Research and case studies

Bill & Melinda Gates Foundation is implementing FAIR data practices in agricultural development (AgDev) projects and exploring the challenges, benefits, and economic impacts for stakeholders and ecosystems.

Why FAIR?

These case studies and reports are examples of investment projects where CABI and other partners contributed to FAIR and responsible data practices. They include examples that underpin the structure of this resource, and examples where steps and activities from this resource were tried and tested.

They offer an introduction to the scope of implementing FAIR data practices and the expected and experienced benefits to AgDev institutions, grantees and their wider ecosystems, and potentially beyond. They also include impact stories illustrating how FAIR practices can inform the work and development of actors across the investment lifecycle and the data chain – from farmers, through the private sector, to politicians and governments.

They cover the economics of FAIR, as well as in-country use cases since the beginning of the Enabling Data Access project was started in 2019.

Understanding the enablers and disablers of mainstreaming FAIR, with CGIAR

This case study examines the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) data principles within CGIAR’s Excellence in Agronomy Initiative (EiA). The study focuses on the challenges and successes encountered in promoting data sharing and compliance across CGIAR’s centers…

The lasting impact of advocating for and facilitating FAIR-informed practice in soil and agronomy

The case of the Coalition of the Willing (CoW) and Ethiopia’s Soil and Agronomy Data Sharing (SADS) directive. CABI worked with multiple partners to institute top-down and bottom-up interventions designed to ultimately improve yields and long-term sustainability for Ethiopia’s agricultural ecosystem via responsible data governance and FAIR practices…

How an effective ‘enabling learning environment’ can impact at an investment

The ACIAR Case Study. As a follow-up to a Small Research Activity, carrying out ‘An assessment of data management and FAIR data principles across the ACIAR research portfolio’, between Dec 2021 – September 2022, which utilized tools and learnings from EDA2, ACIAR awarded CABI a follow up contract. This follow up was to develop a FAIR data strategy for the Soil and Land Management (SLAM) program, a key research program under ACIAR…

Measuring the value of improving data governance and access.

Supporting Soil Health Interventions in Ethiopia. A Bill & Melinda Gates Foundation investment case study. In July 2019 the Centre for Agriculture and Bioscience International (CABI), partnered with the Open Data Institute (ODI) and commissioned a team of economists from the University of the West of England, Bristol (UWE) to measure the value of improving data governance and access in projects supported by foundation programmes…

Improving food security through harmonised soil data in South Asia

This case study presents what the Cereal Systems Initiative for South Asia learned about making data findable, accessible, interoperable and reusable as they developed a soil intelligence system…

Making soil data findable, accessible, interoperable, reusable and open

This case study presents how developing a community-driven soil database can support farmers in decision making…

Sharing Personal Data

This case study presents how the Worldwide Antimalarial Resistance Network (WWARN) having gathered, curated and enabled access to trial data from over 180,000 patients, and in doing so have made a significant contribution to the fight against drug resistance for one of the world’s deadliest infectious diseases.

Data Standards for Soil: Why aren’t they taking root?

This report explores why data standards for soil fail to take root. It highlights why data standards are crucial in a post-pandemic world and how they support resilience and build back better by helping us share better data. It also explores why data standards fail due to the approach, the resources, the environment and the pace.

FAIR and Open data alignment across excellence in agronomy initiative related organizations

The Bill & Melinda Gates Foundation believes that “Providing access to underlying data is key in fulfilling the foundation’s mission of rapid and free exchange of scientific ideas to move humanity forward by improving and saving lives. Without barriers the scientific community can freely benefit from data and build upon each other’s work.”

Incentive systems for research data sharing in funded projects

Sharing research data has shown to improve the findability of data and prevent duplication of effort. However, common cultures and practices in many research disciplines do not support data sharing. A ‘collective action problem’ means that there are commonly misalignments in incentives to cooperate around data – a mismatch of individual, institutional and societal wants and needs.

Anonymising data in agriculture

This guide will help grantees to navigate concerns over breaking legal obligations, security breaches or causing harm to individuals, communities or society. Specifically, it will help explain the techniques for anonymising personal data in agricultural development projects.

Open and FAIR Data Ecosytems Principles, Policies and Platforms

Rapidly evolving digital technologies are transforming the way in which research is conducted globally, with data science becoming the most important element across all domains.

The FAIR Journal

#1 Introducing FAIR data principles

Learn more about FAIR including news, views, explainers and research from agricultural development and the wider data ecosystem.

#2 Why FAIR?: The need for FAIR and responsible data

Explaining the potential benefits of FAIR data practices, its history and why improving data standards is crucial.

#3 A framework for implementing FAIR practices

Introducing a framework which distils the process for implementing FAIR data practices in investments.

#4 FAIR advocacy and knowledge sharing

Sharing examples of resources, knowledge building, and influencing and advocating for FAIR data practices and management.

#5 Making the case for FAIR

Why we need to change data culture in agricultural development so more people benefit from access to the right datasets.

#6 Mainstreaming FAIR principles

How FAIR principles can be implemented practically in agricultural development investments and why this is needed urgently.

#7 Impacts of FAIR and responsible data

Demonstrating how FAIR and responsible data practices can benefit agricultural development and beyond including FAIR for AI.

#8 The value of FAIR

Explore how FAIR practices can unlock value, and the potential economic and ROI gains of improved data practice.

#9 Where's the data?

FAIR Journal #9 is due this winter.