Visualisation has been on my mind this week. Four separate alerts have directed my attention.
1. IEEE Call
On Wednesday, the IACSS listserv brought news from Dietmar Saupe about a special issue of IEEE’s Computer Graphics and Applications special issue on sports data visualization. Final submissions are due on 1 January 2016 for a publication date in September/October 2016.
The editors for this special issue are Rahul Basole (Georgia Institute of Technology) and Dietmar Saupe (
- Player and team management
- Sports media and entertainment
- Operational management
- Sports medicine applications
- Personal fitness and sports data
- Domain studies
2. Ben Mayhew
Ben shared his his visualisation of Championship football matches played in the first wek of the 2015-2016 football season in England. His post plots the cumulative quality of both teams’ shots in each Championship match “expressed in Expected Goals, over the course of each match, to illustrate how it unfolded and whether the result reflected the chances created”.
Ben’s post provides a link to a detailed explanation of how he has visualised the Expected Goals data. I think this is an excellent resource.
Unsurprisingly, given Ben’s commitment to CC licensing, he gives explicit thanks to Michael Caley, Sander Itjsma and Ben Huxley in connection with his work.
3. Andy Kirk
Yesterday, Andy presented some alternatives to BBC football graphics presented in this post about the Premier League..
His post uses two graphics to illustrate different approaches to the same data.
Andy shows how replacing a radar chart with a connected dot plot (“Radars really only make sense if and when there is some compelling logic for the radial arrangement of values (usually temporal, spatial or, occasionally, intuitive groups)”) helps understanding.
His second example replaces a donut chart with with a stacked bar chart.
Andy observes in his conclusion:
Comparing the before/after versions I suspect that the labelling size and prominence of colour of my redesigns would need fine-tuning. It is interesting to see how faded they look when you shrink the final png file down. In the native Illustrator version they look far more vivid to the naked eye. That’s a good lesson in testing out your prototype designs in the size and setting in which they are likely to exist, to see for yourself how they look. Anyway, I’ve not got time to undertake endless iterations but you get the idea.
4. Applications
This morning, I received an alert from the Report App. In it there were links to some visualisation applications I had not used previously. These included:
I have started using these to compare how they might treat the same data.
Audiences and Messages
Ben and Andy’s posts were great additions to my week.
In the introduction to their e-book on Data and Design (2014), Trina Chiasson and her colleagues at Infoactive note Maria Popova’s (2009) description of data visualisation at “the intersection of art and algorithm”. Maria adds:
Ultimately, data visualization is more than complex software or the prettying up of spreadsheets. It’s not innovation for the sake of innovation. It’s about the most ancient of social rituals: storytelling. It’s about telling the story locked in the data differently, more engagingly, in a way that draws us in, makes our eyes open a little wider and our jaw drop ever so slightly. And as we process it, it can sometimes change our perspective altogether.
I wondered how such storytelling might occur in the IEEE special issue. I am keen to submit a paper for review. Ben and Andy have opened my eyes wider this week and prompted jaw dropping.
The arrival of the Report App alert has given me more opportunity to explore how to share information visually.
Photo Credit
Dandelion wish (88/365) (John Liu, CC BY 2.0)