Having spotted the cycle spaces tab on the HESA Estates Management Record I couldn’t pass up the opportunity to have a go at visualising this comparatively simple data set.

The intial question

Q1 – How do providers stack up in the provision of cycle spaces?

TOP10 HE Cycles spaces

This initial viz doesn’t have much by way of interactivity, it’s an info-graphic to introduce the user to the topic and hopefully pull the viewer into the subject in question, a term i’m coining #coffeetableviz.

This TOP10 HE Cycle spaces viz also has a secondary tab (not many people publish a second tab in a tableau publisphere, and that’s because……. no one really looks at the second tab! (The ‘why’ is probably best left for a different post) however go on take a peek..!

For me this headline visual falls a little short, simply ranking an institution based on the absolute volume may be misleading, and may just favor the larger universities, or those in particular regions that are naturally more likely cycle due to locale factors. So to address this I combined the staff and student fte data provided in Estates management record with the cycle space data. Cue Q2…

Q2 – What is the total number of spaces as a ratio of the population at a provider?

FTE per cycle space

Anything else?

It would seem a shame if i didn’t combine this cycle space viz with my first post focusing on method of commute, therefore my Q3 evolved to be something like this:

Q3 – What is the realistic likelihood of me getting a cycle space if I worked or studied at provider ‘X’…….

Take an explore of the exploratory viz below for insight into higher education providers; provision, volume and likelihood of grabbing one of the prized cycle spaces. Thus, avoiding security staff issuing parking infringement warnings, or worse still confiscating your bike because its parked inappropriately.

Furthermore…. Could this be the first in a data driven plot for a Hollywood blockbuster sequal to Field of dreams, where university ‘X’ struggling for student numbers, builds an extraordinarily large number of cycle spaces, convinced that if we build it he will come…… would the question of correlation or causality be scrutinised too heavily in a blockbuster plot?

Create the spaces and they will come

Hope you enjoyed this second #VisualisingHE post focusing on Estates Management data 2014/5.

Adam

About the data set 

Data about Environmental Information for UK higher education providers is collected by HESA (Higher Education Statistics Agency) annually as part of the Estates Management record. This free table includes information about each UK provider, covering a variety of environmental information including;

• Grounds and buildings
• Water and energy usage
• Waste management
• Transport
• Other environmental measurements.

For this post I have used the 2014/5 submission, which is the most up to date publication available at the time of writing. For those not so familiar with HESA time frames you might feel it’s a bit odd that data relating to the academic year 2014/5 is the most up to date given we are in March 2017….  however HESA collect data relating to a reporting period of 01 August in year 1 to 31 July in year 2 and publish the results annually after the submission window.

Finding a topic

Having had a bit of a play in the excel file, Transport info caught my eye, so I decided I would begin my journey into #VisualisingHE Estates Management data with the following question:

Q1 – How do staff and students commute to university?

First off, I wanted to understand the distribution of different modes of travel taken by staff and students, provider by provider. The viz below shows how staff and students from the University of East Anglia commute to work or study. You can explore all providers on my Tableau Public dashboard ‘How do you commute‘. An iphone version is also available so that I can see it on my preferred device.

Method of travel single provider overview

In summary, it is probably no surprise that traveling by car is the most common method of travel overall, but I hope, that visualising the data in this way helps understand provider locale and method of travel trends regionally and which providers are leading in what method.

Take a look at the exploratory dashboard on Tableau Public:

Regional method of travel

Thanks for reading.

Adam