Visualizing Missing Data: Graph Interpretation User Study

Eaton, Cyntrica; Plaisant, Catherine; Drizd, Terence

doi:10.1007/11555261_68

Cited by 42 publications

(34 citation statements)

References 16 publications

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“…The third alternative is perhaps the most common approach, although there are known problems in it even in a 1D situation (Eaton et al, 2005). In this case, we could use the value zero as a reasonable marker for missing information on mileage or horsepower, since the users would probably interpret them correctly.…”

Section: Missing Data In Parallel Coordinate Visualizationsmentioning

confidence: 99%

Interacting with parallel coordinates

Siirtola

Räihä

2006

Interacting with Computers

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Parallel coordinate visualizations have a reputation of being difficult to understand, expertonly representations. We argue that this reputation may be partially unfounded, because many of the parallel coordinate browser implementations lack essential features. This paper presents a survey of current interaction techniques for parallel coordinate browsers and compares them to the visualization design guidelines in the literature. In addition, we report our experiences with parallel coordinate browser prototypes, and describe an experiment where we studied the immediate usability of parallel coordinate visualizations. In the experiment, 16 database professionals performed a set of tasks both with the SQL query language and a parallel coordinate browser. The results show that although the subjects had doubts about the general usefulness of the parallel coordinate technique, they could perform the tasks more efficiently with a parallel coordinate browser than with their familiar query language interface.

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Section: Missing Data In Parallel Coordinate Visualizationsmentioning

confidence: 99%

Interacting with parallel coordinates

Siirtola

Räihä

2006

Interacting with Computers

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“…In order to draw meaningful and accurate conclusions from the data, visualization tools should represent missingness and uncertainty clearly. For instance, a recent study demonstrated that participants interpreting graphics with missing data tended to misinterpret results, but with equal confidence in their interpretations as those viewing more complete graphics [148]. Similarly, geographic analyses are known to be sensitive to overestimation of rates in small populations, which often correspond to large, sparsely populated regions, resulting in visual biases in interpreting choropleth maps [130].…”

Section: Discussionmentioning

confidence: 99%

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

Carroll

Detwiler

et al. 2014

Journal of Biomedical Informatics

203

171

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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.

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“…There are a number of methods for dealing with missing data in information visualisation applications [18]. These include the use of dedicated visual attributes, annotation and animation.…”

Section: Visualisaing Missing Datamentioning

confidence: 99%

MaTSE: The microarray time-series explorer

Craig

Cannon²,

Kukla³

et al. 2012

2012 IEEE Symposium on Biological Data Visualization (BioVis)

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This paper describes the design, development and evaluation of the Microarray Time-Series Explorer (MaTSE), a novel information visualization application for the exploratory analysis of large scale microarray timeseries data. The software combines a variety of visualization and interaction techniques, which work together to allow biologists to explore their data and reveal patterns that would otherwise be impossible to find. These include a scatter-plot that can be animated to view different temporal intervals of the data, a multiple coordinated view framework to support the cross reference of multiple experimental conditions, a novel method for highlighting overlapping groups in the scatterplot, and a pattern browser component that can be used with scatterplot box queries to support cooperative visualization.

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Visualizing Missing Data: Graph Interpretation User Study

Cited by 42 publications

References 16 publications

Interacting with parallel coordinates

Interacting with parallel coordinates

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

MaTSE: The microarray time-series explorer

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