The goal of this section is to address issues related to data visualisation for scientific communication and outreach. This section is written for every person who might be interested in data visualisation, regardless of their academic field and background expertise. It aims at showing how effective data visualisation can be created with simple and accessible tools.
there is no clear cut rule on what you should/should not include in your charts. However, a good rule of thumb is to make editorial decisions beforehand; for example:
- what is your goal? e.g. informing/persuading
- what is the context? is it a visualisation to be included in a paper or part of an outreach event?
- what is your audience? is it knowledgeable?
- how will the visualisation be experienced, can people take their time to understand it in detail or does it have to be more immediate?
- what is the medium, will the figure be printed out, or visualised online?
keep in mind cognitive and perceptual constraints that might affect the data experience
different skills and backgrounds allow to think globally about issues in data visualisation. Specifically, while data science skills can help you with the technical side, awareness and knowledge of possible cognitive and perceptual constraints helps you exploit cognitive and perceptual boundaries and be mindful of cognitive and perceptual limitations which might affect the data fruition.
- excel (part of the office package)
- tableau (proprietary software, not very accessible unfortunately)
- ggplot (R package)
interactivity in charts can be useful but it can also be counterproductive. Specifically, when planning for interactivity in your charts, it is a good idea to keep in mind the editorial questions above and reflect on the best course of actions.