Visualizing Uncertainty About the Future
Abstract
We are all faced with uncertainty about the future, but we can get the measure of some uncertainties in terms of probabilities. Probabilities are notoriously difficult to communicate effectively to lay audiences, and in this review we examine current practice for communicating uncertainties visually, using examples drawn from sport, weather, climate, health, economics, and politics. Despite the burgeoning interest in infographics, there is limited experimental evidence on how different types of visualizations are processed and understood, although the effectiveness of some graphics clearly depends on the relative numeracy of an audience. Fortunately, it is increasingly easy to present data in the form of interactive visualizations and in multiple types of representation that can be adjusted to user needs and capabilities. Nonetheless, communicating deeper uncertainties resulting from incomplete or disputed knowledge--or from essential indeterminacy about the future--remains a challenge.
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To overcome the adverse effect of denominator neglect, it is important to present ratios with the same denominator so that they can be compared with just the numerator.
“First, to overcome the adverse effect of denominator neglect, it is important to present ratios with the same denominator so that they can be compared with just the numerator [116].”
From Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2021) · cites this paper as [116]
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“This problem is not limited to demographic or social science applications, and there is already considerable work in this area more broadly (e.g., Spiegelhalter et al. 2011).”
BackgroundGuía ESC 2021 sobre la prevención de la enfermedad cardiovascular en la práctica clínica
Visseren, F. L. J., Mach, F., Smulders, Y. M., Carballo, D., Koskinas, K. C., Bäck, M., Bénétos, A., Biffi, A., Boavida, J. M., Capodanno, D., et al. (2022) · Revista Española de Cardiología · doi:10.1016/j.recesp.2021.10.016 · Cited by 80 · see citing works
Try, try again: Lessons learned from success and failure in participatory modeling
Sterling, E., Zellner, M., Jenni, K., Leong, K. M., Glynn, P., BenDor, T., Bommel, P., Hubacek, K., Jetter, A. J., Jordan, R., et al. (2019) · Elementa: Science of the Anthropocene · doi:10.1525/elementa.347 · Cited by 71 · see citing works
Beven, K. J., Aspinall, W. P., Bates, P., Borgomeo, E., Goda, K., Hall, J. W., Page, T., Phillips, J. C., Simpson, M. H., Smith, P. J., et al. (2018) · Natural hazards and earth system sciences · doi:10.5194/nhess-18-2769-2018 · Cited by 86 · see citing works
“…decade and a variety of techniques have been explored to represent uncertain data (e.g. Johnson and Sanderson, 2003; MacEachren et al., 2005; Pang, 2008; Kunz et al., 2011; Friedemann et al., 2011; Spiegelhalter et al., 2011; Spiegelhalter and Reisch, 2011; Jupp et al., 2012; Potter et al., 2012).”
BackgroundHow Affect Shapes Risky Choice: Distorted Probability Weighting Versus Probability Neglect
Suter, R., Pachur, T., & Hertwig, R. (2016) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1888 · Cited by 71 · see citing works
Pocock, M., Evans, D., Fontaine, C., Harvey, M., Julliard, R., Mclaughlin, Ó., Silvertown, J., Tamaddoni-Nezhad, A., White, P., & Bohan, D. A. (2016) · Advances in ecological research/Advances in Ecological Research · doi:10.1016/bs.aecr.2015.10.006 · Cited by 71 · see citing works
“In other words, visualisation is a powerful tool, but this means that for scientists, it should be treated carefully and handled with integrity (Spiegelhalter et al., 2011; Tufte, 1983).”
BackgroundMethodInfluentialNudging to Reduce the Perceived Threat of Coronavirus and Stockpiling Intention
Kim, J., Giroux, M., Gonzalez-Jimenez, H., Jang, S., Kim, S., Park, J., Kim, J.-E., Lee, J. C., & Choi, Y. (2020) · Journal of Advertising · doi:10.1080/00913367.2020.1806154 · Cited by 70 · see citing works
Perception and use of uncertainty in severe weather warnings by emergency services in Germany
Kox, T., Gerhold, L., & Ulbrich, U. (2015) · Atmospheric Research · doi:10.1016/j.atmosres.2014.02.024 · Cited by 68 · see citing works
Bornmann, L., Stefaner, M., Anegón, F. D. M., & Mutz, R. (2012) · Online information review (Print) · doi:10.48550/arxiv.1212.0304 · Cited by 68 · see citing works
Communicating uncertainty in seasonal and interannual climate forecasts in Europe
Taylor, A. L., Dessai, S., & de Bruin, W. D. (2015) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2014.0454 · Cited by 67 · see citing works
“These formats were chosen as they are relatively common ways of representing probability [5].”
BackgroundInfluentialDealing with uncertainty: integrating local and scientific knowledge of the climate and weather.
Kniveton, D., Visman, E., Tall, A., Diop, M., Ewbank, R., Njoroge, E., & Pearson, L. (2015) · Disasters. The Journal of Disaster Studies, Policy and Management · doi:10.1111/disa.12108 · Cited by 65
Future Prospects for Energy Technologies: Insights from Expert Elicitations
Verdolini, E., Anadón, L., Baker, E., Bosetti, V., & Reis, L. A. (2018) · Review of Environmental Economics and Policy · doi:10.1093/reep/rex028 · Cited by 64 · see citing works
“The issue of how to communicate data on uncertainty to final users is complex (Spiegelhalter et al. 2011).”
Cellular characterization of ultrasound-stimulated microbubble radiation enhancement
Al‐Mahrouki, A., Iradji, S., Tran, W. T., & Czarnota, G. J. (2014) · Disease Models & Mechanisms · doi:10.1242/dmm.012922 · Cited by 56 · see citing works
“Radiotherapy is considered to be an effective conventional therapy for various tumors (Folkman and Camphausen, 2001; Spiegelhalter et al., 2011; Wei et al., 2012).”
BackgroundIt's the Psychology, Stupid!! Understanding Human Cognition Biases to Inform Sustainable Behavior
Engler, J., Abson, D. J., & von Wehrden, H. (2017) · AMBIO · doi:10.1007/s13280-018-1100-5 · Cited by 78 · see citing works
Penn, L., Rodrigues, A., Haste, A., Marques, M. M., Budig, K., Sainsbury, K., Bell, R., Araújo‐Soares, V., White, M. J., Summerbell, C. D., et al. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-019467 · Cited by 78 · see citing works
“(Interview, intervention deliverer 14, female age 52 years)”
Measuring Graph Literacy without a Test: A Brief Subjective Assessment
Garcia-Retamero, R., Cokely, E. T., Ghazal, S., & Joeris, A. (2016) · Medical Decision Making · doi:10.1177/0272989x16655334 · Cited by 64 · see citing works
Jensen, J. D., Pokharel, M., Scherr, C., King, A. J., Brown, N., & Jones, C. L. (2016) · Risk Analysis · doi:10.1111/risa.12600 · Cited by 62 · see citing works
“replicate past research and because it is frequently used as an exemplar by researchers studying the communication of uncertainty.(4,7,9,20,21)”
Landuyt, D., van der Biest, K., Broekx, S., Staes, J., Meire, P., & Goethals, P. (2015) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2015.05.002 · Cited by 62 · see citing works
“Besides, communicating model uncertainties remains challenging (Spiegelhalter et al., 2011).”
Bayesian Characterization of Uncertainty in Intra-subject Non-rigid Registration
Risholm, P., Janoos, F., Norton, I., Golby, A. J., & Wells, W. M. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.03.002 · Cited by 62 · see citing works
“While a lot of research has gone into finding ways of reducing high-dimensional uncertainty information into simple local lowdimensional objects that can be easily visualized (Spiegelhalter et al., 2011), limited work has been reported on posterior uncertainty visualization in medical applications; including visualiza…”
BackgroundInfluentialRepresenting Uncertainty in Graph Edges: An Evaluation of Paired Visual Variables
Guo, H., Huang, J., & Laidlaw, D. (2015) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2015.2424872 · Cited by 60 · see citing works
“There has been active research on uncertainty visualization techniques and design studies (e.g. [3], [24], [25], [26]) in the areas of geographic information systems, scientific visualization, and information visualization, but they are seldom accompanied by in-depth evaluations of the techniques.”
Desai, P. M., Levine, M., Albers, D., & Mamykina, L. (2018) · International Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174112 · Cited by 59 · see citing works
“This body of literature has demonstrated that individuals are able to broadly understand forecasts as guidelines for daily conditions and can interpret them, often with visual aids such as icons and graphs [25,29,30, 41].”
BackgroundAmeling, J., Auguste, P., Ephraim, P., Lewis-Boyér, L., DePasquale, N., Greer, R., Crews, D., Powe, N., Rabb, H., & Boulware, L. (2012) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-12-140 · Cited by 59
“We did, however, refer to the decision sciences literature extensively as well as the IPDAS criteria throughout the development process [19,25-28,36-40].”
BackgroundA survey of immersive visualization: Focus on perception and interaction
Zhang, Y., Wang, Z.-Y., Zhang, J., Shan, G., & Tian, D. (2023) · Visual Informatics · doi:10.1016/j.visinf.2023.10.003 · Cited by 58 · see citing works
The Binary Bias: A Systematic Distortion in the Integration of Information
Fisher, M. A., & Keil, F. (2018) · Psychology Science · doi:10.1177/0956797618792256 · Cited by 56
Hierarchical Bayesian Modeling of Fluid‐Induced Seismicity
Broccardo, M., Mignan, A., Wiemer, S., Stojadinović, B., & Giardini, D. (2017) · doi:10.1002/2017gl075251 · Cited by 56
Lorenz, S., Dessai, S., Forster, P., & Paavola, J. (2015) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2014.0457 · Cited by 55 · see citing works
“The existing literature suggests that visualizations and communication ought to support user needs [14] and be tailored to the target audience [23,24].”
Epp, C. D., & Bull, S. (2015) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2015.2411604 · Cited by 55 · see citing works
“More-over, carefully selecting visual representations is important since even people with higher numeracy levels can struggle with properly interpreting numerical information [2], [3], [10], [34].”
BackgroundInfluential
- Authors
- Spiegelhalter, D., Pearson, M., & Short, I.
- Affiliations
- University of Cambridge (GB)
- The Open University (GB)
- Corresponding author
- Spiegelhalter, David
- Venue
- Science
- Published
- 2011-09-09
- Volume
- 333
- Issue
- 6048
- Pages
- 1393-1400
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2015011409
- Cited by
- 682
- References
- 0
- Citations by year
- 2026: 21 · 2025: 21 · 2024: 54 · 2023: 39 · 2022: 64 · 2021: 67 · 2020: 52 · 2019: 52 · 2018: 47 · 2017: 40 · 2016: 43 · 2015: 62 · 2014: 36 · 2013: 38 · 2012: 42
- FWCI
- 8.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Open Research Online (The Open University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Social Sciences › Sociology and Political Science › Risk Perception and Management
- Social Sciences › Sociology and Political Science › Climate Change Communication and Perception
- Keywords
- uncertainty communication, probability communication, infographics, interactive visualization, numeracy, lay audiences, future uncertainty, climate uncertainty, weather forecasting, health communication, economics communication, sport
- MeSH terms
- Computer Graphics, Data Display, Forecasting, Humans, Probability, Risk, Information Dissemination, Uncertainty
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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