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Journal ArticleDOI

How to assess visual communication of uncertainty? a systematic review of geospatial uncertainty visualisation user studies

20 Nov 2014-Cartographic Journal (Taylor & Francis)-Vol. 51, Iss: 4, pp 372-386
TL;DR: A systematic review of past user studies of uncertainty visualisation, focusing on the field of geographic visualisation and cartography and thus on displays containing geospatial uncertainty, highlights the importance of user tasks for successful solutions and recommends moving towards task-centered typologies to support systematic evaluation.
Abstract: For decades, uncertainty visualisation has attracted attention in disciplines such as cartography and geographic visualisation, scientific visualisation and information visualisation. Most of this research deals with the development of new approaches to depict uncertainty visually; only a small part is concerned with empirical evaluation of such techniques. This systematic review aims to summarize past user studies and describe their characteristics and findings, focusing on the field of geographic visualisation and cartography and thus on displays containing geospatial uncertainty. From a discussion of the main findings, we derive lessons learned and recommendations for future evaluation in the field of uncertainty visualisation. We highlight the importance of user tasks for successful solutions and recommend moving towards task-centered typologies to support systematic evaluation in the field of uncertainty visualisation.
Citations
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Journal ArticleDOI
TL;DR: An integrative model that is grounded in models of visualization comprehension and a dual-process account of decision making with visualizations is proposed and four cross-domain findings that may constitute universal visualization principles are illustrated.
Abstract: Visualizations—visual representations of information, depicted in graphics—are studied by researchers in numerous ways, ranging from the study of the basic principles of creating visualizations, to the cognitive processes underlying their use, as well as how visualizations communicate complex information (such as in medical risk or spatial patterns). However, findings from different domains are rarely shared across domains though there may be domain-general principles underlying visualizations and their use. The limited cross-domain communication may be due to a lack of a unifying cognitive framework. This review aims to address this gap by proposing an integrative model that is grounded in models of visualization comprehension and a dual-process account of decision making. We review empirical studies of decision making with static two-dimensional visualizations motivated by a wide range of research goals and find significant direct and indirect support for a dual-process account of decision making with visualizations. Consistent with a dual-process model, the first type of visualization decision mechanism produces fast, easy, and computationally light decisions with visualizations. The second facilitates slower, more contemplative, and effortful decisions with visualizations. We illustrate the utility of a dual-process account of decision making with visualizations using four cross-domain findings that may constitute universal visualization principles. Further, we offer guidance for future research, including novel areas of exploration and practical recommendations for visualization designers based on cognitive theory and empirical findings.

120 citations

Journal ArticleDOI
TL;DR: A taxonomy for characterizing decisions made in designing an evaluation of an uncertainty visualization is presented and a concrete set of recommendations for evaluators designed to reduce the mismatch between the conceptualization of uncertainty in visualization versus other fields is concluded.
Abstract: Understanding and accounting for uncertainty is critical to effectively reasoning about visualized data. However, evaluating the impact of an uncertainty visualization is complex due to the difficulties that people have interpreting uncertainty and the challenge of defining correct behavior with uncertainty information. Currently, evaluators of uncertainty visualization must rely on general purpose visualization evaluation frameworks which can be ill-equipped to provide guidance with the unique difficulties of assessing judgments under uncertainty. To help evaluators navigate these complexities, we present a taxonomy for characterizing decisions made in designing an evaluation of an uncertainty visualization. Our taxonomy differentiates six levels of decisions that comprise an uncertainty visualization evaluation: the behavioral targets of the study, expected effects from an uncertainty visualization, evaluation goals, measures, elicitation techniques, and analysis approaches. Applying our taxonomy to 86 user studies of uncertainty visualizations, we find that existing evaluation practice, particularly in visualization research, focuses on Performance and Satisfaction-based measures that assume more predictable and statistically-driven judgment behavior than is suggested by research on human judgment and decision making. We reflect on common themes in evaluation practice concerning the interpretation and semantics of uncertainty, the use of confidence reporting, and a bias toward evaluating performance as accuracy rather than decision quality. We conclude with a concrete set of recommendations for evaluators designed to reduce the mismatch between the conceptualization of uncertainty in visualization versus other fields.

117 citations


Cites background or result from "How to assess visual communication ..."

  • ...Multiple researchers have called for a greater focus on realistic decision making in uncertainty visualization evaluation [38, 55, 54, 79]....

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  • ...Our results confirm and extend recent recommendations made by others [38, 55, 54]....

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  • ...Several recent papers comment on the challenges of designing a realistic uncertainty visualization evaluation while maintaining sufficient experimental control to test predictions [55, 79]....

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  • ...summarize studies reported in 34 publications that describe an evaluation of how geospatial uncertainty visualizations communicate [55]....

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  • ...Recently, scholars have pointed to the challenges evaluating uncertainty visualizations compared to evaluating other visualizations [38, 55, 79]....

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Journal ArticleDOI
24 May 2017
TL;DR: An agenda for empirical research on this user and the interactive designs he or she employs is presented and the focus of the discussion is epistemological and reflects the wide interdisciplinary influences on user studies in cartography.
Abstract: The possibility of digital interactivity requires us to reenvision the map reader as the map user, and to address the perceptual, cognitive, cultural, and practical considerations that influence th...

103 citations

Journal ArticleDOI
13 Mar 2017
TL;DR: Geospatial big data presents a new set of challenges and opportunities for cartographic researchers in technical, methodological and artistic realms as mentioned in this paper, and new computational and technical paradigms for ca...
Abstract: Geospatial big data present a new set of challenges and opportunities for cartographic researchers in technical, methodological and artistic realms. New computational and technical paradigms for ca ...

100 citations


Cites background from "How to assess visual communication ..."

  • ...Challenge: develop new approaches for visualizing the quality and certainty of geospatial big data In Kinkeldey, MacEachren, and Schiewe (2014), the authors reviewed decades of efforts to find a way to communicate data quality information on maps, and have concluded that the task to retrieve…...

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Journal ArticleDOI
TL;DR: A design framework to help scientists develop effective visualisations within nonscientific, professional contexts and concludes that the uptake of science within environmental decision-making requires a highly iterative and collaborative design approach towards the development of tailored visualisations.
Abstract: Environmental science is an applied discipline, which therefore requires interacting with actors outside of the scientific community. Visualisations are increasingly seen as powerful tools to engage users with unfamiliar and complex subject matter. Despite recent research advances, scientists are yet to fully harness the potential of visualisation when interacting with non-scientists. To address this issue, we review the main principles of visualisation, discuss specific graphical challenges for environmental science and highlight some best practice from non-professional contexts. We provide a design framework to enhance the communication and application of scientific information within professional contexts. These guidelines can help scientists incorporate effective visualisations within improved dissemination and knowledge exchange platforms. We conclude that the uptake of science within environmental decision-making requires a highly iterative and collaborative design approach towards the development of tailored visualisations. This enables users to not only generate actionable understanding but also explore information on their own terms. Effective visualisations can engage non-scientists with unfamiliar and complex subject matter.We review the main principles of visualisation and specific graphical challenges for environmental science.We provide a design framework to help scientists develop effective visualisations within nonscientific, professional contexts.The uptake of science within environmental decision-making requires a highly iterative and collaborative design approach.

96 citations

References
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Journal ArticleDOI
TL;DR: This work describes systems that are informationally equivalent and that can be characterized as sentential or diagrammatic, and contrasts the computational efficiency of these representotions for solving several illustrative problems in mothematics and physics.

3,237 citations

Journal ArticleDOI
TL;DR: In this article, a Triad representational approach that unifies temporal-as well as locational-and object-related aspects and that incorporates concepts from perceptual psychology, artifical intelligence, and other fields is presented.
Abstract: The study of spatiotemporal dynamics is certainly not new, nor is it unique to the field of geography. Nevertheless, addressing complex human and environmental issues such as global warming and human impacts on the environment requires empirical examination from a much broader and integrated perspective than can be accomplished with current techniques. Although Geographic Information Systems (GIS) are intended to provide an integrated and flexible tool for analyzing large volumes of data, they are historically geared toward the representation and analysis of situations frozen in time. Efforts to enhance the temporal capabilities of GIS have served to reveal many problems at a fundamental conceptual level. In order to address this problem, this paper presents a new Triad representational approach that unifies temporal-as well as locational-and object-related aspects and that incorporates concepts from perceptual psychology, artifical intelligence, and other fields. The goal of this research is a d...

681 citations


"How to assess visual communication ..." refers background in this paper

  • ...Although these categories seem logical and match with conceptualisations of data used in geographic database research and development (Peuquet, 1994), their use may be limited for the majority of applications of uncertainty visualisation....

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Journal ArticleDOI
TL;DR: These uncertainty visualization techniques present data in such a manner that users are made aware of the locations and degree of uncertainties in their data so as to make more informed analyses and decisions.
Abstract: Visualized data often have dubious origins and quality. Different forms of uncertainty and errors are also introduced as the data are derived, transformed, interpolated, and finally rendered. In the absence of integrated presentation of data and uncertainty, the analysis of the visualization is incomplete at best and often leads to inaccurate or incorrect conclusions. This paper surveys techniques for presenting data together with uncertainty. These uncertainty visualization techniques present data in such a manner that users are made aware of the locations and degree of uncertainties in their data so as to make more informed analyses and decisions. The techniques include adding glyphs, adding geometry, modifying geometry, modifying attributes, animation, sonification, and psycho-visual approaches. We present our results in uncertainty visualization for environmental visualization, surface interpolation, global illumination with radiosity, flow visualization, and figure animation. We also present a classification of the possibilities in uncertainty visualization, and locate our contributions within this classification.

562 citations


"How to assess visual communication ..." refers background or methods in this paper

  • ...Much of the work has focused on developing typologies of uncertainty that represent various aspects of data and how it might be signified (Buttenfield and Weibel, 1988; Pang et al., 1997; Sanyal et al., 2009; Thomson et al., 2005) and on developing methods to depict uncertainty visually (e....

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  • ...…focused on developing typologies of uncertainty that represent various aspects of data and how it might be signified (Buttenfield and Weibel, 1988; Pang et al., 1997; Sanyal et al., 2009; Thomson et al., 2005) and on developing methods to depict uncertainty visually (e.g. Cedilnik and Rheingans,…...

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Journal ArticleDOI
TL;DR: Progress toward visual tools and methods to help analysts manage and understand information uncertainty are reviewed and progress toward frameworks for representing uncertainty, visual representation and user control of displays of information uncertainty is assessed.
Abstract: Developing reliable methods for representing and managing information uncertainty remains a persistent and relevant challenge to GIScience. Information uncertainty is an intricate idea, and recent examinations of this concept have generated many perspectives on its representation and visualization, with perspectives emerging from a wide range of disciplines and application contexts. In this paper, we review and assess progress toward visual tools and methods to help analysts manage and understand information uncertainty. Specifically, we report on efforts to conceptualize uncertainty, decision making with uncertainty, frameworks for representing uncertainty, visual representation and user control of displays of information uncertainty, and evaluative efforts to assess the use and usability of visual displays of uncertainty. We conclude by identifying seven key research challenges in visualizing information uncertainty, particularly as it applies to decision making and analysis.

540 citations


"How to assess visual communication ..." refers background in this paper

  • ...A comprehensive review of uncertainty typologies is provided by MacEachren et al. (2005) and a review of uncertainty visualisation across science by Brodlie et al. (2012)....

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  • ...In practice, it is hard to clearly distinguish between these categories: ‘[t]he categories of uncertainty are often interdependent, and the category boundaries are often hard to delineate’ (MacEachren et al., 2005, p. 156)....

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  • ...Uncertainty categories When uncertainty of geospatial data is depicted, it can be quantified and represented for each of the three core information components: attribute (what), positional (where) and temporal (when) uncertainty (MacEachren et al., 2005)....

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  • ...When uncertainty of geospatial data is depicted, it can be quantified and represented for each of the three core information components: attribute (what), positional (where) and temporal (when) uncertainty (MacEachren et al., 2005)....

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Journal ArticleDOI
TL;DR: The difference between data quality and uncertainty, the application of Berlin's graphic variables to the representation of uncertainty, conceptual models of spatial uncertainty as they relate to kinds of cartographic symbolization, and categories of user interfaces suited to presenting data and uncertainty about that data are addressed.
Abstract: When a GIS is used to drive map-based visualization, exploration of potential relationships takes precedence over presentation of facts. In these early stages of scientific analysis or policy formulation, providing a way for analysts to assess uncertainty in the data they are exploring is critical to the perspectives they form and the approaches they decide to pursue. As a basis from which to develop methods for visualizing uncertain information, this paper addresses the difference between data quality and uncertainty, the application of Berlin's graphic variables to the representation of uncertainty, conceptual models of spatial uncertainty as they relate to kinds of cartographic symbolization, and categories of user interfaces suited to presenting data and uncertainty about that data. Also touched on is the issue of how we might evaluate our attempts to depict uncertain information on maps.

351 citations


"How to assess visual communication ..." refers background or result in this paper

  • ...…November 2014 # The British Cartographic Society 2014 DOI: 10.1179/1743277414Y.0000000099 N coincident/adjacent This categorisation refers to view organisation, i.e. if data and uncertainty are represented in an integrated view (coincident) or in separate views (adjacent) (MacEachren, 1992)....

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  • ...Coincident/adjacent Starting with the earliest research on uncertainty visualisation, coincident approaches (with data and uncertainty integrated in the existing display) have been contrasted with adjacent approaches with data and uncertainty in separate views (MacEachren, 1992)....

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  • ...Another crucial aspect is the role of visual metaphors that have been used to depict uncertainty since the beginning of this field of research, e.g. fog or blur (MacEachren, 1992)....

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  • ...Starting with the earliest research on uncertainty visualisation, coincident approaches (with data and uncertainty integrated in the existing display) have been contrasted with adjacent approaches with data and uncertainty in separate views (MacEachren, 1992)....

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  • ...if data and uncertainty are represented in an integrated view (coincident) or in separate views (adjacent) (MacEachren, 1992)....

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