{"id":9515,"date":"2018-05-09T10:31:18","date_gmt":"2018-05-09T14:31:18","guid":{"rendered":"http:\/\/studentwork.prattsi.org\/infovis\/?p=9515"},"modified":"2018-05-13T13:47:45","modified_gmt":"2018-05-13T17:47:45","slug":"networked-tagp","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/projects\/networked-tagp\/","title":{"rendered":"The Networked Art Genome Project"},"content":{"rendered":"

Introduction<\/b><\/h1>\n

This report explores categorical and hierarchical data from The Art Genome Project (\u201cTAGP\u201d), Artsy\u2019s ongoing study into the characteristics and connections between artists and artworks, using Gephi, an open-source network analysis and visualization software. The goal of the resulting network visualization is to graphically represent abstract information hierarchies, providing a shared point of reference for internal stakeholders at Artsy. Research into the mental models of TAGP\u2019s abstract hierarchy for typical users was conducted through an unmoderated card sort on a thematic subset of the genome using Optimal Workshop, a proprietary web-based platform that offers a suite of user testing tools. Recommendations for future iterations of this visualization based on this user research is included as well.<\/span><\/p>\n

Background<\/span><\/span><\/h3>\n

As described in my previous posts \u201c<\/span>Visualizing Dynamic Hierarchies in The Art Genome Project<\/span><\/a>\u201d and \u201c<\/span>From Treemaps to Network Graphs: Further Visualizations of Hierarchical Relationships in The Art Genome Project<\/span><\/a>,\u201d Artsy\u2019s mission is to make all the world\u2019s art accessible to anyone with an internet connection. By partnering with the world\u2019s leading art auctions, galleries, fairs, and museums, the site functions as a free and powerful resource for users interested in art collecting and education. At present, there are over 900,000+ works of art and design published on the platform by more than 100,000 artists and cultural makers.<\/span><\/p>\n

The Art Genome Project is the classification system and technological framework that fuels Artsy. TAGP maps the characteristics, referred to as “genes” in-house, that connect artists, artworks, architecture, and design objects across time. There are currently over 1,300 genes of more than 40 types covering art-historical movements, subject matter, formal qualities, and more. Importantly, unlike tags, which are binary\u2014something is either tagged “chair” or not\u2014a gene is evaluated on a scale from 0-100 and then hand applied to an artist or artwork record by an expert contributor. While TAGP also uses tags to highlight specific iconography, motifs, and subject matter, dynamic genoming allows for greater nuance when capturing the conceptual and formal aspects of cultural heritage records.<\/span><\/p>\n

TAGP is a semi-structured controlled vocabulary, however it is not in compliance with ISO 25964 or related standards (ISO, n.d.). Its information hierarchy is relatively flat, going two levels deep at most. To meet these standards and create a deep taxonomy that is truly user-friendly, visualizing its current structure and identify areas that are working and, conversely, need improvement to prioritize future iterations is of highest priority to the genome team.<\/span><\/p>\n

Previous work in Tableau Public resulted in a unified dashboard that visualizes quantitative analytic data through line graphs, packed bubble charts, and treemaps, while hierarchical connectivity one level deep was visualized with Gephi. This project extends the latter visualization, attempting to not only add another level of hierarchy to the graph but also to incorporate user experience research, narrowing the scope of the visualization and iteratively improving on the design.<\/span><\/p>\n

Methodology<\/b><\/h1>\n

Card Sorting<\/span><\/span><\/h3>\n

Card sorting is a user experience (UX) research technique in which users organize individual topics into groups according to criteria that make sense to them (Sherwin, 2018). This technique is noted for its usefulness in identifying issues with a product\u2019s category structures, such as the information architecture on a website, by uncovering how users think about content. Open, unmoderated card sorting (versus closed or moderated) was selected due to its flexibility and speed\u2014users can organize content into groups with an online tool on their own time and results are immediately available for analysis. Extensive in-person debriefing was used to gain qualitative insights into users\u2019 rationale that might not have been discovered during the largely unmoderated session.<\/span><\/p>\n

Of the 1,303 genes that comprise The Art Genome Project, 219 Content (e.g. \u201c<\/span>Landscapes<\/span><\/a>,\u201d \u201c<\/span>Portrait<\/span><\/a>\u201d) and Concept (e.g. \u201c<\/span>Political<\/span><\/a>,\u201d \u201c<\/span>Popular Culture<\/span><\/a>\u201d) genes were selected as a subset for card sorting. This is an exceptionally large number of cards to work with, however the eight users selected were all TAGP catalogers (\u201cgenomers\u201d) and considered domain experts. This TAGP gene data subset was created by running SQL queries in Looker, a proprietary data analytics platform, against Artsy\u2019s AWS Redshift data warehouse and exporting the results to a local CSV file. OptimalSort, a card sorting software by Optimal Workshop, was used to input the CSV file and configure the study.<\/span><\/p>\n

Target Audience<\/span><\/span><\/h3>\n

The following user profile for the target audience of TAGP\u2019s internal stakeholders and users is based on the demographics of past and present genomers:<\/span><\/p>\n