It’s April 2020, and as countries across the world find themselves under lockdown, I am inclined to do something fun with data for a change.

Rock climbing, particularly indoor bouldering has seen an explosion in popularity in recent years. Many people will be familiar with the concept, but here is a brief explanation; in this discipline, you climb a short wall using a sequence of holds, or ‘problem’, using your hand and feet, with no rope protection. These sequences are typically short, highly gymnastic and, when indoors, performed in a controlled environment. However, while most indoor climbing walls look like this:

My local climbing wall looks like this:

This beauty is the climbing wall at the University of Oxford Iffley Road Sports Centre. It is a fine example of pre-1990s climbing walls, before the advent of the modern climbing gym, with some unusual and curious features. First, unlike modern climbing walls where plastic holds are regularly replaced and reconfigured, here, climbing holds are permanent. You might notice they are chunks of rock literally cemented into the wall. Second, holds can be used across multiple sequences. This is particularly unusual, in that many sequences overlap over the same holds. As I sat here pondering, I became particularly interested to see if I could generate a visualisation that captured this feature of shared holds that is fairly unique.

Thankfully, two amazing climbers made this task possible; Steve Broadbent who literally wrote the (guide)book for the Iffley wall, and Jamie Bickers, who created and continues to curate a database of climbing problems at Iffley.

First: an explanation. I decided to interpret the climbing wall information as an undirected graph. This has three distinct advantages. First, a network graph allows relational information to be represented at multiple levels. This enables the user to easily answer both macro (e.g. how densely connected is the graph?) and micro (e.g. is there a connection between node A and B?) questions. Second, it allows for the representation of dense information. In this example, all holds (nodes) within a problem are connected to each other. The network is undirected, as climbing problem information is undirected – you are presented with a series of holds, but no instruction as to what order they should be arranged in. Finally, this visualisation allows the identification of ‘hubs’ – that is, nodes that serve as central connection points to join different parts of the graph. It is immediately striking that the arête forms a central hub. I’ll leave it to the reader to find other interesting features in the network.

Click for an interactive display.

Modern bouldering photo by Yns Plt on Unsplash. Original data generated by Steve Broadbent, Jamie Bickers, and many more Oxford University Mountaineering Club members. Network modelling in MATLAB and visualisation in Gephi. Web deployment with Sigma.js. Interactive network visualisation hosted on GitHub.