Automating Event Data Pipelines and Enhancing Discovery UX for DU Event Board

The DU Event Board currently uses manual inputs and basic validation to manage event data. As the number of events grows, this can make it harder to maintain consistency, avoid duplicate entries, and optimize API usage. Event discovery is also primarily based on simple filters and does not yet include offline access. This project improves how event data is processed and maintained. On the backend, it extends the existing GitHub Actions workflow to automatically fetch event metadata (image and description), detect duplicates using title and date similarity, and perform geocoding only once per event by writing coordinates back to the source file. These changes prevent duplicate entries, reduce repeated API calls, and remove the need for manual data fixes. On the frontend, the project adds full-text search, map-based filtering with a time slider, relative date display, and offline support. It also introduces a guided event submission flow that creates structured GitHub Issues, making it easier for contributors to add events. Together, these changes reduce manual review work and make it easier for users to search, filter, and access events.