The Common Data Schema is the farm record that enables Kokonut to scale.

Every Kokonut farm needs a shared baseline record before the network can fund, govern, verify, or compare it with other farms. The Common Data Schema is that baseline. It is the minimum data contract between a farm and Kokonut Network: 13 required fields that describe the farm’s location, budget, revenue model, governance, public goods allocation, local problem, proposed solution, and target market. Without this schema, every farm becomes a one-off story. With it, DAO members, contributors, farm operators, grant reviewers, developers, AI agents, and the public can all inspect the same structured record.

See the 13 Fields →See Adelphi Example

Use this page when registering a farm, drafting a farm funding proposal, building Farm Registry tools, reviewing DAO support, or connecting farm records to MRV evidence.

required fields

farm record

system consumers

MRV

evidence pipeline

EAS

attestation anchor

A farm with an incomplete schema record should not be treated as funding-ready. The schema is not just documentation; it is the baseline record that reviewers, APIs, dashboards, agents, and attestations depend on.

Why the schema matters

The Common Data Schema turns a farm from an informal narrative into a structured, inspectable record.

Without a common schema	With the Common Data Schema
Farm proposals are hard to compare	DAO members can compare farms by shared fields
Impact claims stay self-reported	MRV can attach evidence to a known farm record
Developers need custom logic per farm	APIs, dashboards, and agents can use the same structure
Governance decisions rely on long prose	Reviewers can inspect the budget, location, crops, governance, and public goods commitments quickly
Replication is difficult	New farms can reuse the same intake format

The schema is the first layer of Kokonut’s farm operating system. It does not prove impact on its own, but it makes impact evidence attachable to a consistent farm identity.

What the schema powers

Once the 13 fields are populated, a single farm record can be used by multiple parts of Kokonut simultaneously.

Consumer	How it uses the schema
DAO members	Review farm funding proposals and compare farms across location, budget, crop mix, governance, and public goods commitments.
Farm Registry API	Accepts and stores the farm record so other tools can query the same canonical data.
Kokonut Data Hub	Publicly displays the farm profile, metadata, harvest records, MRV events, and impact metrics.
AI agents	Query farm identity, location, crops, and governance context before forecasting, scoring, drafting, or monitoring.
EAS attestations	Anchor farm events to the correct`farm_id`, so evidence can be traced back to the farm record.

The schema should be understood as the farm’s identity layer. MRV then adds the evidence layer on top of it.

Who uses this page

Farm operators

Use the schema to prepare a farm record before requesting DAO support, registering the farm, or publishing it to the Data Hub.

DAO reviewers

Use the schema to assess whether a farm proposal provides sufficient comparable information to evaluate funding, governance, and risk.

Impact contributors

Use the schema to connect local problems, proposed solutions, public goods allocation, SDGs, and MRV commitments.

Developers

Use the TypeScript interface and validation rules to build Farm Registry integrations, dashboards, agents, and import tools.

Grant reviewers

Use the schema to inspect whether a farm has a traceable funding source, measurable activity, and a public evidence path.

New farms

Use the Adelphi reference record as a concrete example before submitting your own farm intake.

The 13 required fields

The schema is intentionally small. It captures only the minimum data needed to make a farm comparable, fundable, governable, and verifiable.

Group	Field	Type	Required	What reviewers need to see
Identity	Project Date	`Date`	Yes	Official Kokonut project start date in `YYYY-MM-DD` format.
Funding	Forecasted Budget	`Number`	Yes	Total estimated development budget in USD, with assumptions documented in the proposal.
Scope	Land Size	`Number`	Yes	Total land dedicated to agricultural activity, in square metres.
Identity	Project Location	`Coordinates`	Yes	Decimal latitude/longitude, plus region and country.
Funding	Source of Funding	`Text`	Yes	DAO proposal, grant, partner, or public goods funding source.
Production	Revenue Streams	`Multiselect`	Yes	Crop, product, or service revenue tags such as `lettuce`, `coconut`, or `poultry_eggs`.
Governance	Governance Mechanism	`Single Select`	Yes	How the farm will be governed: `moloch_dao`, `guilds`, `multisig`, or `cooperative`.
Governance	Token Allocation	`Richtext`	Yes	Narrative describing $vKKN, Loot, operator share, DAO share, public goods share, or other governance logic.
Public goods	Public Goods Allocation	`Number`	Yes	Percentage of gross revenue allocated to public goods activities. Minimum Kokonut default: `10`.
Narrative	Project Summary	`Richtext`	Yes	Clear summary of location, land size, crop selection, forecast, governance, and impact logic.
Narrative	Local Problem	`Richtext`	Yes	The specific local problem the farm addresses. Name the place, people affected, and why it matters.
Narrative	Proposed Solution	`Richtext`	Yes	How the farm’s production, infrastructure, education, jobs, or MRV workflow address the local problem.
Market	Target Market	`Multiselect`	Yes	Expected distribution channels such as `organic_markets`, `direct_community_sales`, or `local_supermarkets`.

Do not use generic placeholder text for Local Problem, Proposed Solution, or Project Summary. These fields explain why the farm deserves support, how it will be evaluated, and how its impact can be verified later.

Field groups

1. Identity fields

These fields answer the questions: Which farm is this, where is it, and when did it enter Kokonut?

Field	Validation guidance
Project Date	Use ISO 8601 format: `YYYY-MM-DD`. This should be the official Kokonut project registration/start date.
Project Location	Store coordinates in decimal latitude/longitude format. Include region and country for human readability.

Example:

{
  "project_date": "2024-01-15",
  "project_location": {
    "coordinates": "18.938879,-69.735003",
    "region": "Gonzalo, Sabana Grande de Boyá, Monte Plata",
    "country": "Dominican Republic"
  }
}

2. Scope and production fields

These fields answer: What is the farm producing, and at what scale?

Field	Validation guidance
Land Size	Use square meters. If total land and agricultural area differ, include the agricultural area in the Project Summary.
Revenue Streams	Use lowercase underscore tags. Include crops, animal products, native plants, biochar, or other revenue sources.
Target Market	Use lowercase underscore tags for expected channels and add custom tags only when needed.

Common revenue_streams values:

lettuce · passion_fruit · coconut · poultry_eggs · biochar · indian_yam · tomato · broccoli · spinach · arugula · native_plants

Common target_market values:

organic_markets · local_supermarkets · direct_community_sales · national_supermarkets · export

3. Funding and public goods fields

These fields answer: What does the farm need, where did support come from, and what flows back to public goods?

Field	Validation guidance
Forecasted Budget	Use USD. Treat this as a planning estimate, not a guaranteed outcome or investment return.
Source of Funding	Include proposal numbers, grant names, or partner names wherever possible.
Public Goods Allocation	Use an integer percentage from 0 to 100. Kokonut’s default minimum is 10%.

Budget and revenue fields should distinguish forecasts from actuals. Forecasts help reviewers plan; actuals should be tracked through farm records, harvest logs, and MRV updates.

4. Governance fields

These fields answer the questions: Who governs the farm, and how are ownership, contributions, and public goods recognized?

Field	Accepted values or guidance
Governance Mechanism	`moloch_dao`, `guilds`, `multisig`, or `cooperative`.
Token Allocation	Explain how governance rights, Loot, operator shares, DAO shares, contributor recognition, or public goods allocations work.

Governance values:

Value	Use when…
`moloch_dao`	The farm is governed through the Kokonut Moloch DAO and DAO-approved funding proposals.
`guilds`	The farm or workstream is coordinated primarily through contribution-weighted Guild participation.
`multisig`	A defined group of signers manages execution or transitional governance.
`cooperative`	A traditional cooperative or local governance structure is the primary operating body.

5. Narrative fields

These fields answer: Why should this farm exist, and what problem does it solve?

Field	A good answer includes
Project Summary	Location, land size, farm type, production plan, governance model, funding source, and impact thesis.
Local Problem	Specific local economic, ecological, food, labor, gender, education, or infrastructure problem.
Proposed Solution	How farm operations, infrastructure, crops, community programs, MRV, and governance address the problem.

These fields should be written clearly enough for a DAO member, grant reviewer, or local partner to understand without having to read the entire farm proposal.

TypeScript interface

The canonical machine-readable representation of the Common Data Schema uses snake_case fields.

interface KokonutFarmRecord {
  // Identity
  project_date: string; // ISO 8601, e.g. "2024-01-15"
  project_location: {
    coordinates: string; // Decimal lat,lng, e.g. "18.938879,-69.735003"
    region: string; // Human-readable place name
    country: string; // Full country name
  };

  // Scope and production
  land_size: number; // Square metres
  revenue_streams: string[]; // e.g. ["lettuce", "coconut", "passion_fruit", "poultry_eggs"]
  target_market: string[]; // e.g. ["organic_markets", "local_supermarkets"]

  // Funding and public goods
  forecasted_budget: number; // USD
  source_of_funding: string; // e.g. "Kokonut DAO Proposal #12 / Public Nouns Proposal #69"
  public_goods_allocation: number; // Percentage 0–100

  // Governance
  governance_mechanism: "moloch_dao" | "guilds" | "multisig" | "cooperative";
  token_allocation: string; // Markdown-compatible rich text narrative

  // Narrative
  project_summary: string;
  local_problem: string;
  proposed_solution: string;
}

JSON example

{
  "project_date": "2024-01-15",
  "project_location": {
    "coordinates": "18.938879,-69.735003",
    "region": "Gonzalo, Sabana Grande de Boyá, Monte Plata",
    "country": "Dominican Republic"
  },
  "land_size": 15725,
  "revenue_streams": ["lettuce", "passion_fruit", "coconut", "poultry_eggs", "indian_yam", "biochar", "native_plants"],
  "target_market": ["organic_markets", "local_supermarkets", "direct_community_sales"],
  "forecasted_budget": 85000,
  "source_of_funding": "Kokonut DAO Proposal #12 / Public Nouns Proposal #69",
  "public_goods_allocation": 10,
  "governance_mechanism": "moloch_dao",
  "token_allocation": "70% DAO members · 20% farm operators · 10% public goods fund",
  "project_summary": "15,725 m² agro-ecological farm in Monte Plata, Dominican Republic.",
  "local_problem": "Economic hardship, food insecurity, environmental degradation, and gender inequality in the Monte Plata rural community.",
  "proposed_solution": "Regenerative agro-ecological production integrating soil restoration, biodiversity conservation, organic food production, community education, and public MRV."
}

Adelphi reference record

Adelphi is Kokonut Network’s first live farm and the reference implementation for this schema.

Field	Adelphi value
Project Date	`2024-01-15`
Forecasted Budget	`85000` USD
Land Size	`15725` m²
Project Location	`"18.938879,-69.735003"` · Gonzalo, Sabana Grande de Boyá, Monte Plata · Dominican Republic
Source of Funding	`"Kokonut DAO Proposal #12 / Public Nouns Proposal #69"`
Revenue Streams	`lettuce`, `passion_fruit`, `coconut`, `poultry_eggs`, `indian_yam`, `biochar`, `native_plants`
Governance Mechanism	`moloch_dao`
Token Allocation	70% DAO members · 20% farm operators · 10% public goods fund
Public Goods Allocation	`10`%
Project Summary	15,725 m² agro-ecological farm in Monte Plata, Dominican Republic, with organic vegetables, fruits, coconuts, public goods funding, and women-led operations.
Local Problem	Economic hardship, food insecurity, environmental degradation, and gender inequality in the Monte Plata rural community.
Proposed Solution	Regenerative agro-ecological production integrating soil restoration, biodiversity conservation, organic food production, and community education.
Target Market	`organic_markets`, `local_supermarkets`, `direct_community_sales`

Explore Adelphi live data →

Validation checklist before a farm proposal

Before a farm submits a funding proposal, reviewers should be able to answer each question below.

Check	Reviewer question
Identity	Can we identify the farm, location, start date, and operating context?
Scope	Do we know the land size, productive area, crop mix, and target market?
Budget	Is the forecasted budget specific enough to evaluate and to set milestones?
Funding source	Is the source of funding traceable to a grant, proposal, partner, or treasury request?
Governance	Is the governance mechanism clear enough to know who decides and who is accountable?
Token allocation	Are DAO members, operators, contributors, and public goods allocations explained?
Public goods	Is the public goods allocation percentage explicit?
Problem	Is the local problem specific, place-based, and relevant?
Solution	Does the proposed farm solution directly answer the stated problem?
MRV readiness	Can future farm events attach back to this record through `farm_id`?

A strong farm record is not necessarily long. It is specific, traceable, and structured enough for funding, operations, MRV, and governance to use the same source of truth.

How the schema connects to MRV

The Common Data Schema defines the farm. MRV verifies what happens on the farm after registration.

Schema layer	MRV dependency
`project_location`	Connects remote sensing, field logs, drone imagery, and satellite indices to the correct place.
`revenue_streams`	Helps match harvest records and production forecasts to the correct crops or products.
`governance_mechanism`	Determines who reviews evidence, approves changes, and responds to risks.
`source_of_funding`	Links evidence back to the proposal, grant, or DAO decision that funded the work.
`public_goods_allocation`	Let the network track whether farm revenue supports public goods commitments.
`local_problem` and `proposed_solution`	Provide the narrative baseline that SDG and impact reporting can evaluate over time.

Schema governance and backward compatibility

The Common Data Schema is a root data contract. Farm records, APIs, dashboards, AI agents, and attestations depend on these field names and types. Changing the schema requires a Framework Upgrade Proposal because schema changes can affect live farms, MRV payloads, Data Hub queries, and agent behavior. Any breaking change must include:

A migration plan for currently registered farms
A dual-write period where old and new formats are accepted
A cutover date after which the old format is no longer accepted
Documentation updates for farm operators, developers, and proposal authors
A passed DAO vote before the change becomes active

Additive optional fields are lower-risk, but they still require documentation and governance review. Required field changes, field renames, or type changes should be treated as high sensitivity.

Use the Framework Upgrade Proposal Template →

Common mistakes to avoid

Mistake	Why does it create risk
Using vague location descriptions	Remote sensing, field logs, and farm events cannot reliably attach to the farm.
Treating forecasted budget as guaranteed performance	Forecasts are planning tools and must be refined against actuals.
Omitting the source of funding	Reviewers cannot trace the farm back to the proposal, grant, or treasury decision that supported it.
Writing generic local problems	The DAO cannot evaluate whether the proposed solution fits the community context.
Mixing $vKKN, Loot, and Guild Points without explanation	Governance, capital, and contribution recognition become confusing.
Changing field names casually	APIs, agents, attestations, and dashboards may break.

Next steps

Farm Funding Proposal Template

Use the schema in a DAO-ready farm funding proposal, including budget, milestones, MRV commitments, and public goods allocation.

MRV Methodology

See how farm records become verifiable evidence through payloads, IPFS, Farm Registry events, EAS attestations, and the Data Hub.

Kokonut Framework Introduction

Understand how this schema fits into Kokonut’s larger system for comparable, fundable, governable, and verifiable farms.

Adelphi Summary

Review the first live Kokonut farm using the schema in practice.

Proposal Templates

Choose the right proposal type before requesting farm funding, Guild work, Framework changes, or partnerships.

Adelphi Data Hub

Inspect the live reference farm record and its connected MRV and impact data.

Use the Farm Funding Template →Explore Adelphi Data

Framework Components

Framework Features

Framework Add-ons

Development Phases

Common Data Schema

The Common Data Schema is the farm record that enables Kokonut to scale.

Why the schema matters

What the schema powers

Who uses this page

Farm operators

DAO reviewers

Impact contributors

Developers

Grant reviewers

New farms

The 13 required fields

Field groups

1. Identity fields

2. Scope and production fields

3. Funding and public goods fields

4. Governance fields

5. Narrative fields

TypeScript interface

JSON example

Adelphi reference record

Validation checklist before a farm proposal

How the schema connects to MRV

Schema governance and backward compatibility

Common mistakes to avoid

Next steps

Farm Funding Proposal Template

MRV Methodology

Kokonut Framework Introduction

Adelphi Summary

Proposal Templates

Adelphi Data Hub

​The Common Data Schema is the farm record that enables Kokonut to scale.

​Why the schema matters

​What the schema powers

​Who uses this page

Farm operators

DAO reviewers

Impact contributors

Developers

Grant reviewers

New farms

​The 13 required fields

​Field groups

​1. Identity fields

​2. Scope and production fields

​3. Funding and public goods fields

​4. Governance fields

​5. Narrative fields

​TypeScript interface

​JSON example

​Adelphi reference record

​Validation checklist before a farm proposal

​How the schema connects to MRV

​Schema governance and backward compatibility

​Common mistakes to avoid

​Next steps

Farm Funding Proposal Template

MRV Methodology

Kokonut Framework Introduction

Adelphi Summary

Proposal Templates

Adelphi Data Hub

The Common Data Schema is the farm record that enables Kokonut to scale.

Why the schema matters

What the schema powers

Who uses this page

The 13 required fields

Field groups

1. Identity fields

2. Scope and production fields

3. Funding and public goods fields

4. Governance fields

5. Narrative fields

TypeScript interface

JSON example

Adelphi reference record

Validation checklist before a farm proposal

How the schema connects to MRV

Schema governance and backward compatibility

Common mistakes to avoid

Next steps