Information Visualisation for Science and Policy: Engaging Users and Avoiding Bias. McInerny, G. J., Chen, M., Freeman, R., Gavaghan, D., Meyer, M., Rowland, F., Spiegelhalter, D. J., Stefaner, M., Tessarolo, G., & Hortal, J. 29(3):148–157. ![Information Visualisation for Science and Policy: Engaging Users and Avoiding Bias [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex [Highlights] [::] Science and policy rely on reliable and unbiased communications. [::] Visualisations and graphics are a powerful means to communicate. [::] Ecology lacks appropriate expertise, skills, and knowledge in visualisation. [::] Great opportunities are available if we rethink the role of visualisation in our work. [::] The way we think about visualisation needs to be reframed within our disciplines. [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.
@article{mcinernyInformationVisualisationScience2014,
title = {Information Visualisation for Science and Policy: Engaging Users and Avoiding Bias},
author = {McInerny, Greg J. and Chen, Min and Freeman, Robin and Gavaghan, David and Meyer, Miriah and Rowland, Francis and Spiegelhalter, David J. and Stefaner, Moritz and Tessarolo, Geizi and Hortal, Joaquin},
date = {2014-03},
journaltitle = {Trends in Ecology \& Evolution},
volume = {29},
pages = {148--157},
issn = {0169-5347},
doi = {10.1016/j.tree.2014.01.003},
url = {https://doi.org/10.1016/j.tree.2014.01.003},
abstract = {[Highlights]
[::] Science and policy rely on reliable and unbiased communications. [::] Visualisations and graphics are a powerful means to communicate. [::] Ecology lacks appropriate expertise, skills, and knowledge in visualisation. [::] Great opportunities are available if we rethink the role of visualisation in our work. [::] The way we think about visualisation needs to be reframed within our disciplines.
[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.},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13073657,~to-add-doi-URL,cognitive-biases,science-policy-interface,scientific-communication,technology-mediated-communication,uncertainty,visual-notation,visualization},
number = {3}
}
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