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DOI: 10.1016/j.tree.2014.01.003
论文题名:
Information visualisation for science and policy: Engaging users and avoiding bias
作者: McInerny G.J.; Chen M.; Freeman R.; Gavaghan D.; Meyer M.; Rowland F.; Spiegelhalter D.J.; Stefaner M.; Tessarolo G.; Hortal J.
刊名: Trends in Ecology and Evolution
ISSN: 1695347
出版年: 2014
卷: 29, 期:3
起始页码: 148
结束页码: 157
语种: 英语
Scopus关键词: biodiversity ; ecosystem service ; information ; information management ; visualization ; computer program ; computer simulation ; ecosystem ; environmental protection ; geography ; human ; information processing ; interpersonal communication ; methodology ; policy ; review ; Communication ; Computer Simulation ; Conservation of Natural Resources ; Data Display ; Ecosystem ; Geography ; Humans ; Public Policy ; Software
英文摘要: 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. © 2014 Elsevier Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/67245
Appears in Collections:全球变化的国际研究计划
气候变化与战略

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作者单位: Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford, OX1 3QD, United Kingdom; Computational Science Laboratory, Microsoft Research Ltd, 21 Station Road, Cambridge, CB1 2FB, United Kingdom; Oxford E-science Research Centre, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, United Kingdom; Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, United Kingdom; Scientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT 84112, United States; EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom; Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge, Cambridge, CB3 0WB, United Kingdom; 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

Recommended Citation:
McInerny G.J.,Chen M.,Freeman R.,et al. Information visualisation for science and policy: Engaging users and avoiding bias[J]. Trends in Ecology and Evolution,2014-01-01,29(3)
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