Combining Usability Techniques to Design Geovisualization Tools for Epidemiology

Characterizing user needs for Beescape: A spatial decision support tool focused on pollinator health

Interactive maps can serve as powerful environmental decision-support tools. However, designing an interactive map that meets the needs of diverse constituencies is a challenge. In this article, we evaluate and characterize user needs for an interactive map and spatial decision-support tool called Beescape. Beescape is designed to visualize resources and environmental risks to bees and other pollinators (such as availability of nutritional resources from flowering plants and exposure to pesticides) in order to help users make informed decisions about managing bee populations and associated landscapes. We conducted a needs assessment workshop with twenty stakeholders from four user groups including beekeepers, growers, conservationists, and pollinator scientists to elicit their knowledge to guide future Beescape development. The results of the workshop identify current analytical gaps with the existing Beescape prototype, including the need for predictive and historical tools, more actionable data layers, finer-grain spatial data, and better explanations on what data represent and how they were created. Our findings on user's analytical, informational, and interface needs can be utilized to guide the future development of spatial decision support tools like Beescape, and our methodological approach may apply to other environmental informatics tools where it is important to design for multiple constituent user groups.

Introducing the Combined Atlas Framework for large‐scale web‐based data visualization – The GloNAF Atlas of Plant Invasion

Large‐scale biodiversity data, for example, on species distribution and richness information, are being mobilized and becoming available at an increasing rate. Interactive web applications like atlases have been developed to visualize available datasets and make them accessible to a wider audience. Web mapping tools are changing rapidly, and different underlying concepts have been developed to visualize datasets at a high cartographic standard.

Here, we introduce the Combined Atlas Framework for the development of interactive web atlases for ecological data visualization. We combine two existing approaches: the five stages of the user‐centred design approach for web mapping applications and the three U approach for interface success.

Subsequently, we illustrate the use of this framework by developing the Atlas of Plant Invasions based on the Global Naturalized Alien Flora (GloNAF) database. This case study illustrates how the newly developed Combined Atlas Framework with a user‐centred design philosophy can generate measurable success through communication with the target user group, iterative prototyping and competitive analysis of other existing web mapping approaches.

The framework is useful in creating an atlas that employs user feedback to determine usability and utility features within an interactive atlas system. Finally, this framework will enable a better‐informed development process of future visualization and dissemination of biodiversity data through web mapping applications and interactive atlases.

User Evaluation of Map-Based Visual Analytic Tools

Big data have also become a big challenge for cartographers, as the majority of big data may be localized. The use of visual analytics tools, as well as comprising interactive maps, stimulates inter-disciplinary actors to explore new ideas and decision-making methods. This paper deals with the evaluation of three map-based visual analytics tools by means of the eye-tracking method. The conceptual part of the paper begins with an analysis of the state-of-the-art and ends with the design of proof-of-concept experiments. The verification part consists of the design, composition, and realization of the conducted eye-tracking experiment, in which three map-based visual analytics tools were tested in terms of user-friendliness. A set of recommendations on GUI (graphical user interface) design and interactive functionality for map makers is formulated on the basis of the discovered errors and shortcomings in the assessed stimuli. The results of the verification were used as inputs for improving the three tested map-based visual analytics tools and might serve as a best practice for map-based visual analytics tools in general, as well as for improving the policy making cycle as elaborated by the European project PoliVisu (Policy Development based on Advanced Geospatial Data Analytics and Visualization).

Web-based geo-visualisation of spatial information to support evidence-based health policy: a case study of the development process of HealthTracks

Place is of critical importance to health as it can reveal patterns of disease spread and clustering, associations with risk factors, and areas with greatest need for, or least access to healthcare services and promotion activities. Furthermore, in order to get a good understanding of the health status and needs of a particular area a broad range of data are required which can often be difficult and time consuming to obtain and collate. This process has been expedited by bringing together multiple data sources and making them available in an online geo-visualisation, HealthTracks, which consists of a mapping and reporting component. The overall aim of the HealthTracks project is to make spatial health information more accessible to policymakers, analysts, planners and program managers to inform decision-making across the Department of Health Western Australia. Preliminary mapping and reporting applications that have been utilised to inform service planning, increased awareness of the utility of spatial information and improved efficiency in data access were developed. The future for HealthTracks involves expanding the range of data available and developing new analytical capabilities in order to work towards providing external agencies, researchers and eventually the general public access to rich local area spatial data.

Visualization and analytics tools for infectious disease epidemiology: a systematic review

BACKGROUND

A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools.

METHODS

We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review.

RESULTS

A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use.

DISCUSSION AND CONCLUSION

As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload.

Designing a web-based learning portal for geographic visualization and analysis in public health

Interactive mapping and spatial analysis tools are under-utilized by health researchers and decision-makers as a result of scarce training materials, few examples demonstrating the successful use of geographic visualization, and poor mechanisms for sharing results generated by geovisualization. Here, we report on the development of the Geovisual EXplication(G-EX) Portal, a web-based application designed to connect researchers in geovisualization and related mapping sciences, to users who are working in public health and epidemiology. This paper focuses on the design and development of the G-EX Portal Learn module, a set of tools intended to disseminate learning artifacts. Initial design and development of the G-EX Portal has been guided by our past research on the use and usability of geovisualization in public health. As part of the iterative design and development process, we conducted a needs assessment survey with targeted end-users, which we report on here. The survey focused on users' current learning habits, their preferred kind of learning artifacts and issues they may have with contributing learning artifacts to web portals. Survey results showed that users desire a diverse set of learning artifacts in terms of both formats and topics covered. Results also revealed a willingness of users to contribute both learning artifacts and personal information that would help other users to evaluate the credibility of the learning artifact source. We include a detailed description of the G-EX Portal Learn module and focus on modifications to the design of the Learn module as a result from feedback we received from our survey.

Human-centered approaches in geovisualization design: investigating multiple methods through a long-term case study

Working with three domain specialists we investigate human-centered approaches to geovisualization following an ISO13407 taxonomy covering context of use, requirements and early stages of design. Our case study, undertaken over three years, draws attention to repeating trends: that generic approaches fail to elicit adequate requirements for geovis application design; that the use of real data is key to understanding needs and possibilities; that trust and knowledge must be built and developed with collaborators. These processes take time but modified human-centred approaches can be effective. A scenario developed through contextual inquiry but supplemented with domain data and graphics is useful to geovis designers. Wireframe, paper and digital prototypes enable successful communication between specialist and geovis domains when incorporating real and interesting data, prompting exploratory behaviour and eliciting previously unconsidered requirements. Paper prototypes are particularly successful at eliciting suggestions, especially for novel visualization. Enabling specialists to explore their data freely with a digital prototype is as effective as using a structured task protocol and is easier to administer. Autoethnography has potential for framing the design process. We conclude that a common understanding of context of use, domain data and visualization possibilities are essential to successful geovis design and develop as this progresses. HC approaches can make a significant contribution here. However, modified approaches, applied with flexibility, are most promising. We advise early, collaborative engagement with data – through simple, transient visual artefacts supported by data sketches and existing designs – before moving to successively more sophisticated data wireframes and data prototypes.

The case for visual analytics of arsenic concentrations in foods

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species.

Resolution Control for Balancing Overview + Detail in Spatial, Multivariate Analysis

Parallel coordinates, re-orderable matrices, and dendrograms are widely used for visual exploration of multivariate data. This research proposes an approach to systematically integrate the methods in a complementary manner for supporting multi-resolution visual data analysis with an enhanced overview+detail exploratory strategy. The paper focuses on three topics: (1) dynamic control across resolutions at which data are explored; (2) coordination and color mapping among the views; and (3) enhanced features of each view designed for the overview+detail exploratory tasks. We contend that systematically coordinating the views through user-controlled resolutions within a highly interactive analysis environment will boost productivity for exploration tasks. We offer a case study analysis to demonstrate this potential. The case study is focused on a complex, geographically referenced dataset including public health, demographic and environmental components.

Informing geospatial toolset design: understanding the process of cancer data exploration and analysis

There is an increasing need for new methods and tools that support knowledge construction from complex geospatial datasets related to public health. This study is part of a larger effort to develop, implement, and test such methods and tools. To be successful, the design of methods and tools must be grounded in a solid understanding of the work practices within the domain of use; the research reported here focuses on developing that understanding. We adopted a user-centered approach to toolset design where we investigated the work of cancer researchers and used the results of that investigation as inputs into the development of design guidelines for new geovisualization and spatial analysis tools. Specifically, we conducted key informant interviews focused on use, or potential use, of geographic information, methods, and tools and complemented this with a systematic analysis of published, peer-reviewed articles on geospatial cancer research. Results were used to characterize the typical process of analysis, to identify fundamental differences between intensive users of geospatial methods and infrequent users, and to outline key stages in analysis and tasks within the stages that methods and tools must support. Our findings inform design and implementation decisions for visual and analytic tools that support cancer prevention and control research and they provide insight into the processes used by cancer researchers for addressing the challenges of geographic factors in public health research and policy.

Distributed usability evaluation of the Pennsylvania Cancer Atlas

Background

The Pennsylvania Cancer Atlas (PA-CA) is an interactive online atlas to help policy-makers, program managers, and epidemiologists with tasks related to cancer prevention and control. The PA-CA includes maps, graphs, tables, that are dynamically linked to support data exploration and decision-making with spatio-temporal cancer data. Our Atlas development process follows a user-centered design approach. To assess the usability of the initial versions of the PA-CA, we developed and applied a novel strategy for soliciting user feedback through multiple distributed focus groups and surveys. Our process of acquiring user feedback leverages an online web application (e-Delphi). In this paper we describe the PA-CA, detail how we have adapted e-Delphi web application to support usability and utility evaluation of the PA-CA, and present the results of our evaluation.

Results

We report results from four sets of users. Each group provided structured individual and group assessments of the PA-CA as well as input on the kinds of users and applications for which it is best suited. Overall reactions to the PA-CA are quite positive. Participants did, however, provide a range of useful suggestions. Key suggestions focused on improving interaction functions, enhancing methods of temporal analysis, addressing data issues, and providing additional data displays and help functions. These suggestions were incorporated in each design and implementation iteration for the PA-CA and used to inform a set of web-atlas design principles.

Conclusion

For the Atlas, we find that a design that utilizes linked map, graph, and table views is understandable to and perceived to be useful by the target audience of cancer prevention and control professionals. However, it is clear that considerable variation in experience using maps and graphics exists and for those with less experience, integrated tutorials and help features are needed. In relation to our usability assessment strategy, we find that our distributed, web-based method for soliciting user input is generally effective. Advantages include the ability to gather information from users distributed in time and space and the relative anonymity of the participants while disadvantages include less control over when and how often participants provide input and challenges for obtaining rich input.

A design framework for exploratory geovisualization in epidemiology

This paper presents a design framework for geographic visualization based on iterative evaluations of a toolkit designed to support cancer epidemiology. The Exploratory Spatio-Temporal Analysis Toolkit (ESTAT), is intended to support visual exploration through multivariate health data. Its purpose is to provide epidemiologists with the ability to generate new hypotheses or further refine those they may already have. Through an iterative user-centered design process, ESTAT has been evaluated by epidemiologists at the National Cancer Institute (NCI). Results of these evaluations are discussed, and a design framework based on evaluation evidence is presented. The framework provides specific recommendations and considerations for the design and development of a geovisualization toolkit for epidemiology. Its basic structure provides a model for future design and evaluation efforts in information visualization.

Visual Inquiry Toolkit - An Integrated Approach for Exploring and Interpreting Space-Time, Multivariate Patterns

While many datasets carry geographic and temporal references, our ability to analyze these datasets lags behind our ability to collect them because of the challenges posed by both data complexity and scalability issues. This study develops a visual analytics approach that integrates human knowledge and judgments with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate datasets. Specifically, a variety of methods are employed for data clustering, pattern searching, information visualization and synthesis. By combining both human and machine strengths, this approach has a better chance to discover novel, relevant and potentially useful information that is difficult to detect by any method used in isolation. We demonstrate the effectiveness of the approach by applying the Visual Inquiry Toolkit we developed to analysis of a dataset containing geographically referenced, time-varying and multivariate data for U.S. technology industries.