The university of missouri, in partnership with the university of wisconsin-milwaukee, will plan for the investigation, exploration, and testing of the capabilities of artificial intelligence to map…

The University of Missouri System, in partnership with the University of Wisconsin-Milwaukee, received a $151,034 Project Grant from the Institute of Museum and Library Services (IMLS) under the National Leadership Grants program (CFDA 45.312) awarded October 1, 2025, with completion targeted for September 30, 2027. This planning and exploration project investigates the application of artificial intelligence (AI) to map and query knowledge organization systems through application programming interfaces (APIs), with the goal of enhancing data search and retrieval capabilities across public datasets.

The project will produce multiple digital deliverables and technical outputs designed for replication and broad adoption. Specific products include institutional project webpages, a GitHub repository for code storage and documentation, Jupyter Notebooks for code samples and testing, and a comprehensive library of Python code for interacting with AI platforms and APIs. Key technical outputs include documented prompting scripts for engaging with publicly available generative AI systems; detailed maps and diagrams of data available through Census and PubMed Entrez APIs; an expandable, information science-driven search capability for Census.gov and PubMed data; and lookup tables and code for translating Census JavaScript Object Notation outputs into usable formats. These resources are intended to serve as replicable tools and methodologies for the library and information science professions.

The university of missouri, in partnership with the university of wisconsin-milwaukee, will plan for the investigation, exploration, and testing of the capabilities of artificial intelligence to map knowledge organization systems in the form of application programming interfaces to make data search and retrieval easier. The project features the production of several digital products including project webpages at each institution; github repository for code storage and documentation; and jupyter notebooks usage for code samples and testing. The project outcomes will include: a series of methods including prompting scripts to engage in conversation with publicly available generative artificial intelligence to map, reference, and learn to query other open application program; documented python code for interacting with application programming interfaces for artificial intelligence platforms, with maps in the form of tables and diagrams for currently available data in census, and pubmed entrez application program interfaces; an expandable library and information science-driven search for census.GOV and pubmed data; and lookup tables and code for translating census javascript object notation outputs to usable data.