I recently attended this dense two-day workshop run by Andy Kirk of Datavisualisation.com. It and introduces participants to a set of processes and critical analytical tools with which visualise data, defined as the visual (re)presentation of data to facilitate understanding. It does not cover information design, info-graphics or data art. There are around 15 participants.
Five stages of data visualisation are identified, ranging from formulating the brief and collecting data, to establishing editorial perspective and constructing the visual solution. The emphasis is on producing designs that are truthful, accessible and elegant. A key device is small group critiques. Participants are asked to critically evaluate selected visualisations and report on whether, for example, they liked and/or learned anything from them, how well colour has been used to enhance understanding and so on. For example, this graphic tends to be neither liked nor seen as informative because it makes random (therefore confusing) use of colour, scale and annotation. The most informative element is the subtitle (for detailed critique see here):
By contrast this interactive graphic from the OECD Better Life project tends to be regarded as both likeable and informative. It draws the audience in, and their time and effort are rewarded with increased understanding:
The workshop explores a wide range of resources, including the most distinctive 20 of the 300 odd visualisation tools currently available online. Special attention is drawn to:
- Import.io, a web-based tool which converts web pages into data
- Tableau.com, a tool for rapid visual analysis and more considered pieces available free to students, for a reduced fee to academics, and free to the general public in lighter form.
- R, an open source package akin to excel but with much better graphical tools
- Raw, an open web-based app that converts your data into a wide range of high quality visualisations in vector (i.e. infinitely scalable) format.
Datavisualisation.com is an excellent point from which explore the field. Note in particular:
- Resources page, which is a catalogue of the key data visualisation tools, including free online.
- Blog page, including the Collections tab, which has a monthly pick of data visualisations.
Keep an eye out for Kirk’s new book on the topic expected soon.
Thanks to Kent Q-Step for funding my attendance on the course.