Art is a vast and ever-intriguing phenomenon. There are many ways to explore artistic creations and the communities surrounding the endeavour. As a collective, it can be visualised with time, as constellations of clusters, as abstracted agents, and via human-defined categories. This project is an attempt to gleam some insight from artistic works when considered within the creative community that is DeviantArt.
This project was undertaken whilst at the University of California, San Diego (UCSD), under the mentorship of Lev Manovich, in Data Visualisation, at the Software Studies Lab (2012).
Visual artworks and their metadata were analysed and visualised in an iterative process to gain insights which could be refined into reports and posters.
Tools used included R, Mondrian, Excel, Processing, Java, Photoshop, Illustrator, InDesign.
Report 1: Clustering DeviantArt Artworks
Here, artworks were spatially clustered by their visual characteristics to uncover insights. The two posters produced were designed in conjunction with Teenah Eco who filtered through the data I visually analysed, transforming them into the lovely posters here.
Process and findings are in the report 'Clustering DeviantArt Artworks'.
Report 2: Exploring DeviantArt Categories
DeviantArt Categories also proved to be an intriguing data source for gathering insights.
Process and findings are in the report 'Exploring DeviantArt Categories'.
The above reports describe their associated processes. Additional learnings were derived from exploring DeviantArt as a whole, comic book data, and by building an interactive installation with Cooper Hewitt - Smithsonian Design Museum data. Links to these explorations are found in my blog post.