References
BBC Visual and Data Journalism Team. 2019. “BBC Visual and Data
Journalism Cookbook for R Graphics.” https://github.com/bbc/rcookbook.
Beecham, R. 2020. “Using Position, Angle and Thickness to Expose
the Shifting Geographies of the 2019 UK
General Election.” Environment and
Planning A: Economy and Space 52 (5): 833–36. https://doi.org/10.1177/0308518X20909392.
———. 2024. “
gridmappr
: An R Package for
Creating Small Multiple Gridmap Layouts.” In GISRUK
2024. Leeds, UK: Zenodo. https://doi.org/10.5281/zenodo.10926863.
Beecham, R., J. Dykes, L. Hama, and N. Lomax. 2021. “On the Use of
‘Glyphmaps’ for Analysing the Scale and Temporal Spread of
COVID-19 Reported Cases.” ISPRS International Journal of
Geo-Information 10 (4). https://doi.org/10.3390/ijgi10040213.
Beecham, R., J. Dykes, W. Meulemans, A. Slingsby, C. Turkay, and J.
Wood. 2017. “Map Line-Ups: Effects of Spatial Structure on
Graphical Inference.” IEEE Transactions on Visualization
& Computer Graphics 23 (1): 391–400. https://doi.org/10.1109/TVCG.2016.2598862.
Beecham, R., J. Dykes, C. Rooney, and W. Wong. 2021. “Design Exposition Discussion Documents for Rich Design
Discourse in Applied Visualization.” IEEE
Transactions on Visualization and Computer Graphics 27 (8):
3451–62. https://doi.org/10.1109/TVCG.2020.2979433.
Beecham, R., and R. Lovelace. 2023. “A Framework for Inserting
Visually-Supported Inferences into Geographical Analysis Workflow:
Application to Road Safety Research” 55: 345–66. https://doi.org/10.1111/gean.12338.
Beecham, R., and A. Slingsby. 2019. “Characterising Labour Market
Self-Containment in London with Geographically Arranged
Small Multiples.” Environment and Planning A: Economy and
Space 51 (6): 1217–24. https://doi.org/10.1177/0308518x19850580.
Beecham, R., A. Slingsby, and C. Brunsdon. 2018. “Locally-Varying
Explanations Behind the United Kingdom’s Vote
to Leave the European Union.”
Journal of Spatial Information Science 16: 117–36. https://doi.org/10.5311/josis.2018.16.377.
Beecham, R., N. Williams, and L. Comber. 2020.
“Regionally-Structured Explanations Behind Area-Level Populism:
An Update to Recent Ecological Analyses.” PLOS
One 15 (3): e0229974. https://doi.org/10.1371/journal.pone.0229974.
Beecham, R., and J. Wood. 2014. “Exploring Gendered Cycling
Behaviours Within a Large-Scale Behavioural Data-Set.”
Transportation Planning and Technology 37 (1): 83–97. https://doi.org/10.1080/03081060.2013.844903.
Beecham, R., Y. Yang, C. Tait, and R. Lovelace. 2023. “Connected
Bikeability in London: Which Localities Are Better Connected by Bike and
Does This Matter?” Environment and Planning B: Urban
Analytics and City Science 50 (8): 2103–17. https://doi.org/10.1177/23998083231165122.
Bhatia, A., and H. Reich. 2020. Covidtrends. https://github.com/aatishb/covidtrends.
Boukhelifa, N., A. Bezerianos, T. Isenberg, and J. Fekete. 2012.
“Evaluating Sketchiness as a Visual
Variable for the Depiction of
Qualitative Uncertainty.” IEEE
Transactions on Visualization and Computer Graphics 18 (12):
2769–78. https://doi.org/10.1109/TVCG.2012.220.
Brewer, C., and A. Campbell. 1998. “Beyond Graduated Circles:
Varied Point Symbols for Representing Quantitative Data on Maps.”
Cartographic Perspectives, no. 29: 6–25. https://doi.org/10.14714/CP29.672.
Brunsdon, C., and M. Charlton. 2011. “An Assessment
of the Effectiveness of Multiple
Hypothesis Testing for
Geographical Anomaly
Detection.” Environment and Planning B: Planning
and Design 38 (2): 216–30. https://doi.org/10.1068/b36093.
Brunsdon, C., and A. Comber. 2021. “Opening Practice: Supporting
Reproducibility and Critical Spatial Data Science.” Journal
of Geographical Systems 23: 477–96. https://doi.org/10.1007/s10109-020-00334-2.
Brunsdon, C., M. Fortheringham, and M. Charlton. 2002.
“Geographically Weighted Summary Statistics: A Framework for
Localised Exploratory Data Analysis.” Computers, Environment
and Urban Systems 26: 501–24. https://doi.org/10.1016/S0198-9715(01)00009-6.
Buja, A., D. Cook, H. Hofmann, M. Lawrence, E-K Lee, D. Swayne, and H.
Wickham. 2009. “Statistical Inference for Exploratory Data
Analysis and Model Diagnostics.” Philosophical Transactions
of the Royal Society A: Mathematical, Physical and Engineering
Sciences 367 (1906): 4361–83. https://doi.org/10.1098/rsta.2009.0120.
Burn-Murdoch, J. 2020. “BELIV 2020 Keynote: John
Burn-Murdoch.” In 2020 IEEE Workshop on Evaluation and Beyond
- Methodological Approaches to Visualization (BELIV), 9–9. https://doi.org/10.1109/BELIV51497.2020.00007.
———. 2021. “Vaccines Are Working: Charts That Show the Covid
Endgame.” The Financial Times. https://www.ft.com/content/d71729a3-72e8-490c-bd7e-757027f9b226.
———. 2023. “Making Charts That Make an Impact.” Invited
talk, Data Visualization Society’s Outlier Conference. https://www.youtube.com/watch?v=tIbaQUo6H9g&ab_channel=DataVisualizationSociety.
Butler, D., and S. Van Beek. 1990. “Why Not Swing?
Measuring Electoral Change.” Political Science
& Politics 23 (2): 178–84. https://doi.org/10.2307/420065.
Charlotte Muth, L. 2018. “Your Friendly Guide to Colors in Data
Visualisation: An Overview of Color Tools.”
Datawrapper. https://www.datawrapper.de/blog/colorguide.
Cleveland, W., and R. McGill. 1984. “Graphical
Perception: Theory,
Experimentation, and Application to the
Development of Graphical
Methods.” Journal of the American Statistical
Association 79 (387): 531–54. https://doi.org/10.2307/2288400.
Comber, A., C. Brunsdon, M. Charlton, G. Dong, R. Harris, B. Lu, Y. Lü,
et al. 2023. “A Route Map for Successful Applications of
Geographically Weighted Regression.” Geographical
Analysis 55 (1): 155–78. https://doi.org/10.1111/gean.12316.
Correll, M., and M. Gleicher. 2014. “Error Bars
Considered Harmful: Exploring
Alternate Encodings for Mean and
Error.” IEEE Transactions on Visualization and
Computer Graphics 20 (12): 2142–51. https://doi.org/10.1109/TVCG.2014.2346298.
Donoho, D. 2017. “50 Years of Data
Science.” Journal of Computational and Graphical
Statistics 26 (6): 745–66. https://doi.org/10.1080/10618600.2017.1384734.
Dykes, J., and C. Brunsdon. 2007. “Geographically Weighted
Visualization: Interactive Graphics for Scale-Varying
Exploratory Analysis.” IEEE Transactions on Visualization and
Computer Graphics 13 (6): 1161–68. https://doi.org/10.1109/tvcg.2007.70558.
———. 2021. “‘It’s not a bad flu
season’ - Covid myths debunked with data.” https://www-ft-com.proxy-ub.rug.nl/video/0cd6f9f9-664e-40f9-bad4-dde59d7c746c?playlist-name=latest&playlist-offset=223.
Franconeri, S. L., L. M. Padilla, P. Shah, J. M. Zacks, and J. Hullman.
2021. “The Science of Visual Data Communication: What
Works.” Psychological Science in the Public Interest 22
(3): 110–61. https://doi.org/10.1177/15291006211051956
.
Friendly, M. 1992. “Mosaic Displays for Loglinear Models.”
In ASA, Proceedings of the
Statistical Graphics
Section, 61–68.
Gamio, L., and D. Keating. 2016. “How Trump Redrew
the Electoral Map, from Sea to Shining Sea.” The Washington
Post. https://www.washingtonpost.com/graphics/politics/2016-election/election-results-from-coast-to-coast/.
Gelman, A. 2004. “Exploratory Data Analysis for Complex
Models.” Journal of Computational and Graphical
Statistics 13 (4): 755–79. https://doi.org/10.1198/106186004X11435.
Gelman, A., and J. Hill. 2006. Data Analysis Using Regression and
Multilevel/Hierarchical Models. Cambridge, UK: Cambridge University
Press. https://doi.org/10.1017/CBO9780511790942.
Gelman, A., J. Hill, and A. Vehtari. 2020. Regression and Other
Stories. Analytical Methods for Social Research. Cambridge
University Press. https://doi.org/10.1017/9781139161879.
Gelman, A., J. Hill, and M. Yajima. 2012. “Why We (Usually) Don’t
Have to Worry about Multiple Comparisons.” Journal of
Research on Educational Effectiveness 5 (2): 189–211. https://doi.org/10.1080/19345747.2011.618213.
Gleicher, M., D. Albers, R. Walker, I. Jusufi, C. Hansen, and J.
Roberts. 2011. “Visual Comparison for Information
Visualization.” Information Visualization
10 (4): 289–309. https://doi.org/10.1177/1473871611416549.
Gross, J. 2016. “How to Better Communicate Election Forecasts — in
One Simple Chart.” The Washington Post. https://www.washingtonpost.com/news/monkey-cage/wp/2016/11/29/how-to-better-communicate-election-forecasts-in-one-simple-chart/.
Hanretty, C. 2017. “Areal Interpolation and the UK’s
Referendum on EU Membership.” Journal of
Elections, Public Opinion and Parties 37 (4): 466–83. https://doi.org/10.1080/17457289.2017.1287081.
Haroz, S., R. Kosara, and S. L. Franconeri. 2016. “The Connected
Scatterplot for Presenting Paired Time Series.” IEEE
Transactions on Visualization and Computer Graphics 22 (9):
2174–86. https://doi.org/10.1109/TVCG.2015.2502587.
Harrower, M., and C. A. Brewer. 2003. “ColorBrewer.org: An Online
Tool for Selecting Colour Schemes for Maps.” The Cartographic
Journal 40 (1): 27–37. https://doi.org/10.1179/000870403235002042.
Healy, K. 2019. Data Visualization: A Practical Introduction.
Princeton, NJ: Princeton University Press. https://socviz.co.
———. 2020.
covdata
: COVID-19 Case and Mortality Time
Series. http://kjhealy.github.io/covdata.
Heer, J., and M. Bostock. 2010. “Crowdsourcing
Graphical Perception: Using
Mechanical Turk to Assess
Visualization Design.” In
ACM Human Factors in
Computing Systems, 203–12. https://doi.org/10.1145/1753326.1753357.
Henry Riche, N., C. Hurter, N. Diakopoulos, and S. Carpendale, eds.
2018. Data-Driven Storytelling. Abingdon, UK: CRC
Press. https://doi.org/10.1201/9781315281575.
Hullman, J., and A. Gelman. 2021. “Designing for Interactive
Exploratory Data Analysis Requires Theories of Graphical
Inference.” Harvard Data Science Review 3 (3).
Hullman, J., P. Resnick, and E. Adar. 2015. “Hypothetical
Outcome Plots Outperform
Error Bars and Violin
Plots for Inferences About
Reliability of Variable
Ordering.” PLOS One 10 (11). https://doi.org/10.1371/journal.pone.0142444.
Ismay, C., and A. Kim. 2020. Statistical Inference via Data Science:
A ModernDive into R and the Tidyverse.
New York, NY: CRC Press. https://doi.org/10.1201/9780367409913.
Jeppson, H., and H. Hofmann. 2023. “Generalized Mosaic Plots in
the ggplot2 Framework.” The R
Journal 14 (4): 50–78. https://doi.org/10.32614/RJ-2023-013.
Kale, A., F. Nguyen, M. Kay, and J. Hullman. 2019. “Hypothetical
Outcome Plots Help Untrained Observers Judge Trends in Ambiguous
Data.” IEEE Transactions on Visualization and Computer
Graphics 25 (1): 892–902. https://doi.org/10.1109/TVCG.2018.2864909.
Kay, M. 2021. “Uncertainty Visualization as a Moral
Imperative.” Invited talk, BostonCHI meeting. https://www.youtube.com/watch?v=mfQ3QVyw4N0&ab_channel=BostonCHI.
———. 2024. “
ggdist
: Visualizations of Distributions
and Uncertainty in the Grammar of Graphics.” IEEE
Transactions on Visualization and Computer Graphics 30 (1): 414–24.
https://doi.org/10.1109/TVCG.2023.3327195.
Kinkeldey, C., A. MacEachren, and J. Schiewe. 2014. “How to
Assess Visual Communication of
Uncertainty? A Systematic
Review of Geospatial Uncertainty
Visualisation User
Studies.” The Cartographic Journal 51 (4):
372–86. https://doi.org/10.1179/1743277414Y.0000000099.
Kosara, R. 2023. “Lesson 4: Presentation, Uncertainty,
ISOTYPE.” ObservableHQ Notebook; ObservableHQ. https://observablehq.com/@observablehq/lesson-4-presentation-uncertainty-isotype?collection=@observablehq/advanced-data-vis-course.
Kuhn, M., and J. Silge. 2023. Tidy Modelling
with R. Sebastopol, CA: O’Reilly.
Lawlor, O., and H. Robertson. 2021. “Masters
series: Maarten Lambrechts’ connected scatter plot.” https://www.washingtonpost.com/news/monkey-cage/wp/2016/11/29/how-to-better-communicate-election-forecasts-in-one-simple-chart/?noredirect=on.
Lovelace, R., M. Morgan, L. Hama, M. Padgham, D. Ranzolin, and A.
Sparks. 2019. “Stats 19: A Package for Working with Open Road
Crash Data.” The Journal of Open Source Software 4 (33):
1181. https://doi.org/10.21105/joss.01181.
Lovelace, R., J. Nowosad, and J. Muenchow. 2019. Geocomputation with
R. London, UK: CRC Press.
Loy, A., H. Hofmann, and D. Cook. 2017. “Model Choice
and Diagnostics for Linear
Mixed-Effects Models
Using Statistics on Street
Corners.” Journal of Computational and Graphical
Statistics 26 (3): 478–92. https://doi.org/10.1080/10618600.2017.1330207.
McGill, Tukey, R., and W. A. Larsen. 1978. “Variations of Box
Plots.” The American Statistician 32: 12–16. https://doi.org/10.2307/2683468.
Munzner, T. 2014. Visualization Analysis and
Design. AK Peters
Visualization Series. Boca Raton, FL: CRC
Press.
NHC. 2023. “National Hurricane Center and
Central Pacific Hurricane Center.” https://www.nhc.noaa.gov/.
Noble, S., D. McLennan, M. Noble, E. Plunkett, N. Gutacker, M. Silk, and
G. Wright. 2019. “The English Indices of Deprivation 2019.”
Ministry of Housing, Communities & Local Government. https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019.
Open Science Collaboration. 2015. “Estimating the Reproducibility
of Psychological Science.” Science 349 (6251): aac4716.
https://doi.org/10.1126/science.aac4716.
Padilla, L., M. Kay, and J. Hullman. 2021. “Uncertainty
Visualization.” In Wiley StatsRef:
Statistics Reference Online,
edited by B. Everitt N. Balakrishnan T. Colton and J. L. Teugels. Wiley.
https://doi.org/10.1002/9781118445112.stat08296.
Pebesma, E. 2018. “Simple Features for R:
Standardized Support for Spatial Vector Data.”
The R Journal 10 (1): 439–46. https://doi.org/10.32614/RJ-2018-009.
Roth, R. 2021. “Cartographic Design as
Visual Storytelling: Synthesis
and Review of Map-Based
Narratives, Genres, and
Tropes.” The Cartographic Journal 58 (1):
83–114. https://doi.org/10.1080/00087041.2019.1633103.
Scherer, C. 2023. “Designing Data Visualizations to Successfully
Tell a Story.” Workshop at Posit::conf(2023), Chicago, IL. https://posit-conf-2023.github.io/dataviz-storytelling/.
Silver, N. 2016. “Why FiveThirtyEight Gave Trump a Better Chance
Than Almost Anyone Else.” FiveThirtyEight. https://fivethirtyeight.com/features/why-fivethirtyeight-gave-trump-a-better-chance-than-almost-anyone-else.
Stevens, S. 1946. “On the Theory of Scales of Measurement.”
Science 103 (2684): 677–80. https://doi.org/10.1126/science.103.2684.677.
The Turing Way Community. 2025. “The Turing Way: A Handbook for
Reproducible, Ethical and Collaborative Research.” Zenodo. https://doi.org/10.5281/zenodo.15213042.
Thebault, R., and A. Hauslohner. 2020. “Covid-19’s Deadly New
Surge Is in Rural America as States Re-Open -
The Washington Post.”
The Washington Post. https://www.washingtonpost.com/nation/2020/05/24/coronavirus-rural-america-outbreaks/?arc404=true.
Tortosa, E. V., R. Lovelace, E. Heinen, and R. P. Mann. 2021.
“Socioeconomic Inequalities in Cycling Safety: An Analysis of
Cycling Injury Risk by Residential Deprivation Level in England.”
Journal of Transport & Health 23: 101291. https://doi.org/10.1016/j.jth.2021.101291.
Tufte, E. 1983. The Visual Display of
Quantitative Information. Cheshire, CT:
Graphics Press.
Tukey, J. W. 1962. “The Future of Data
Analysis.” The Annals of Mathematical Statistics
33 (1): 1–67. https://doi.org/10.1214/aoms/1177704711.
Tukey, John W. 1977. Exploratory Data
Analysis. Reading, MA: Addison-Wesley.
Uberoi, E., C. Baker, and R. Cracknell. 2020. “General Election
2019: Full Results and Analysis.” House of Commons
Library. https://commonslibrary.parliament.uk/research-briefings/cbp-8749/.
Van Goethem, A., A. Reimer, B. Speckmann, and J. Wood. 2014.
“Stenomaps: Shorthand for Shapes.” IEEE Transactions on
Visualization and Computer Graphics 20 (12): 2053–62. https://doi.org/10.1109/TVCG.2014.2346274.
Visvalingam, M. 1981. “The Signed Chi-Score Measure for the
Classification and Mapping of Polychotomous Data.” The
Cartographic Journal 18 (1): 32–43. https://doi.org/10.1179/caj.1981.18.1.32.
White, T. 2017. “Symbolization and the Visual
Variables.” In The Geographic
Information Science &
Technology Body of
Knowledge, edited by John P. Wilson.
Wickham, H. 2010. “A Layered Grammar of Graphics.”
Journal of Computational and Graphical Statistics 19 (1): 3–28.
https://doi.org/10.1198/jcgs.2009.07098.
———. 2014. “Tidy Data.” Journal of
Statistical Software 59 (10): 1–23. https://doi.org/10.18637/jss.v059.i10.
Wickham, H., M. Çetinkaya-Rundel, and G. Grolemund. 2023. R for
Data Science: Import,
Tidy, Transform, Visualize, and
Model Data. Second. Sebastopol, CA:
O’Reilly Media.
Wickham, H., D. Cook, H. Hofmann, and A. Buja. 2010. “Graphical
Inference for Infovis.” IEEE Transactions on Visualization
and Computer Graphics 16 (6): 973–79. https://doi.org/10.1109/TVCG.2010.161.
Wickham, H., and G. Grolemund. 2017. R for Data
Science: Import, Tidy,
Transform, Visualize, and Model
Data. Sebastopol, CA: O’Reilly Media.
Wickham, H., D. Navarro, and T. Lin Pedersen. 2023. ggplot2: Elegant Graphics for Data
Analysis. 3rd ed. New York, NY: Springer.
Wilkinson, L. 1999. The Grammar of
Graphics. New York, NY: Springer.
Wolf, L. J., L. Anselin, D. Arribas-Bel, and L. Rivers Mobley. 2021.
“On Spatial and Platial Dependence: Examining Shrinkage in
Spatially Dependent Multilevel Models.” Annals of the
American Association of Geographers 111 (6): 1679–91. https://doi.org/10.1080/24694452.2020.1841602.
Wood, J., J. Dykes, and A. Slingsby. 2010. “Visualisation of
Origins, Destinations and Flows
with OD Maps.” The Cartographic
Journal 47 (2): 117–29. https://doi.org/10.1179/000870410X12658023467367.
Wood, J., P. Isenberg, T. Isenberg, J. Dykes, N. Boukhelifa, and A.
Slingsby. 2012. “Sketchy Rendering for
Information Visualization.” IEEE
Transactions on Visualization and Computer Graphics 18 (12):
2749–58. https://doi.org/10.1109/TVCG.2012.262.
Wood, J., A. Kachkaev, and J. Dykes. 2018. “Design
Exposition with Literate
Visualization.” IEEE Transactions on
Visualization and Computer Graphics 25 (1): 759–68. https://doi.org/10.1109/TVCG.2018.2864836.
Wood, J., A. Slingsby, and J. Dykes. 2011. “Visualizing the
Dynamics of London’s
Bicycle-Hire Scheme.”
Cartographica: The International Journal for Geographic Information
and Geovisualization, no. 4: 239–51. https://doi.org/10.1179/000870410X12658023467367.
Yang, F., M. Cau, C. Mortenson, H. Fakhari, A. D. Lokmanoglu, J.
Hullman, S. Franconeri, N. Diakopoulos, E. C. Nisbet, and M. Kay. 2024.
“Swaying the Public? Impacts of Election Forecast Visualizations
on Emotion, Trust, and Intention in the 2022 U.S.
Midterms.” IEEE Transactions on Visualization and Computer
Graphics 30 (1): 23–33. https://doi.org/10.1109/TVCG.2023.3327356.
Yang, Y., R. Beecham, A. Heppenstall, A. Turner, and A. Comber. 2022.
“Understanding the Impacts of Public Transit Disruptions on
Bikeshare Schemes and Cycling Behaviours Using Spatiotemporal and
Graph-Based Analysis: A Case Study of Four
London Tube Strikes.” Journal of
Transport Geography 98: 103255. https://doi.org/10.1016/j.jtrangeo.2021.103255.