From Collection Records to Data Layers:
A Critical Experiment in Collaborative Practice
The CaD@Pitt (short for Collections as Data at Pitt) project is based in the University of Pittsburgh Library System and aims to increase the visibility and discoverability of library collections, make library collections data accessible for computational use, teach critical and computationally minded data practices, and enable scholars to extend/enrich collections data with research-driven data. CaD@Pitt was made possible by Collections as Data: Part to Whole, an Andrew K. Mellon Foundation-funded initiative. Check out the final report for our implementation grant project.
While our project is intended to support any and all library collections, it has prioritized those reflecting the perspectives of underrepresented groups, including African Americans, Afro-Latinx communities, American labor unionists, American left-wing organizations, the LGBTQ community, and feminists.
Data Layers Model
The CaD@Pitt “data layers” model diverges from monolithic data models (i.e., singular, non-interpretive, and exhaustive). Data layering liberates data creation and curation from the expectation of perfection or singularity of authority by enabling data to be enriched, augmented and interpreted incrementally.
The CaD@Pitt project facilitates scholars’ engagement with and enrichment of library collections data through five  instructional modules that 1) orient learners to collections as data and as products of curation and 2) teach critical and computationally minded data practices.