Common Farm Conventions

The Problem It Solves

The agricultural sector faces a significant challenge: data is often collected and stored in diverse, incompatible formats across different farms, organizations, and software tools. This fragmentation makes it difficult to:

• Share data effectively: Collaborating on projects, reporting to funders, and participating in research initiatives becomes cumbersome and error-prone.
• Integrate systems: Connecting different farm management software, analysis tools, or data platforms requires custom, time-consuming development of APIs.
• Ensure data quality: Without common standards, validating data consistency and accuracy is difficult.
• Gain broader insights: Aggregating data for regional analysis, benchmarking, or developing predictive models is often impractical.

What are Common Farm Conventions

Common Farm Conventions provide a solution by establishing a shared data model on how to structure and describe agricultural data for specific purposes. Think of them as blueprints for data exchange.

Instead of rigid, one-size-fits-all global standard, Conventions offer a flexible approach:

1. Built on a Common Foundation: They leverage the robust and widely adopted farmOS data model for the core concepts (Assets, Logs, etc.).  This model is proven to work for a very wide range of agricultural applications.
2. Leveraging JSON Schema: Conventions are defined using JSON Schema, a powerful standard for describing the structure and constraints of JSON data. This provides technical advantages like programmatic data validation across most programming languages.
3. Modularity and Extensibility: The “base” Common Farm Convention broadly describes many typical farm records (planting, harvest, etc.) so each group isn’t reinventing the wheel.  However, groups can then create “child” conventions, inheriting from and extending that base, tailoring it to specific needs without losing compatibility.

Why It Matters

For Project Managers & Data Managers:

• Improved Data Quality: Built-in validation rules ensure data consistency and completeness from the start.
• Simplified Collaboration: Easily share and receive data with partners who adhere to the same conventions.
• Streamlined Reporting: Standardized data formats make aggregation and reporting more efficient.
• Clear Documentation: Conventions come with human-readable documentation generated directly from the schemas.

For Developers & Technical Teams:

• AI Ready: Modern LLMs are extensively trained to generate, modify, and test JSON Schema and can accurately create synthetic data to test edge cases.  A great mix of human and machine readable.
• Robust Validation: Leverage JSON Schema tooling for automatic data validation in applications.
• Interoperability: Easier integration between systems that understand the same conventions. Reduces the need for custom data mapping.
• Machine Readability: JSON Schema provides a clear, machine-understandable definition of the data structure.
• Auto-Generated Documentation: Reduce the burden of writing and maintaining data format documentation.
• Extensibility: Create project-specific conventions that build upon the common base, promoting reuse and reducing redundant effort.
• Alignment with Modern Practices: Uses well-established web standards (JSON, JSON Schema).

Getting Started (The “Toolbox”)

Ready to adopt or contribute? Here’s where to start:

• Documentation & Wiki: The Common Farm Conventions Wiki walks through the rationale, structure, and usage of conventions, including guides for both adopters and contributors.
• Browse Existing Conventions: The project already includes conventions for common farm activities: field definitions, plantings, tillage, harvest, fertilizer and lime applications, irrigation, seed treatments, soil lab tests, mowing, grazing, solarization, and more. Browse them in the Conventions section (this is the “field” convention) of the wiki.
• Create Your Own Convention: The wiki includes a guide on both “How to Convention” (the very human process of data consensus) and how to set up a convention (the technical process of building and deploying a convention)  you actually create a convention.
• Join the Community Call: The Common Farm Convention community meets on alternate Thursdays at 1:00pm EST, right after the farmOS developer call. Meeting link: https://meet.jit.si/farmos-dev. Check the farmOS forum for the latest schedule and notes, or just post to introduce yourself and your needs.
• Contribute: As a GPL-3.0 project hosted on GitLab, contributions are welcome — whether that’s proposing a new convention, refining an existing schema, improving documentation, or building tooling. Open an issue or submit a merge request on the project repository.

Community-Driven, Practically Governed

Common Farm Conventions grew out of a practical need: organizations in the OpenTEAM ecosystem wanted to share data. Rather than imposing a top-down specification, the conventions process is collaborative and iterative — shaped by the developers, researchers, and agricultural organizations who actually use the data.

The Common Farm Convention “Base” model is managed by Our Sci in partnership with Mike Stenta and the FarmOS community.  While it is heavily influenced by the FarmOS data model, and often what makes sense for FarmOS also makes sense for the Common Farm Convention “Base” model, that isn’t required.  Ongoing discussion happens on the farmOS community forum and biweekly Convention calls. Proposals for new conventions or changes to existing ones are discussed in community meetings, tracked as issues on GitLab, and refined through merge requests. The goal is to keep the process lightweight enough that real-world projects can move quickly, while maintaining enough rigor that the conventions remain useful and trustworthy across organizations.
 

The Ecosystem

Common Farm Conventions are currently used by or integrated with the following projects and platforms:

• farmOS – The open-source farm management platform whose data model provides the foundation for all conventions.
• SurveyStack – A data collection platform by Our Sci that uses conventions to structure farm data entry and push records into farmOS.
• Pasa Sustainable Agriculture – Pasa’s Soil Health Benchmark Study uses SurveyStack and farmOS conventions to collect standardized management records from 150+ farms across the Eastern US.
• Point Blue – Point Blue is using conventions along with FarmOS for their Range C and Crop C Programs, and evaluating its use in additional data sharing opportunities.