Data Visualisation Week 1: Represent I CAN

One of the first challenges we faced was defining data visualisation and we do so by looking for five identifiable characteristics. Characteristics that I remember by using the mnemonic Represent I CAN.

Representation
Data visualisations obviously represents complex data in a graphical form but should also be more effective at representing this data than other methods. The act of visual representation should help us understand and interpret the data in ways other representations couldn’t.

Interaction
Data visualisation frequently allows users control over the navigation and exploration of data elements. This perhaps characterises data visualisations from infographics which are more commonly static.

Connection
Good data visualisations should allow data to be compared and contrasted. This makes data visualisation quite contextual and should allow the user to see different aspects of the data side by side as part of their analysis.

Aesthetic
Whilst data visualisations are useful, their analytical function is complemented by beautiful design aesthetics to encourage engagement.

Narrative
A data visualisation should take a user on a journey from a question to a clear answer without extraneous elements.

Visualising race data by Tanya Bibikova, Sergey Dolinin, Gleb Arestov (Data Laboratory).  Source: Information is Beautiful Awards Showcase

These characteristics can help us with design but they can also help us evaluate data visualisations. To practice applying these characteristics we looked at visualisations from the 2014 Information is Beautiful awards showcase and the Hubway Data Visualisation challenge and critically appraised selected examples justifying whether we thought they were good or bad examples using these characteristics.

The Hubway example is particularly interesting as a) these all use the same data b) they have award categories for different characteristics, such as aesthetics, narrative and exploration, as well as an overall winner suggesting that a data visualisation can emphasise one characteristic over the others or attempt a balance and occupy a broad spectrum from art to analytics.

I’m interested in information behaviour in sporting domains so from the Information is Beautiful Awards I particularly liked the White Nights Marathon Results which represented the flow of a race as an “interactive running map” overlaid onto a map of the race route around St Petersburg. It was certainly one of the most interesting, interactive, aesthetic and engaging ways I’ve seen race results and an unfolding race narrative visualised.


Code:
Week 1 Gist on Github
DataViz Github Repository


Featured Visualisation Image Credit:
The Data Centric Universe by Jan Willem Tulp.
Source: Visualizing.org (CC BY-NC-SA 3.0)


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