Case study: digitizing a 50-year Hall of Fame

The problem. The James P. Kelly UC Athletics Hall of Fame spans five decades of inductees - athletes, coaches, teams, administrators - and its history lived in plaques, programs, and scattered documents. If you wanted to know who went in with the class of 1987, you needed the wall.

The bet. A Hall of Fame is fundamentally a dataset wearing a ceremony: names, classes, sports, categories, stories, photos. Structure the dataset properly and everything else - search, rosters, anniversary content, event planning - falls out for free.

How it's built.

• The registry came first. Every inductee from 1976 to 2025 - over two hundred entries - normalized into structured records: class year, sport, category (athlete, coach, team, contributor), and biography.
• The showcase at hof.gobearcats.ai is a React app built with Lovable - browsable by class, sport, and era.
• The same structured data feeds operational work: induction ceremony planning, anniversary storytelling, and archival photo matching against the department's 3M-image asset library.

What I learned.

1. Digitization is mostly data modeling. The scraping and entry was a fraction of the work; deciding the schema - how to represent a two-sport athlete, a team induction, a posthumous honoree - was the real project. Get the model right and the UI is easy.
2. Structured history compounds. Once the registry existed, every downstream ask ("all basketball inductees from the 90s for a video segment") went from a research project to a query.
3. Institutional memory is a product surface. The Hall of Fame page gets emotional reactions no dashboard ever will. Some of the highest ROI software is just history, treated with respect and good typography.

Status. Live, growing with each induction class, with photo archive integration as the next frontier.