WonderCat is a relational database of human experiences with narrative. The project is designed as an experimental alternative to reading lists (in courses) and recommendation algorithms (in the real world). It is intended primarily as a discovery tool, helping users find creative works that have been valuable to real readers. It does not deliver personalized recommendations.

The tool is built around three taxonomies: Experiences, Narrative Technologies, and Impacts. The terms in these taxonomies and their definitions are published as glossaries, and we have designed a review process for glossary terms that allows any user of WonderCat to contribute to our ever-expanding understanding of narrative in the world.

The site is built with WordPress, which has been customized with ACF. Visualizations of this data are built with the R package Shiny, which pulls in Wikidata to provide dynamic visualizations of the experiences in our database.

Our presentation will focus on two goals we tackled in Summer 2025, presenting our solutions (so far) and inviting ideas from the Reclaim community. Our first goal was to make Shiny WonderCat load more quickly (we’ll share our experiments with cron jobs) and our second was to develop an editorial workflow that encourages the general public to engage with our editorial board (we’ll share our experiments with Gravity Flow).

We hope participants will leave the session inspired to develop their own alternatives to recommendation algorithms.