Seven Principles for Mobilizing Open Data to Power India's Agri-Stack

This document outlines seven key principles for mobilizing open data to power India’s Agri-Stack, aiming to digitally transform agriculture. It addresses the challenges and opportunities in the Indian agricultural sector and proposes a framework for leveraging digital innovation. This is valuable for policymakers, researchers, and practitioners involved in digital agriculture initiatives in India.

Key Insights

Principle 1: Common Digital Taxonomies

Digital taxonomies facilitate data interoperability by creating standard classifications of codes. This involves:

• Creating a standard classification of codes at the national level to bring uniformity in data.
• Establishing standardized specifications for assessing physical quality, grading, and the presence of chemical residues.
• Organizing standard information in directories and registries of legal and public entities.
• Developing data models and schemas based on standards like Health Level 7 (HL7) for secure data exchange.

Principle 2: Establishing Identity

Implementing Know Your Farmer (KYF) norms helps collect data from various entities within regulatory boundaries, reducing acquisition costs. Key aspects include:

• Maintaining an Electronic Farm Record (EFR) with demographic and topographical information.
• Capturing data at the farm level with location-wise details, using manual or digital collection methods.
• Ensuring the technology adopted is context-specific and designed to capture details without additional effort from farmers.

Principle 3: Database of Buyers and Sellers

Creating a reliable list of farm input sellers and produce buyers will address trust issues. This involves:

• Leveraging technology to create a unique digital list of sellers and buyers with a verification mechanism.
• Promoting practices such as Unique Digital Identity, verification systems, third-party auditing, and certification.
• Allowing technology firms to leverage farm-level information to devise comprehensive credit ratings for improved access to credit.

Principle 4: Data Sharing Policy

Designing policies that balance data confidentiality with the potential benefits of data sharing is crucial. This includes:

• Developing a robust data management and sharing policy that clearly states the do’s and don’ts of data sharing.
• Using the ORGANS principle (Open standards, Revocable, Granular, Auditable, Notice, Secure) as the basis for data sharing by consent managers.
• Designing agreements in simple language to protect the rights of data principals.

Principle 5: Flexible Architecture

Data shared and integrated by various players should lead to customized, timely advisory for farmers. This requires:

• Shifting from generalized advisory services to farm-specific services that consider crop type, price realization, and input availability.
• Supporting a multi-modal delivery system (e.g., mobile, radio, YouTube, WhatsApp) with the right technology based on the local context.
• Grading the quality of information exchanged through the platform via feedback ratings and standardization mechanisms.

Principle 6: Open-source Nature

Basing the technology stack on the principles of federated architecture and open source promotes trust and enables faster scalability. This involves:

• Adopting a federated architecture that allows for necessary checks and balances in the centralization and decentralization of data sharing.
• Maintaining common repositories for data to avoid duplication and protect the constitutional rights of the states.
• Ensuring the core data is validated and clean.

Principle 7: Partnership-driven Approach

A collaborative model is needed where stakeholders create a platform that delivers value-added information to the farmer. This requires:

• Designing a data-sharing mechanism that incentivizes data generators.
• Focusing on aspects of data that do not create a conflict of interest.
• Employing a multi-pronged approach involving Policies, Platforms, Protocols, and Partnerships.

Key Statistics & Data

• Agriculture provides employment to almost 46.5% of India’s labor force (Periodic Labour Force Survey 2020-21).
• Agriculture contributes to almost 18% of the Gross Value Added (GVA) of the Indian economy.
• India’s share in world trade of agriculture exports increased from 0.52% in 1990 to 1.71% in 2019.
• The average monthly income of an agricultural household stands at INR 10,218 (Situational Assessment Survey 2021).
• 86% of farmers fall under the category of small and marginal with holdings size less than 2 hectares.
• Farm mechanization in India is low at 40-45%.
• The adoption of Agri-Stack-based approaches is expected to result in almost INR 5-7 lakh crore worth of benefits for farmers by 2030.

Methodology

This policy brief summarizes the key principles discussed at a consultation workshop organized by the CGIAR Research Initiative on Digital Innovation in partnership with The Agri Collaboratory (TAC) in Delhi in November 2022. The workshop involved 70 stakeholders representing 54 organizations and focused on the design principles of thematic use cases for Agri-Stack. The document analyzes the key discussion points from the workshop to derive the seven key principles for mobilizing open data in the Agri-Stack.

Implications and Conclusions

The document concludes that digitalization can help Indian agriculture be globally competitive and self-sustainable. However, existing initiatives are yet to reach scale due to issues like lack of common digital taxonomy and interoperability. The Agri-Stack initiative aims to address these challenges by developing a national framework for digital agriculture. The document proposes that the next steps should focus on:

• Development of common digital taxonomies through expert committees.
• Re-engineering e-NAM to provide additional services.
• Formulation of data sharing and management policies.
• Creation of a vibrant and active open community to oversee the development and implementation of Agriculture Data Exchange.