Docs Rnl Methodology

Event Scanning Methodology

June 16, 20261 min read

Scan architecture

RNL's event discovery runs on automated cron-scheduled scans. Each scan cycle:

  1. Checks monitored venue websites and event platforms for new listings
  2. Extracts structured data: artist/band name, venue, date, time, genre tags, ticket/info URLs
  3. Deduplicates against existing listings to avoid showing the same event twice
  4. Updates existing listings if details have changed (time change, venue change, cancellation)
  5. Records the scan timestamp for freshness tracking

Freshness tracking

Every event listing carries a "last verified" timestamp showing when the scanner last confirmed the listing was still active. This transparency lets you distinguish between freshly verified events and listings that may be stale.

The freshness system integrates with the platform-wide content freshness framework — the same system that powers Wire scan timestamps and CTS classification updates. When data hasn't been verified recently, the interface indicates this so you can check the source directly.

Data quality

Event data quality depends on the source. Venue websites vary in how they structure and present event information. The scanner handles this variation through source-specific extraction logic — each monitored venue has its own parsing rules tuned to that venue's website format.

When a source changes its website structure, the scanner may miss events until the extraction rules are updated. The freshness tracking system helps detect this — if a venue that usually has weekly events suddenly shows no new listings, it flags for investigation.

MG
Matthew J. Goss, Jr.
Retired COMEX/NYMEX floor trader, Goldman Sachs and FlexTrade Systems alumnus, multi-instrumentalist, published author, and independent mathematics researcher. Founder of Quantiterate.