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Privacy Services DB

Privacy marke DBPrivacy services x web3 initial market DB aggregation: segmentation, key links (web, git, docs), ecosystem, product liveliness etc. 600 projects in the

Current status

600 projects in the DB (basic data aggregated)

Internal need (regular basis)

  • actualise current data
  • add new projects
  • moved sunset projects into “Sunset” category
  • fix broken links

Ultimate need

  • aggregate reach data to match explorer project profile

📖 Contributor guide

Maintaining privacy services database example: PR at GitHub


goal: up to date information in the database algorhithm:

  1. Open database
  2. Pick up a category (from DeFi to Infrastructure)
  3. Check
  • product-readiness (actual state: devnet, testnet, mainnet)
  • team status (public, anon)
  • github/docs-readiness (available/not)
  • ecosystem
  • token (yes/no/Coinmarketcap link).
  1. Add missing data & make a PR.


goal: broader list of categories within the privacy market. algorhithm:

  1. Open database
  2. Check “other” & “dapps” categories.
  3. Find sub-categories (min 3-4 projects per category). Examples: “marketplaces” or “data lakes”.
  4. Once a new sub-category has been found - create it & move those projects under it.


goal: actual information on terminated or abandoned projects. algorhithm:

  1. Open database
  2. Check sunset projects (Twitter &/or Discord activity, GitHub activity).
  3. 6 months hiatus - mark them with an icon of the moon next to them.

category accuracy

goal: check Infrastructure, dApps, Other categories if projects really belong there (some projects misslead readers pretending to be infrastructure, for example) algorhithm:

  1. Open database
  2. Check projects’ website, documentation.
  3. Make observations if a projects belongs to particular category (infrastructure - providing broader protocol toolkit for different decentralised implementations).
  4. If project nature differs from category where it exists - move it to the right category.