediately, and for help files to be available on demand to explain complicated procedures.

Linked brushing and selection are commonly available in geovisualization tools. In ESTAT, the fact that the interface is very nearly “alive” was the most novel feature to those who helped evaluate the toolkit. While many users were able to immediately understand how to take advantage of this interactivity, the lack of explicit methods to undo changes and return to default setups made it difficult to conduct a thorough exploration of the data available. While it remains a major challenge to program an undo method to capture everything a user does in a linked and coordinated environment like ESTAT, even adding a simple undo method that would allow control over the most recent actions in addition to a reset method to restore defaults would provide users sufficient means to iteratively explore and analyze. This is most appropriately addressed at the individual tool level because each visualization tool has its own unique way of visually communicating brushing events and selections.

Feedback from our users has shown that our desire to provide as much control as possible over the look and feel of the user interface should not obscure the most commonly used features. Moreover, the initial setup should look as ‘standard’ as is reasonable. This was particularly the case with our time series graph, which was initially very similar in look and feel to our parallel coordinate plot, and therefore caused a great deal of confusion as some users thought there were two PCP’s, or they were unsure as to which was displaying temporal data and which was not. We conducted a quick survey of the common representation methods for time series graphs and retooled the interface accordingly (Figure 3). Initial response to the changes by our colleagues at NCI has been positive.

Figure 4: The old time series graph is shown above the new design. The old design drew heavily upon the PCP tool, and therefore appeared visually similar. The new design features a layout drawn from a survey of existing tools that create time series graphs. In the new design, the time scale and variable information are emphasized.

Applications

Moving ahead, evaluation activities need to focus attention on the composition of applications. Devising the proper combination of individual tools together into a unified and efficient whole is a non-trivial problem. Strong internal linkages were needed in order to coordinate every view in precisely the same manner. As an example, metadata descriptions were made available in the PCP, time series graph, and data loader. These were all tools that the lead developer on ESTAT had created himself. The map and scatterplot were originally Java beans developed by other members of the GeoVISTA Center. Users were not able to reconcile the fact that metadata appeared to be available only in some tools, and not all of them. Subsequently, we have adopted a more proactive stance on issues of consistency like this. Additionally, users often mentioned the need for specific external linkages to other software tools they use during normal work. Most epidemiologists who worked with ESTAT use statistical analysis software (including SAS, S Plus, and R) to accomplish their daily work. One scenario that emerged often was that analysts wished to explore their data using ESTAT and then select a subset of variables to export out to one of these other statistical packages for rigorous analysis.

Geovisual Analysis

The work attempted with a geovisualization toolkit requires a close examination of the paths and processes involved with geovisual analysis. In the case of ESTAT, careful concern for eliciting the process of epidemiology in its current form was needed in order to imagine the ways in which ESTAT would augment that in a positive manner. Analysts are busy already – so designers and developers must pay close attention to what work is being attempted and in which ways new tools are going to benefit this situation.

ESTAT evaluations revealed that epidemiologists will often attempt confirmatory analysis before or as part of exploratory analysis. We originally designed ESTAT with exploratory tasks in mind, but in several instances analysts pointed out their desire to first confirm what they already knew with ESTAT to verify the visual reports with their existing domain knowledge.

Additionally, many epidemiologists wished to see a greater emphasis on statistical methods to augment geovisualization. General skepticism of purely visual reporting was alleviated to a large extent after initial re-design efforts added a number of summary statistics that provided additional numerical evidence. During case study collaboration, these supplemental statistics enabled our analysis of patterns of colon cancer in Pennsylvania, West Virginia, and Kentucky (Figure 4). In that instance, the epidemiologist wished to start using ESTAT by confirming it should show the same correlation values he had computed on his own using traditional means.

Figure 4: Using category median summary lines to look at state-to-state differences across socioeconomic indicators and colon cancer incidence in Appalachia. Here, the summary line for Pennsylvania has been highlighted in the PCP (the darkest purple line), and the map has updated to show only that subset. The map shows the rate of ascending colon cancer incidence versus access to doctors, the darkest counties showing high rates of cancer and high access to doctors.

Externalities

It is evident, after the long run of iterative user-centered design and evaluation activities, that there are a wide range of external factors that are important design considerations. It is often the case that as we approach research from the perspective of GIScience experts, we wish to control the offhand remarks and casual reactions of users to our tools, as they are not the specific focus of our evaluations. However, if we decide to listen closely and capture as much of what our users tell us as possible, trends often emerge. With ESTAT, I have noticed a great deal of interest in data issues. Users are excited about the tools I present them, and they are eager to imagine the ways in which they will make good use of them. The most common caveat they have, however, is that they assume there will be an inherent problem loading the data they use into our toolkit. A surprising number of epidemiologists I have worked with are aware of the trials and tribulations that commercial GIS tools present analysts when they try to import and merge data. The assumption then is that new tools must be based on this same technological structure and therefore will be

just as impossible to use for the non-GIS expert who has no time to learn about constructing spatial databases.

Additional externalities were mentioned by epidemiologists during the various ESTAT evaluation activities. In focus groups, users mentioned current debates within epidemiology regarding the validity of ecological studies. They also mentioned their concern that analysts outside of federal agencies would not have sufficient access to technical infrastructure and support in order to best take advantage of tools like ESTAT. Finally, a number of users discussed how new tools and methods were adopted by their colleagues, and revealed that without specific encouragement from their supervisors, they were reluctant to adopt any new approaches.

DISCUSSION

Prior work to evaluate geovisualization toolkits has often mentioned specific design elements or piecemeal recommendations as a result of evaluation activities. The general framework I propose here serves to clarify the relevant goals of future evaluation work with geovisualization toolkits. It is essential to address each of the major areas of the framework, from individual tools to externalities, in order to completely consider all of the critical elements required to make toolkits usable in and of themselves as well as useful in the daily work of an expert analyst.

By focusing on direct feedback from our users over the iterative process of design, ESTAT has evolved steadily into a usable and efficient toolkit for exploratory epidemiology. Colleagues in the GeoVISTA Center have enjoyed the quick and comprehensive feedback that ESTAT evaluations have generated, and as a result the entire design and development team now approaches work with an ingrained understanding that our tools must support real world work, done by real world users as much as they must demonstrate innovative methods and technology.

In the near future we will introduce the ESTAT toolkit in its refined form to a wider audience of epidemiologists at NCI. We are working on web-based feedback mechanisms for new users to take advantage of and inform us of their reactions to the tools as well as inevitable bugs and other problems that we will need to fix. A frequently updated build of the ESTAT toolkit is available via the web through the GeoVISTA Center at https://www.doczj.com/doc/6d12305211.html,/grants/nci-esda/tutorials.html. Sample data is also provided, in addition to a detailed user guide.

FUTURE WORK

The findings of this work are tailored to experiences with supporting cancer epidemiology amongst a number of users at a federal agency. While the details may differ, it is likely that the general framework proposed here will be transferable to other use contexts.

The next step is to apply the general design framework proposed in this paper to a new user-centered design situation. Then it can be critiqued for potential gaps in coverage and to assess whether or not it has sufficiently organized the evaluation process to render design and development more efficient than it was before. As cartographers continue to develop new, flexible geovisualization methods, further research is necessary in order to develop techniques to design and evaluate these new tools for real world applications.

ACKNOWLEDGEMENTS

This material is supported by the National Institutes of Health under grant #R01 CA95949-01. The development of ESTAT has been sponsored through a contract from the National Cancer Institute. Additionally, Linda Pickle at NCI has provided invaluable access to her fellow researchers for use as participants, without which none of this research would have been possible. Special thanks go to Jin Chen, the lead developer of the ESTAT toolkit. Finally, I wish to acknowledge the support of Alan MacEachren, who has inspired and guided much of this research.

REFERENCES

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Eyton, J. R. 1984. Complementary-color two-variable maps. Annals of the Association of American Geographers 74:477-90.

Gahegan, M. 1998. Scatterplots and scenes: Visualization techniques for exploratory spatial analysis.

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Inselberg, A. 1985. The plane with parallel coordinates. The Visual Computer 1:69-91.

MacEachren, A. M., F. Boscoe, D. Haug, and L. W. Pickle. 1998. Geographic visualization: Designing manipulable maps for exploring temporally varying georeferenced statistics. Proceedings of IEEE Information Visualization Symposium, Research Triangle Park, North Carolina, October 19-20. MacEachren, A. M., and M.-J. Kraak. 2001. Research challenges in geovisualization. Cartography and Geographic Information Science 28:3-12.

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Suchan, T. A. 2002. Usability studies of geovisualization software in the workplace. Proceedings of National Conference for Digital Government Research, Los Angeles, CA, May 19-22. Takatsuka, M., and M. Gahegan. 2002. GeoVISTA Studio: A codeless visual programming environment for geoscientific data analysis and visualization. Computers and Geosciences 28:1131-44.

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ABOUT THE AUTHOR

Anthony Robinson recently finished his M.S. degree in Geography at the Pennsylvania State University. His thesis research has focused on designing a geovisualization toolkit to support exploratory epidemiology for cancer researchers at the National Cancer Institute. Anthony has worked with dozens of users at NCI to evaluate ESTAT (Exploratory Spatio-Temporal Analysis Toolkit). In the fall of 2005, Anthony will begin his PhD studies with his advisor, Alan MacEachren, and he plans to continue working on user issues, design, and new cartographic techniques for medical geographic visualization.

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