Evaluating the effect of visually represented geodata uncertainty on decision-making: systematic review, lessons learned, and recommendations

Kinkeldey, Christoph; MacEachren, Alan M.; Riveiro, Maria; Schiewe, Jochen

doi:10.1080/15230406.2015.1089792

Cited by 83 publications

(78 citation statements)

References 39 publications

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“…When high level tasks are used, few authors justify their choice [19]. Recent reviews [19,18,3] on the exploration of uncertain data show an existing, large body of work that focuses on communication [17,12], collaboration [35,8] and user evaluations [4,34]. These reviews also highlight the need to focus on enabling reasoning and sense-making under uncertainty [25].…”

Section: Introductionmentioning

confidence: 99%

How Data Workers Cope with Uncertainty

Boukhelifa

Perrin

Huron

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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Section: Introductionmentioning

confidence: 99%

How Data Workers Cope with Uncertainty

Boukhelifa

Perrin

Huron

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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“…Gershon, 1998;Pang, Wittenbrink, & Lodha, 1997), and several review studies have been conducted (e.g. Epp & Bull, 2015;Kinkeldey, MacEachren, & Schiewe, 2014;Kinkeldey et al, 2015;MacEachren et al, 2005). These studies conclude that the presentation format could make a difference for user decision-making and understanding of the concept.…”

Section: The Presentation Of Measurement Errormentioning

confidence: 99%

“…The presentation of error information has received growing attention across a range of disciplines outside the field of education (e.g. Brodlie, Osoria, & Lopes, 2012;Kinkeldey, MacEachren, Riveiro, & Schiewe, 2015), resulting in the development of many potential visual tools for presenting ME. To help designers choose a presentation format, various taxonomies have been proposed (e.g.…”

Section: The Presentation Of Measurement Errormentioning

confidence: 99%

Comparing the influence of various measurement error presentations in test score reports on educational decision-making

Otter

Muilenburg

Wools

et al. 2018

Assessment in Education: Principles, Policy & Practice

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a Faculty of Behavioral, management and social sciences (Bms), university of twente, enschede, the netherlands; b citolab, cito institute for educational measurement, Arnhem, the netherlands; c Psychometric research centre, cito institute for educational measurement, Arnhem, the netherlands ABSTRACT This study investigated (1) the extent to which presentations of measurement error in score reports influence teachers' decisions and (2) teachers' preferences in relation to these presentations. Three presentation formats of measurement error (blur, colour value and error bar) were compared to a presentation format that omitted measurement error. The results from a factorial survey analysis showed that the position of a score in relation to a cut-off score impacted most significantly on decisions. Moreover, the teachers (N = 337) indicated the need for additional information significantly more often when the score reports included an error bar compared to when they omitted measurement error. The error bar was also the most preferred presentation format. The results were supported in thinkaloud protocols and focus groups, although several interpretation problems and misconceptions of measurement error were identified.

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“…Based on advances in both hardware and software libraries to generate animated visualizations, recent research has investigated the use of animation for visualizations in air-traffic analysis (Buschmann et al, 2016), emergency management (Wang et al, 2017), storm surge flooding (Reyes and Chen, 2017) and soil acidification (Russo et al, 2014), to name but a few examples. Readers looking for more complete reviews of the work that has been done around the communication of uncertainty in geographic information are referred to the broad review papers by MacEachren et al (2005), Kinkeldey et al (2014), and Kinkeldey et al (2017). Readers looking for practical recommendations as to which kind of visualization is suitable for which user group are referred to Senaratne et al (2012), who conducted a usability study with different visualizations of uncertainty and users from different backgrounds.…”

Section: Related Workmentioning

confidence: 99%

Animation as a Visual Indicator of Positional Uncertainty in Geographic Information

Keßler

Lotstein

2018

Lecture Notes in Geoinformation and Cartography

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Effectively communicating the uncertainty that is inherent in any kind of geographic information remains a challenge. This paper investigates the efficacy of animation as a visual variable to represent positional uncertainty in a web mapping context. More specifically, two different kinds of animation (a 'bouncing' and a 'rubberband' effect) have been compared to two static visual variables (symbol size and transparency), as well as different combinations of those variables in an online experiment with 163 participants. The participants' task was to identify the most and least uncertain point objects in a series of web maps. The results indicate that the use of animation to represent uncertainty imposes a learning step on the participants, which is reflected in longer response times. However, once the participants got used to the animations, they were both more consistent and slightly faster in solving the tasks, especially when the animation was combined with a second visual variable. According to the test results, animation is also particularly well suited to represent positional uncertainty, as more participants interpreted the animated visualizations correctly, compared to the static visualizations using symbol size and transparency. Somewhat contradictory to those results, the participants showed a clear preference for those static visualizations.

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Evaluating the effect of visually represented geodata uncertainty on decision-making: systematic review, lessons learned, and recommendations

Cited by 83 publications

References 39 publications

How Data Workers Cope with Uncertainty

How Data Workers Cope with Uncertainty

Comparing the influence of various measurement error presentations in test score reports on educational decision-making

Animation as a Visual Indicator of Positional Uncertainty in Geographic Information

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