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Visual Display of Quantitative Information
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La Representación Visual de Información
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Data Analysis for Politics and Policy, $2
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Presenting Data and Information
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Graphic Visualization of Risks
Does anyone have references to good examples of ways to display Risks? A risk is multi-faceted with factors such as Probability, Consequence, Cost, and Age among others. How can these many dimensions be shown in a cohesive picture?
-- Chris Kearns (email)
From informationdesign.org, here is a reference:
Warnings and risk communication: Guidance for healthcare
facilities, edited by Michael S. Wogalter, David M. DeJoy, Kenneth
SUMMARY: Questions regarding how best to communicate
and risk information, whether such communications are
likely to be effective, and what factors influence the
communication process are of importance to today's
society. Stimulated by the tremendous growth in
litigation on product liability and associated
personal injury, research into communicating warnings
effectively has developed rapidly over the last few
years. This book addresses the major issues in theory,
research and applications of warnings and risk
communication, bringing together leading international
authorities in the field.
Part 1. Introduction
1 Overview (K.R. Laughery, A. Hammond)
2 Organizing theoretical framework: a consolidated
communication-human information processing (C-HIP) model
(M.S. Wogalter, D.M. DeJoy, K.R. Laughery
Part 2. Methods/techniques
3 Intermediate processing stages: methodological
for research on warnings (S.L. Young, D.R. Lovvoll)
4 Methodological techniques for evaluating behavioral
and compliance (M.S. Wogalter, T.A. Dingus)
Part 3. Research on warnings: stages of the model
5 Source (E.P. Cox III)
6 Channel (M.B. Mazis, L.A. Morris)
7 Attention capture and maintenance (M.S. Wogalter,
8 Comprehension and memory (S.D. Leonard, H.Otani,
9 Attitude and beliefs (D.M. DeJoy)
10 Motivation (D.M. DeJoy)
11 Behaviour (N.C. Silver, C.C Braun)
Part 4. Practical issues of warning design
12 Standards and government regulations in the USA
13 Practical considerations regarding the design and evaluation
of product warnings (J.P. Frantz, T.P. Rhoades, M.R. Lehto)
Part 5. Forensics
14 T he law relating to warnings (M.S. Madden)
15 The expert witness (K.R. Laughery)
Hardback: 25,5 x 17,5 cm, 384 pages, illustrated
Price: GBP 54.95
Published: September 1999
Publisher: Taylor & Francis
There is an excellent book by Mark Monmonier titled "Cartographies of Danger." There is some excellent discussion throughout on the presentation of hazard (which threatens life or property) as opposed to risk (the probability of a threat being realized), which may be helpful to you.
-- Stephany (email)
Hillary "Holly" Hosmer has presented a paper on visualizing qualitative risk factors in risk analysis. The only quantitative display she covers is the Cost/Loss (lives, dollars, objects).
NIST-sponsored conference paper: Visualizing Risks: Icons for Information Attack Scenarios, Hilary H. Hosmer Data Security, Inc. PDF NIST.GOV.
At first glance, it might appear to be an exercise in "chart junk". However, given the use tree concepts and tree/network diagrams in risk and fault analysis, there is a need to lift the cognitive level from tree-of-words to tree-of-concepts. It's in that (unstated) context that she searchs for expressive Icons that can be used as "selective" elements in Network Diagrams of risk relationships. This is outside the realm of chart/table I.D. data-graphics, but still within the realm of I.A. and on the edges of Bertins larger classification scheme. I don't know if she's had research funding for the next, quantitative, step, which is what the questioner was directly requesting. Chris might ask her directly, if she doesn't reply to my answer.
Full Disclosure -- You'll find my name in the Acknowledgements, near another name familiar to all readers of this forum. Back when I was researching in Risk Analysis, E.T. only had the first book out and we were still worrying about how to compute the probabilities and measures; how to present it was not yet a concern for most in the field.
-- Bill Ricker (email)
M Granger Morgan and Max Henrion report some experiments in visualising probability distributions in "Uncertainty" published in 1990 by the Cambridge University Press.
-- Matthew Leitch (email)
Searches on Google, Google Scholar, and PubMed reveal that most current evidence indicates beauty recognition is an evolutionary trait that reduces risk in mate selection.
Aharon, et al, published this study in Neuron in 2001: Beautiful Faces Have Variable Reward Value: fMRI and Behavioral Evidence. From the abstract:
In this study, discrete categories of beautiful faces are shown to have differing reward values and to differentially activate reward circuitry in human subjects. In particular, young heterosexual males rate pictures of beautiful males and females as attractive, but exert effort via a keypress procedure only to view pictures of attractive females. Functional magnetic resonance imaging at 3 T shows that passive viewing of beautiful female faces activates reward circuitry, in particular the nucleus accumbens. An extended set of subcortical and paralimbic reward regions also appear to follow aspects of the keypress rather than the rating procedures, suggesting that reward circuitry function does not include aesthetic assessment.
Some additional work on the attractiveness problem done by some German students is available at their Beauty Check site.
Anatomically, the nucleus accumbens is deep in the brain, near the brain stem. It is an old part of the brain in evolutionary terms and far removed from the prefrontal cortex, the area of the brain commonly associated with risk assessment and other "executive" functions. The prefrontal cortex is new in evolutionary terms and doesn't fully mature in humans until 25 years of age. Thus this risk assessment may be highly formalized in the mature mind, automated, and not interfered with by conscious thought.
-- Niels Olson (email)
A useful review article, "Visualizing uncertainty about the future," has just been published in Science [DOI: 10.1126/science.1191181].
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.
The article itself is paywalled, but the interesting supplementary text and interactive
graphics are freely available. The movies are hosted at the authors' web site, understandinguncertainty.org.
-- Alexey J. Merz (email)
The 2011 Wisconsin Crash Calendar
This is a "pure" data visualization, in that the data are the graphic. You can learn more about the project and download
the 2011 Wisconsin Crash Calendar here: http://www.ghsa.org/html/resources/showcase/wi1.html
and here: http://wisconsinsafetydataportal.org/index.cfm/wi-crash-calendar/
The linked version is graphical and does not display the number of actual crashes, although that is a display option. The
data can be recalculated for one or more counties or agencies. Another version uses the same categories without the
property damage crashes, which provides an interesting comparison. A Crash Calendar using preliminary 2012 data will
My larger goal is to "webize" this to create an interactive visualization that includes choropleth maps.
I would be very interested in comments or suggestions.
Joni Graves, AICP
LTAP Transportation Information Center,
Department of Engineering Professional Development
University of Wisconsin-Madison
-- Joni Graves (email)