Working on the Artist Book Critical Index (ABCI), I’ve already gotten to work with data I really enjoy: linked data, the semantic web, distributed knowledge graphs. I enjoy ontology and vocabulary creation and being part of building semantic frameworks that other organizations can then pick up and use.

Angela Dressen’s “Cultural Heritage Data for Research – An Introduction” covers semantic web work in the art history space with clear appreciation and understanding, but in the Linked Art section, it also presents the idea that with proper tools, you then don’t need data scientists in the museum space.¹ The idea that if the structure’s in place and it’s easy enough to use, museums don’t need data professionals in permanent positions is part of why digital humanities projects fall short or become obsolete. When data projects are approached as short-term, quick-burst projects, they die out quickly. Not because the data isn’t good anymore or the tools are bad, but because there is no one cranking the engine to improve the data and move the project forward. If there’s one thing I’ve learned working on the ABCI, it’s that there has to be human energy for all aspects of the project, including the data handling and project maintenance.

The ABCI started as a Zotero library made by the Sloane Art Library’s now-retired manager, Josh Hockensmith, who is a book artist. He was making an index of reference works connected to artists’ books: where they were cited and on what page an image could be found. Graduate students were then assigned to the project and started expanding beyond UNC’s own collection by adding WorldCat links. It is a really unique, robust data set that could only come from human beings.

One of the key points Broman and Woo make in “Data Organization in Spreadsheets” is that the raw data should live in a different place than where it is analyzed and manipulated.² This was one of the untidiest aspects of the original Zotero ABCI library. The workflow for photographing artist books was living in the same Zotero, and it was difficult to untangle verified entries from unverified ones, even when they were marked with workflow tags.

We also had to deal with missing data, the equivalent of what Broman and Woo talk about with leaving cells empty.³ The early ABCI entries had full metadata. But as the point became simply tracking citations between books and linking to the catalog entry at UNC or WorldCat.org, entries started having just author and title, with no standardization in capitalization, author name order, or which creators should be listed. And because the citation information had to live in Zotero’s notes field, which is a free-for-all of text, we had to figure out some constraints, along with using Claude Code, to pull the citation data out and attach it to the items it belonged to.

One of my favorite parts of the process has been creating ontologies and vocabularies. It’s modeling how the data should look in triple format, in our case Turtle, with an example, because often when you start doing an example is when you start saying, “Oh no, that data would be great to have, but we don’t have that,” or, “What do we call a construction method?” Luckily, I was able to piggyback off the work of the Book Arts Research Database⁴ and Opening Artists’ Books⁵ for reference.

Sometimes a tool becomes unexpectedly good at another job, in this case, metadata checking. One unexpected side effect of the ABCI has been pointing out where our catalog metadata was misentered or left out. More than once, the Sloane Art Librarian, Alice Whiteside, has asked me to use the tool to pull books with a particular construction method, only to find that a book is missing or mislabeled. If you are working with incorrect data to start with, you’re going to end up with incorrect data.

As for data I would like to work with in the near future, I’ve been fascinated lately by maps of crafters and craft spaces. Especially having read more of Brendan Keogh’s recent work about viewing video game developers as craftspeople, I’d like to make a network map of video game creators and the companies or specific games they’ve connected to. Art history already acknowledges that who an artist is taught by and where they have worked has a large influence on their oeuvre. This type of lineage study is not something I’ve encountered yet in game studies.

My first step for a network map of game artists/craftspeople would be to model one simple connection. I generally do not start in a spreadsheet but think with pen and paper about how the graph might flow and then start throwing it into Turtle triples. I would start with a relatively well-established indie or smaller-team game from a company where English is a primary language. From there, I would pick one creator in an art leadership role, like an art director or character designer, and work through their CV. Once I know what information I’m looking for, I’d break out the spreadsheet to gather everything about one person, translate it over, see how it works, and troubleshoot. Then I’d look to other sources of linked data I could link out to, like Wikidata. From there, whether or how to proceed to a larger scale would really depend on what the data revealed in the small model.