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Trends Ecol Evol. 2014 Mar;29(3):148-57. doi: 10.1016/j.tree.2014.01.003. Epub 2014 Feb 21.

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

Author information

1
Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK; Computational Science Laboratory, Microsoft Research Ltd, 21 Station Road, Cambridge, CB1 2FB, UK. Electronic address: gmcinerny@hotmail.com.
2
Oxford E-science Research Centre, 7 Keble Road, University of Oxford, Oxford, OX1 3QG, UK.
3
Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
4
Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK.
5
Scientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT 84112, USA.
6
EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
7
Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge, Cambridge, CB3 0WB, UK.
8
Lilienthal, Germany.
9
Departamento de Ecologia, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, GO, Brazil; Departamento de Biogeografía y Cambio Global, Museo Nacional de Ciencias Naturales (CSIC), C/José Gutiérrez Abascal 2, 28006 Madrid, Spain.
10
Departamento de Biogeografía y Cambio Global, Museo Nacional de Ciencias Naturales (CSIC), C/José Gutiérrez Abascal 2, 28006 Madrid, Spain.

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.

PMID:
24565371
DOI:
10.1016/j.tree.2014.01.003
[Indexed for MEDLINE]
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