SCIENCE@home

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

G. McInerny,Min Chen,Robin Freeman,D. Gavaghan,Miriah D. Meyer,Francis Rowland,D. Spiegelhalter,Moritz Stefaner,Geiziane Tessarolo,Joaquín Hortal

Published 2014 in Trends in Ecology & Evolution

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.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-78 of 78 references · Page 1 of 1

CITED BY

Showing 1-100 of 147 citing papers · Page 1 of 2

12
Next