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Mykola Siusko 2023-11-01 16:13:59 +01:00 odevzdal GitHub
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@ -35,37 +35,28 @@ The scoring model could consist of passive & active parts. When passive means wh
## Checklists (example: trusted sources list).
_Benefit_: serves as a self-check navigation within the complex audit stream (and a predecessor of an actionable database)
_Downside_: there will be always something missing from the list
**Approach**:
- pick a direction (like "trusted sources")
- write down it as an actionable plan
- help a person spend less time on data aggregation (the easiest to follow checklist - the better)
_Checklist MVP_:
- **Storage**: What user information is stored? (username, IP address, last connection, wallets associate, etc) -> the less the better
- **Infra**: Number of nodes/servers/ -> the larger the footprint the best privacy
- **Signup**: no email or tel number for signup -> the less data the better
- **Traction**: number of people using it -> the more the better (with examples)
- **Public comms**: simplified socials analysis (for a negative sentiment)
- **Product-readiness**: test-net, mainnet; date of the release.
| _Benefit_ | _Downside_ | **Approach** | _Checklist MVP_ |
| ------------- | ------------- | ------------- | ------------- |
| serves as a self-check navigation within the complex audit stream (and a predecessor of an actionable database) | there will be always something missing from the list | pick a direction (like "trusted sources") | **Storage**: What user information is stored? (username, IP address, last connection, wallets associate, etc) -> the less the better |
| | | write down it as an actionable plan | **Infra**: Number of nodes/servers/ -> the larger the footprint the best privacy |
| | | help a person spend less time on data aggregation (the easiest to follow checklist - the better) | **Signup**: no email or tel number for signup -> the less data the better |
| | | | **Traction**: number of people using it -> the more the better (with examples) |
| | | | **Public comms**: simplified socials analysis (for a negative sentiment) |
| | | | **Product-readiness**: test-net, mainnet; date of the release. |
This is a mix of objective metrics & subjective takeaways (like an old product release can be a negative sentiment for privacy & vice versa). Case studies will help to empower these assumptions.
If we will collect good case studies lib -> it will help people to have market benchmarks for every step of scoring system.
# Academy (content from case studies to third-party services to check net data, leakages).
_Benefit_: this will be the backbone of our platform in the future that will bridge the gap between lack of privacy-centric education, lack of third-party services to check-up solutions & poor transparency on behalf of privacy-devs.
_Downside_: usually takes too long time to deliver & many different contributors (should be simplified via tracks like Web3 Privacy 101).
**Approach**:
1. Stick with privacy 101 (basics).
2. Brake down the most crucial knowledge into simplified blocks.
3. Create a simplified & actionable "lecture framework" for guest lectors.
4. Invite lectors within a micro-learning format.
5. Cover basic 10 lectures via "Web3 privacy 101 introduction".
6. Deploy via videos + texts > test them out.
| _Benefit_ | _Downside_ | **Approach** |
| ------------- | ------------- | ------------- |
| this will be the backbone of our platform in the future that will bridge the gap between lack of privacy-centric education, lack of third-party services to check-up solutions & poor transparency on behalf of privacy-devs. | usually takes too long time to deliver & many different contributors (should be simplified via tracks like Web3 Privacy 101). | Stick with privacy 101 (basics). |
| | | Brake down the most crucial knowledge into simplified blocks. |
| | | Create a simplified & actionable "lecture framework" for guest lectors. |
| | | Invite lectors within a micro-learning format. |
| | | Cover basic 10 lectures via "Web3 privacy 101 introduction". |
| | | Deploy via videos + texts > test them out. |
## _Long 2do list (filtered out product features)_