BLOG POSTS

When considering the trajectory and development of the data visualisation field I contemplate the dual role of the scientific and creative communities: I believe scientists tell us what we should do and creatives tell us what we could do.

As I am in the process of writing my book I find that the same challenges in the use of language crop up. The main one I have difficulty being consistent about is how to term the person who reads, uses, consumes etc. visualisation work. Especially, when I am constructing a sentence that really needs a singular catch-all label and not a multi-comma-separated list – that just makes it clumsy both to write and to read.

With the dust settling after the UK elections, a brief reflection on the winners and losers from a data and visualisation perspective. I have selected two of each as follows…

Back in January I claimed that I would be hitting the new year with plans of more frequent smaller posts to offer ‘some practical tidbits most probably relating to quite narrow design considerations’. That lasted for about a week, so its certainly long overdue that I pick this back up.

It is always a privilege to be asked to give talks and this last week I’ve given two more at the National Audit Office as well as a webinar for Tableau. As many people like to have access to the slide content after each talk I don’t mind at all sharing them.

Earlier this week TheUpshot published a new interactive project visualising the ‘Yield Curve’. Created by Gregor Aisch and Amanda Cox the work provides a “3-D view of a chart that predicts the economic future”.

During the week I posted an article about some of the issues and options around using colour to represent gender (that is, the binary of Male or Female). I included a one-question poll to gather some insights about the attitudes out there towards the use of colour with gender.

A quick post to share something that I’ve been really in to this past week or so: dendrochronology. Also known as tree-ring dating, it is the “scientific method of dating based on the analysis of patterns of tree rings”.

You work you’re way through the data, come up with an idea for the most interesting angle of analysis, chart your data, and delight yourself with the compelling emerging display: look how clearly it shows the difference between men vs. women!

One of the frequent questions I get asked, particularly by people from a scientific or financial domain, is how to effectively visualise uncertainty of data and of statistics. My response is usually to make suggestions around annotated markings and/or colour gradients to indicate increasing or declining certainties.