Graphing Artists’ Books: Visualizing Connections within Vanderbilt’s Collection of Southern Presses

This exhibition highlights a selection of artists' books pubulished in southern states from the Vanderbilt University Special Collections Library in conjunction with a Neo4j Social Network Analysis, visualized with Github's Graph Gist. 

Dean's Fellow Haley Brown (Class of '17) began this project in Fall 2015, by analyzing a selection of of artists' books, recording specific information from the books themselves, and contacting artists on an individual basis to discover important relationships within their artistic communities. 

These relationships, ranging from types of books published, schools attended and education received, mentorships and programs attended, artistic collaborations, and more, were encoded in the Neo4j graph database as a series of nodes (a computer science term meaning any connection on a network or graph). The nodes were then displayed with Graph Gist and the Cypher query language. The process of data collection, code writing, and correspondence with the numerous artists represented in the collection has created a unique product that allows for a complex and revealing reading of our artists' books and the wider artists' book community across the nation. 

Some findings from this project were presented at the College Book Art Association (CBAA) conference lecture in January 2016. 


  • Books added to the collection after August 2015 have not been included
  • Some of the more detailed information about artists included in the gist (i.e. mentorships) was obtained through direct correspondence with the artists. Not all artists responded or chose to share information for certain questions. Gaps in the datset reflect this dynamic.  

*The working definition for the "South" mirrored the U.S. Census Bureau's, which includes: Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia, Delaware, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, and Texas.