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I managed to not check the track when submitting :/

Squidsway Governance Report and Tool

Actionable governance insights, from a rich data chain indexer

The proposal for Squidsway funds two things on an ongoing basis.

The Squidsway tool:

A chain indexer with rich data ingestion modules,
for testing and quickly iterating hypotheses and generating actionable insights about user behaviour.

The Squidsway project:

Publishing governance insight reports roughly every 3 months (and on shorter timescales case-by-case).
Continually adding modules to the tool, to support investigation through the tool, for the purpose of generating insights.

The tool will be open source, for any dev (eg, ecosystem product teams) to use, and future work includes an LLM-based frontend for non-devs to query it.
The project will be funded by the community on an ongoing basis, so will be focused on live, open questions that the community is discussing at any given time. There will be a mechanism for the community to request data on issues of interest.

This proposal funds only the first three months. If the community likes what it sees, then subsequent proposals will fund ongoing work.

GOVERNANCE FAILURES ARE A TREASURY ISSUE.

SQUIDSWAY WILL SOLVE THOSE FAILURES FASTER.

I want to improve Polkadot governance because I'm a cypherpunk and I think Polkadot can lead the world, not in just governance of blockchains, but in blockchain-based governance of the offchain world.
Governance is a product on Polkadot, its a field we are leading in, and we should invest in growing the lead we have - make it something to showcase.

But you, dear tokenholder, should fund improving Polkadot governance because

GOVERNANCE FAILURES ARE A TREASURY ISSUE

We are iterating our processes based on assumption, hunches and louder voices, instead of evidence.
That wastes time and costs money.

The alternative to iterating based on vibes is data.
Squidsway is a proposal to collect and compile specific bespoke data, targeted at objectively assessing how OpenGov users respond to everything we do in OpenGov - and to generate insights from these assessments, in order to inform how we continue to iterate OpenGov.

Deliverables

This first proposal is for $8k USDT, to fund 80 (=40+40) hours over around 3 months,
being the development of an MVP, followed by the first half of the validation phase.

At the end of the work funded by this proposal, the tool should consist of:

modules to:

. ingest relevant governance events from chain data

. ingest structured/quantitative offchain data (e.g. from Polkassembly)

. curate data (using queries to assign tags, e.g. "whale", "shrimp")

and

. an indexer capable of reindexing based on these types of data.

At the end of the work funded by this proposal, I expect that the outputs I will report to be sufficient to demonstrate that the tool is functioning - concrete, but probably boring and uncontentious, observations.
Don't worry- the plan is for the insights to become more insightful over time as the tool grows to be able to ingest and compile more awkwardly structured data!

The second proposal would fund the second half of the validation phase.
By the end of that work, I intend that the tool will be ingesting qualitative (natural language) data and outputs would begin to demonstrate what is possible with the tool. I should also have some basic benchmarking to flag up any feasibility questions and potential non-labour costs for the future.

At the end of each funded period, I will report the hours spent on each sprint or other labour.
Overspends in each funding period will be added on to the next proposal for retrospective funding.
Underspends will be subtracted from the next proposal or, in the case of the project winding down (i.e. if a referendum fails), returned to treasury.

Funding

I am proposing to work via sprints, each being 20-80 hours, at $100/hr.

I am proposing to, initially, submit individual treasury referenda to fund upfront around 2 months of work (40-160 hours) each, initially with their own proposals which will be updates to this original proposal.

When the work and delivered outputs settle into a more steady rhythm (i.e. timing, expectations and amount to request become predictable), I plan to switch to the Treasury Guardian model (scheduled funding).

After about a year, the need to code modules to ingest new data sources should have reduced significantly, leaving the compilation of data (ie reindexing and querying) as the largest labour cost (which would also reduce if the LLM frontend becomes popular).

I would hope that, a year after the validation phase, that multiple people in the community will be proficient in using the tool, so that compiling the governance report would be less about the project generating insights and more like curating insights generated by the community using the tool.

Methodology

The methodology is intended to be very, very agile.
The idea of generating insights is to tell us something we didn't know, rather than setting out to prove or disprove a pre-defined set of hypotheses.
Central to that is the ability to, in investigative terms, 'pull on threads' - or, in software terms, to 'rapidly iterate'. This means that the treasury will, for each sprint/for each proposal, be funding something that it does not know what it will be.

This agile way of working is necessary because:

We need to go where the evidence takes us
It's likely that many of each of the small technical steps that would make up a milestone can only be identified once a previous step is complete, so identifying and costing out these small technical steps in advance would either lead to wasted labour or force investigations down an inflexible path.

The fact that, in the base case of Squidsway funding referenda, the treasury will be funding something unknown should be mitigated by the ongoing nature of the project, and the fact that each 'milestone' (ie funding period) is a small amount.

Any Questions?

Two parts, insights and tool

The tool is a backend, not a frontend

I can haz dashboard?

How is different from, say, Dune Analytics?

What do we get from these governance insights?

What kind of 'user behaviour' are we trying to encourage?

What are these 'iterations' of OpenGov?

Can you investigate ?

WTF is 'rich data' / 'chain indexer'?

Contact

Read the full proposal