Provision of cycle spaces – HESA Estates Management Record

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.png