Scoring model analytics based on a 50+ privacy projects survey
We are shipping an educational website to help the general public understand whether a web3-service is private or not. Its core feature - scoring mechanism validated by the market (reference: web3 - l2beat, web2 - IMDB).
| Original idea | Privacy market survey | Scoring model MVP | Community feedback model 1.1 | ETHRome data set | DeFi category scoring x model 1.2 | Playbook for non-techies 1.3 |
|---|---|---|---|---|---|---|
| link | link | link | link | link | link | link |
17 Oct, 2023 update
2 DO list
Analyze
- Analyze latest privacy scoring assessment here
- Analyze Data manifesto made during ETHRome
- Analyze pull requests by Railgun, Waku, Lit, Discreet, Webb here
Create
- Github page in this repo
- Enrich scoring model MVP with the new parameters that could be easily automated or quickly manually aggregated (if not - move data set into a backlog)
- Try to apply previous scoring model approach (with % &/or semaphore take: green, yellow, red) to new parameters & observe how scoring model could change (write down potential changes & implications)
Delivery
- Final page will be breaken down into:
- Updated scoring model MVP data set (without scoring approach)
- Simulation of the old MVP + new MVP: how scoring could change with new parameters
- Backlog (data that can't be quickly parsed)
- MVP description: here
- Initial idea: here
- Privacy players' survey
- Test framework: PDF
- Latest scoring assessment: here
- ETHRome prototype
- DeFi category testing
- Scoring assessment 1.0 explainer
- Data brief x 1.0 comparison
- Platform features backlog