Data visualisation: Contributions to evidence-based decision-making
Read the whole report here
Imogen Robinson at SciDev has just published a report for researchers thinking about whether data visualisations could get more people to read and act on their research.
They've talked to a lot of people from different countries and different types of organisations, as well as including some interesting analytics from their own articles that show how much higher interest and engagement is when an article includes a visualisation.
We've picked out four key questions that the report suggests anyone should asks before they decide to create a visualisation to summarise their research:
Is high-quality, interesting data available?
Does your target audience have the capacity to access and understand data visualisations? This can include skills related to things such as language, statistics, visual literacy, computers and critical thinking, all of which earlier research suggests influence how people interact with visualations. It also means thinking about whether the audience have the bandwidth and technology to view the visualisation.
Do you have the production skills to make visualisations on your team, or can you access them? Priority skills are data analysis, visual design, digital skills, and storytelling or journalism skills.
Do you have organisational buy-in to build a team to work on visualisations and invest in developing these skills?
They also suggest some hypotheses for what makes visualisations most effective:
Data visualisations are most effective when they are based on topical issues.
Data visualisations should be tailored to the target audiences’ interests and needs to be most effective.
[Data visualisations] that follow good design principles and provide clear links to the original data are likely to be most effective.
It would be great to test these empirically in future.
