Improving the visual communication of environmental model projections.
Improving the visual communication of environmental model projections.
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DOI：
10.1038/s41598-021-98290-4
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发表时间：
2021-09-27
影响因子：
4.6
通讯作者：
Webb TJ
中科院分区：
文献类型：
--
作者：
Bannister HJ;Blackwell PG;Hyder K;Webb TJ
环境和生态系统模型可以通过在一组共同的情景下预测未来的替代状态，帮助指导对不断变化的自然系统的管理。将对比模型组合成多模型集合（MME）可以提高预测的技能和可靠性，但相关的不确定性使输出的沟通复杂化，影响管理决策的有效性，有时还影响公众对科学证据本身的信任。有效的数据可视化可以在准确传达这些复杂结果方面发挥关键作用，但我们缺乏证据基础，使我们能够设计出具有视觉吸引力的数据，同时有效地传达准确的信息。为了解决这个问题，我们进行了一项调查，以确定最有效的方法来可视化传达全球气候模型集合的输出。我们测量了调查参与者能够以不同的方式解释10个描绘同一组模型输出的可视化的准确性，信心和易用性，以及他们的偏好。点图和箱形图优于所有其他可视化，热图和雷达图相对无效，而我们的信息图在视觉吸引力方面得分很高，但缺乏准确解释所需的信息。我们提供了一套指导方针，用于在广泛的研究领域中直观地传达MME的输出，旨在最大限度地发挥可视化的影响，同时最大限度地减少误解的可能性，增加模型的社会影响，并确保它们能够在未来支持管理。
Environmental and ecosystem models can help to guide management of changing natural systems by projecting alternative future states under a common set of scenarios. Combining contrasting models into multi-model ensembles (MMEs) can improve the skill and reliability of projections, but associated uncertainty complicates communication of outputs, affecting both the effectiveness of management decisions and, sometimes, public trust in scientific evidence itself. Effective data visualisation can play a key role in accurately communicating such complex outcomes, but we lack an evidence base to enable us to design them to be visually appealing whilst also effectively communicating accurate information. To address this, we conducted a survey to identify the most effective methods for visually communicating the outputs of an ensemble of global climate models. We measured the accuracy, confidence, and ease with which the survey participants were able to interpret 10 visualisations depicting the same set of model outputs in different ways, as well as their preferences. Dot and box plots outperformed all other visualisations, heat maps and radar plots were comparatively ineffective, while our infographic scored highly for visual appeal but lacked information necessary for accurate interpretation. We provide a set of guidelines for visually communicating the outputs of MMEs across a wide range of research areas, aimed at maximising the impact of the visualisations, whilst minimizing the potential for misinterpretations, increasing the societal impact of the models and ensuring they are well-placed to support management in the future.
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影响因子：
2.5
作者：
Dahshan, M.;Polys, N. F.;Pollyea, R. M.
通讯作者：
Pollyea, R. M.
DOI：
10.1083/jcb.200611141
发表时间：
2007-04-09
期刊：
The Journal of cell biology
影响因子：
--
作者：
Cumming G;Fidler F;Vaux DL
通讯作者：
Vaux DL
DOI：
10.1109/tvcg.2006.163
发表时间：
2006-09-01
影响因子：
5.2
作者：
Heer, Jeffrey;Agrawala, Maneesh
通讯作者：
Agrawala, Maneesh
影响因子：
3.5
作者：
Frewer, L
通讯作者：
Frewer, L
影响因子：
4.4
作者：
Daron, Joseph D.;Lorenz, Susanne;Jack, Christopher
通讯作者：
Jack, Christopher