Theme Specific Highlights - Digital and data sovereignty
The sessions under the theme of digital and data sovereignty focused on the importance of putting farmers and other agri-food system actors in control of their data, as well as giving them an increased stake in the governance and decision making of digital solutions. The sessions also pointed out the benefits and potential pitfalls of using technologies in the agriculture space. Some of the challenges and potential solutions discussed include:
1
Smallholder farmer’s lack of control over their data
2
Absence of open source platforms due to existing data gaps
3
Lack of use of Agri 4.0. solutions in decision-making
Challenge: Smallholder farmer’s lack of control over their farm data
Digitization is accelerating the transformation of the agriculture sector in LMICs at an unprecedented rate, resulting in the generation of a large amount of data. However, laws to protect this data and ensure judicious use need to be strengthened. Provisions are needed to ensure the data is collected and used only for the specific activities to which the contributor has consented and for which the contributor has been compensated.
However, existing constraints such as limited access, awareness, and low-literacy level of smallholder farmers, limit their capability to exert control over their personal data. This data is used for many purposes by agri corporates and product companies, from product development to go-to-market strategy formulation. Low data sovereignty in agricultural value chains presents various risks and missed opportunities.
POTENTIAL SOLUTION: It is important to undertake a detailed study to understand the interventions required to build data sovereignty across the agriculture value chain. Accordingly, technology providers in the public and private sectors have to work in sync to implement data sovereignty by utilizing advanced technologies like blockchain, decentralization and web3. Also, existing laws need to be strengthened or new laws enacted to ensure the collection and usage of data is restricted to specific activities for which the contributor has provided consent and for which they have been compensated.
A) Under GIZ’s i4Ag fund, Dalberg Data Insights enterprise recently finalized a study on data sovereignty that makes recommendations on how to improve control over data for smallholder farmers.
This study identified three types of interventions to build data sovereignty in agricultural value chains-
Strengthen the enabling environment and the capacity of farmers. For example- Indian Digital Ecosystem for Agriculture (IDEA).
Establish the foundational layer of the data sovereignty platform with the public sector. For example FarmStack software via the Digital Agriculture Advisory Services (DAAS), Ethiopia.
Enable usability and sharing of data with the private sector. For example the International Dairy Data Exchange Network.
If successfully implemented, these interventions can enable farmers to generate direct income, in-kind value, non-monetary gains, as well as other indirect benefits.
B) Digital Green developed the FarmStack solution with support from BMGF, the UK’s Foreign, Commonwealth and Development Office, and Walmart Foundation.
FarmStack is an open-source protocol that powers the secure transfer of data. It works on codifying data exchange among farmers and other stakeholders, in which a data provider (farmers) can share their data in a protected way with the data consumer and have that be enforceable in software. This solution uses a distributed ledger or a blockchain to bring in decentralization in data storage, such that instead of a single host or owner there is distributed ownership of the data. In addition, smart contracts embed certain types of logical parameters, with respect to particular conditions. Hence, FarmStack enables secure data exchanges that reduce costs for the organizations and secure farmers' data.
Challenge: Absence of open source platforms due to existing data gaps
Digital Public Goods (DPGs) are an amalgamation of digital content, software, and data that are open and freely accessible. Open data platforms form a critical component of digital public goods as they enable evidence-based decisions without requiring stakeholders to spend resources on data collection. Open data platforms such as DPG in the Global South, that focus on creating enabling environments required to develop such platforms as well as exploring the use of models that present data-as-a-Service, can play a key role in empowering stakeholders. However, there are significant data gaps that prevent satellite-based analytics from achieving scale in emerging markets and, in turn, the creation of open source comprehensive data platforms. This is primarily due to a scarcity of high-quality on-ground information and training to power predictive analytics.
POTENTIAL SOLUTION: Integrating field data with remote sensing data and predictive analytics has the potential to generate accurate data to fill in existing gaps and in the creation of open-source comprehensive data platforms. This data may be used by the solution providers to design specific products/ solutions for smallholder farmers.
Enabling Crop analytics at Scale (ECAAS) by Tetra Tech is based on remote sensing and has the potential to provide foundational insights around crop area estimation, yield forecasting, field boundary detection and object identification.
ECAAS is a multiphase project funded by the Bill & Melinda Gates Foundation. Using its Tetra Tech Delta technology enablement program, Tetra tech is supporting innovation, community partnerships, and data sharing infrastructure to better collect, process, and share high-quality georeferenced training data for ML models. The solution focuses on two aspects: lowering the cost and increasing options for collecting ground truth and training data through technological innovations; and increasing access and incentivizing sharing of ground truth and training data collected by various organizations.
Through the ECAAS project, Tetra Tech facilitates the scaling of ground-truth datasets through a network approach and is governed by common standards for data collection and exchange established by organizations working in this space. ECAAS currently serves as one distinct network hub where other organizations collaborate to generate precise ground data. For example, organizations like Farmerline, ICRISAT, and 6th Grain have collaborated under ECAAS. These organizations use AI, ML, and crop analytics solutions for next-generation field boundary mapping, crop production analytics, and data sharing platforms to validate the ground data.
Better ground data combined with the satellite data and predictive analytics provide better statistics. This will result in an improved food system by providing region-specific information for inputs and extension services throughout the growing season.
Challenge: Lack of use of Agri 4.0 solutions in decision making
In the past decade, the role of technology in agriculture has increased significantly and will continue to do so, driven by population increase and dwindling agricultural land and resources. Artificial Intelligence (AI), Machine Learning (ML), remote sensing, and other 4.0 technologies are steadily emerging as important tools in improving quality and productivity across the agriculture value chain. Despite the availability of numerous tools and solutions, decision makers and governments face challenges in implementing agri 4.0-based solutions. This limits learnings on agricultural outcomes for smallholder farmers that are necessary to drive better agricultural project design, investment, and implementation.
POTENTIAL SOLUTION: To take informed decisions and to frame favorable policies, decision makers have to adopt a data-driven approach to gain deeper insights into the issues. Selection and application of the right digital tools may provide useful insights and facilitate this decision-making process.
Development Gateway, under the VIFAA Program, is working along with the International Fertilizer Development Center (IFDC) and Wallace & Associates with support from the Bill & Melinda Gates Foundation, on the development of dashboards and tools to improve, manage, and visualize fertilizer data in Africa.
The objective of this program is to strengthen data supply and support policies and investments to improve affordability, availability, and quality of fertilizers. Currently, the program is focused on Kenya, Nigeria, and Ghana. VIFAA uses Machine Learning and works with Quantitative Engineering Design to develop context-specific, easy-to-understand dashboards that provide sector performance insights to decision-makers.
