Literature DB >> 24565371

Information visualisation for science and policy: engaging users and avoiding bias.

Greg J McInerny1, Min Chen2, Robin Freeman3, David Gavaghan4, Miriah Meyer5, Francis Rowland6, David J Spiegelhalter7, Moritz Stefaner8, Geizi Tessarolo9, Joaquin Hortal10.   

Abstract

Visualisations and graphics are fundamental to studying complex subject matter. However, beyond acknowledging this value, scientists and science-policy programmes rarely consider how visualisations can enable discovery, create engaging and robust reporting, or support online resources. Producing accessible and unbiased visualisations from complicated, uncertain data requires expertise and knowledge from science, policy, computing, and design. However, visualisation is rarely found in our scientific training, organisations, or collaborations. As new policy programmes develop [e.g., the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES)], we need information visualisation to permeate increasingly both the work of scientists and science policy. The alternative is increased potential for missed discoveries, miscommunications, and, at worst, creating a bias towards the research that is easiest to display.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2014        PMID: 24565371     DOI: 10.1016/j.tree.2014.01.003

Source DB:  PubMed          Journal:  Trends Ecol Evol        ISSN: 0169-5347            Impact factor:   17.712


  10 in total

1.  The Evolution of Scientific Visualisations: A Case Study Approach to Big Data for Varied Audiences.

Authors:  Andrew J Lunn; Vivien Shaw; Isabelle C Winder
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 3.650

Review 2.  Multidimensional physical activity: an opportunity, not a problem.

Authors:  Dylan Thompson; Oliver Peacock; Max Western; Alan M Batterham
Journal:  Exerc Sport Sci Rev       Date:  2015-04       Impact factor: 6.230

3.  Tailoring the visual communication of climate projections for local adaptation practitioners in Germany and the UK.

Authors:  Susanne Lorenz; Suraje Dessai; Piers M Forster; Jouni Paavola
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2015-11-28       Impact factor: 4.226

4.  Funnel plots and choropleth maps in cancer risk communication: a comparison of tools for disseminating population-based incidence data to stakeholders.

Authors:  Walter Mazzucco; Rosanna Cusimano; Maurizio Zarcone; Sergio Mazzola; Francesco Vitale
Journal:  BMJ Open       Date:  2017-03-30       Impact factor: 2.692

5.  Estimating everyday risk: Subjective judgments are related to objective risk, mapping of numerical magnitudes and previous experience.

Authors:  Hannah A D Keage; Tobias Loetscher
Journal:  PLoS One       Date:  2018-12-05       Impact factor: 3.240

6.  ESPRES: A web application for interactive analysis of multiple pressures in aquatic ecosystems.

Authors:  Angel Udias; Alberto Pistocchi; Olga Vigiak; Bruna Grizzetti; Faycal Bouraoui; Cesar Alfaro
Journal:  Sci Total Environ       Date:  2020-07-11       Impact factor: 7.963

7.  Evaluating the usability and acceptability of a geographical information system (GIS) prototype to visualise socio-economic and public health data.

Authors:  Joshua Wells; Robert Grant; John Chang; Reem Kayyali
Journal:  BMC Public Health       Date:  2021-11-24       Impact factor: 3.295

8.  Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium.

Authors:  Neil Davies; Dawn Field; David Gavaghan; Sally J Holbrook; Serge Planes; Matthias Troyer; Michael Bonsall; Joachim Claudet; George Roderick; Russell J Schmitt; Linda Amaral Zettler; Véronique Berteaux; Hervé C Bossin; Charlotte Cabasse; Antoine Collin; John Deck; Tony Dell; Jennifer Dunne; Ruth Gates; Mike Harfoot; James L Hench; Marania Hopuare; Patrick Kirch; Georgios Kotoulas; Alex Kosenkov; Alex Kusenko; James J Leichter; Hunter Lenihan; Antonios Magoulas; Neo Martinez; Chris Meyer; Benoit Stoll; Billie Swalla; Daniel M Tartakovsky; Hinano Teavai Murphy; Slava Turyshev; Fernanda Valdvinos; Rich Williams; Spencer Wood
Journal:  Gigascience       Date:  2016-03-17       Impact factor: 6.524

9.  Explaining Spatial Variation in the Recording Effort of Citizen Science Data across Multiple Taxa.

Authors:  Louise Mair; Alejandro Ruete
Journal:  PLoS One       Date:  2016-01-28       Impact factor: 3.240

10.  Temporal degradation of data limits biodiversity research.

Authors:  Geiziane Tessarolo; Richard Ladle; Thiago Rangel; Joaquin Hortal
Journal:  Ecol Evol       Date:  2017-07-27       Impact factor: 2.912

  10 in total

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