# July 27 Dolt Bounty retro

## What went well?

* engagement & re-engagement with community + potential supporters
* iterated on our schema / planned and made some changes
* we filled out the agencies table to a high level of completion → a prerequisite to the datasets table
* excellent support from the Dolt team!
* learned that volunteer interest plays a big role in determining our focus
* got a start on refining the review process
* we split the bounty into two pieces so we had an opportunity to learn

## What could have gone better?

* there's not currently an automated review process or script
* we discussed the difference between a dataset URL and an agency homepage
  * people ended up focusing on the agency homepage URL more than the datasets
* one person ran away with the scoreboard by using machine readable lat/long

## Next steps

* Katie to share some metrics on engagement
* Minimize variables + types of submissions allowed, particularly differences in **scraped vs. manually gathered data**
* Plan next bounty for \~8/25 start
  * Formalize the fact that our team should do the reviews + scripts
  * Smaller bounties help us iterate on a faster loop
  * Look at [attribution + scoreboard code](https://github.com/dolthub/bounties) and make contributions to how rewards are given out.
  * Announce $50/participant (pending Katie + Dolt approval)

## Notes for bounty success

1. Pick a common schema for data (i.e. "incident reports")
2. Allow people to submit data linking back to the source (i.e. dataset)
3. Focus on discrete, scrapeable goals with relevant topics
   * e.g. hospital bounty was in response to a law which passed which required hospitals to publish data
   * national scope for a narrow data focus is a potential alternative to the narrow geo focus
     * helps with schema normalization + big stories + big moves
     * local is storytelling → action loop
4. Focus on additions vs edits, enforceable by requiring properties