Analytics & Research (A&R) subgroup
The full scope of work under A&R subgroup is as follows:
A&R is responsible for the gathering of intel and analytics of all things pertinent to ENS DAO, especially Governance, under one roof. A&R should also actively seek to pull engagement data from third-party providers such as ShowKarma pertaining to users, delegates and contributors. A&R shall also actively seek to archive & analyse data pertaining to off-chain and on-chain votes, ENS token dispersion, Discourse data, Discord data and Twitter analytics. The aim of this exercise is to equip the DAO with all the necessary data and information required in its several decision-making processes, e.g. Steward elections etc.
A&R is responsible for briefing all working groups with data-driven approaches to streamline ENS DAO. One example of a duty of A&R toward ENS DAO is to formulate a dynamic and machine-generated model for capturing reputation and health of DAO delegates, stewards and contributors. Currently, most reputation models are static, manual, rudimentary and gameable. An ideal reputation should not be gameable or static. In this context, A&R should look into already existing approaches such as classic Hedonic modelling & regression and Hedonic-AI regression to rid us of manual and gameable models; this is possible but needs dedicated work to formulate training datasets (for Hedonic-AI) and quantifiable data for fitting (classic Hedonic). This work requires devising detailed semi-annual surveys to capture the state of ENS (at the very least) in consultation with the ENS DAO community and contributors. The result of this undertaking should be to provide the DAO with actionable intel during elections (e.g. reputation & health of candidates) and other relevant decision-making processes. A&R is also responsible for actively assessing threats to ENS and propose ideas to make the DAO resistant to risk and volatility; an example of this is to devise practical ways of reducing dead vote count, off-boarding process for delegates & contributors, and suggesting improvements to governance model.
Analytics & Research
First semi-annual survey of the ENS DAO in June 2022. The survey will be designed in a quantitative, anonymous and no-text format to gauge the health of ENS Governance and to signal possible amendments to the current processes. The strict quantitative nature of the survey prompts should enable the results to be utilised in Hedonic regression model for steward and delegate health/reputation in Q3/4. The results will be showcased in form of community-mandated steward and delegate health cards. This must be ready before the next Steward elections for Q3/4.
Partner with Show Karma to pull daily engagement data for contributors, stewards and delegates from Discourse and generate first ENS DAO (semi-annual) Governance Report. This will contribute toward multi-modal graphic representation of steward and delegate impact. This must be ready before the next Steward elections for Q3/4. Flipside Crypto may make contribution in this report with their analytics inputs.
- Develop the dynamic, linearised (easy AI switch later) and ungameable health model employing Hedonic regression methods. This is where the quantitative surveys performed in June Q2 will become useful from hard analytics perspective. The results of hedonic regression will yield the relative perceived values of traits/qualities/processes of ENS DAO that the community finds meaningful.
- Bring Discord (bot search; have some ideas from DAOist GGG talk by Kristin Chen from Top.gg), Twitter analytics into the frame
- Research work on two subjects:
a) Voting power diffusion in Sybil-agnostic voting systems aka “dead votes” issue (like ENS),
b) Propose practical off-boarding process for delegates, and
c) Propose re-delegation strategies to counter dead votes.
- Second semi-annual survey in December 2022
- Second ENS DAO Governance report
- (to be added)