The Right to Data for Development (Bluenumber)

Arguments

A poor data environment for crop production generates damaging consequences, including low yields, minimum added value to the final products, and misuse of data.

Supporting facts:

• Inadequate data in crop production results in low crop yields and limited financial benefits for farmers.

• Misuse of data by different stakeholders across the value chain is a consequence of a poor data environment.

Topics: Crop Production, Data Environment, Misuse of Data

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Digital technologies such as artificial intelligence, remote sensing, and blockchain can transform how stakeholders interact with agri-food information and services.

Supporting facts:

• The digital technology-induced change demands principles of responsible and ethical digital transformation.

• Innovations should be socially, ethically, and environmentally sustainable.

Topics: Digital Technologies, Agri-food Information, Artificial Intelligence, Blockchain

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CIMMYT has a framework for responsible data systems for crop production, producing valuable information for other sectors.

Supporting facts:

• CIMMYT's framework includes accurate crop monitoring systems and research-based protocols for data collection and analysis.

• The system provides detailed information on management practices, associated costs, dosage requirements, and application practices.

Topics: CIMMYT, Responsible Data Systems, Crop Production

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Interoperability is crucial in agriculture data systems

Supporting facts:

• Interoperability is key to working in a bigger ecosystem

• Agriculture systems need to be mapped to the main ontologies to ensure interoperability

Topics: Agriculture, Data Interoperability

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CIMMYT is in a transformation process from a traditional way of extracting and using data to a more responsible framework

Supporting facts:

• CIMMYT is moving away from the traditional way of extracting data and using that data, towards a more responsible framework where the data belongs to the farmers.

Topics: Data Extraction, Data Stewardship, Transformation Process

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Data is an asset for the farmer.

Supporting facts:

• Farmers' data can be part of a value chain in terms of data, and data adds value that can change from owner to owner.

• Farmers have their data as an asset and decide who to share that data with.

Topics: Data Ownership, Value Chain, Farmers

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The same basic data set collected and protected by farmers can be part of a value chain.

Supporting facts:

• If an added value process, analysis, clustering, etc is done, it gives rise to a different level, a different owner and a different buyer.

Topics: Data Ownership, Value Chain, Farmers

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There is a right to data for development

Supporting facts:

• We are in the transformation process

Topics: Data rights, Development

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Report

The analysis highlights several important points regarding data in crop production and its impact on various stakeholders. It emphasises that a poor data environment can have detrimental effects, including low crop yields, limited financial benefits for farmers, and misuse of data.

Without adequate data in crop production, farmers may struggle to achieve optimal yields, leading to lower profits and reduced food production. In addition, the misuse of data by different stakeholders along the value chain is a consequence of a poor data environment, potentially leading to unethical practices or biased decision-making.

However, the analysis also acknowledges the transformative potential of digital technologies such as artificial intelligence, remote sensing, and blockchain in revolutionising how stakeholders interact with agri-food information and services. These technologies have the ability to enhance efficiency, accuracy, and traceability in crop production, enabling better decision-making and ensuring responsible and sustainable practices.

It is argued that the principles of responsible and ethical digital transformation should be upheld to ensure the social, ethical, and environmental sustainability of these innovations. Furthermore, the analysis highlights the importance of recognising crop data as an asset belonging to farmers.

It suggests that farmers should have the ability to sell their crop data directly to industry companies or ag-tech firms, thereby adding value to their products and improving their financial access. The argument is made that this data can also be used for credit scoring, enabling farmers to access financial services more easily.

By treating crop data as an asset, farmers have greater control over their data and can decide who to share it with, empowering them in the agricultural value chain. The responsible data systems framework developed by CIMMYT is commended for its contribution to crop production.

This framework includes accurate crop monitoring systems and research-based protocols for data collection and analysis. By providing detailed information on management practices, associated costs, dosage requirements, and application practices, this system generates valuable information not only for farmers but also for other sectors that rely on crop data.

This framework promotes responsible and transparent data practices, ensuring the efficient use of resources and promoting sustainable agriculture. The importance of interoperability in agriculture data systems is also highlighted. Interoperability refers to the ability of different systems and platforms to work together effectively and share information seamlessly.

It is argued that interoperability is crucial in agriculture data systems as it enables stakeholders to work in a larger ecosystem, facilitating the exchange of information and promoting collaboration. Agriculture systems need to be mapped to the main ontologies to ensure interoperability and enable the efficient exchange and utilisation of data.

Moreover, the analysis stresses the value of publishing historical datasets and making them accessible to all. By making historical data available, it allows for better analysis, insights, and informed decision-making. It also promotes transparency and accountability as historical data can be used to track progress, measure impact, and foster collaboration among stakeholders.

The analysis reveals that a historical dataset, collected over the years, is planned to be published and made accessible to the public, indicating a step towards greater data transparency and openness. CIMMYT's transition from a traditional approach to data extraction and use towards a more responsible framework is also discussed.

The organisation is moving away from the conventional practice of extracting and using data without active involvement or ownership by the farmers. Recognising the importance of data belonging to the farmers, CIMMYT aims to promote a more responsible framework where farmers have greater control and ownership over their data.

This shift reflects an increasing emphasis on data stewardship and empowering farmers in the decision-making process. The analysis also highlights the concept of data as an asset in the agricultural value chain. Farmers' data can be part of a value chain in terms of data, where its value can change as it moves from owner to owner.

Moreover, if additional value processes such as analysis or clustering are performed on the data, it can result in a different level of value, ownership, and potential buyers. Recognising data as an asset emphasizes the economic and strategic significance of data for farmers.

Furthermore, it is noted that CIMMYT is gradually transforming from being solely a data keeper to a data broker, facilitating conversations between different parties involved in crop production. CIMMYT acknowledges that this transition needs to go further, to address data ownership issues and promote a more inclusive and collaborative approach.

This change reflects the recognition of the importance of shared responsibility in data management and the need for data ownership to evolve in a way that benefits all stakeholders. The analysis also mentions the right to data for development, highlighting the transformation process currently underway.

This implies that access to data is seen as crucial for driving development, innovation, and partnerships to achieve the United Nations Sustainable Development Goals. It highlights the recognition that data plays a pivotal role in addressing various global challenges and promoting positive change.

In conclusion, the analysis showcases the various dimensions and perspectives related to data in crop production. It emphasises the need for a responsible data environment, where data is treated as an asset belonging to farmers, and ethical principles guide the use of digital technologies.

The responsible data systems framework developed by CIMMYT is praised for its valuable insights and contribution to the agricultural sector. Interoperability, publishing historical datasets, empowering farmers through data ownership, and promoting data stewardship are all crucial aspects highlighted in the analysis.

Ultimately, these insights contribute to a broader understanding of the importance of data in agriculture and the potential for responsible and sustainable practices to drive positive outcomes for farmers, stakeholders, and global development.

Arguments

Multiple stakeholders are collecting the same type of data from farmers, leading to data duplication and inconsistencies

Supporting facts:

• Farmers are registered in multiple platforms resulting in multiple identities

• Multiple organizations map out the same farmer's field and store the data independently

Topics: Data Collection, Agriculture, Policy-making, Farmers Data

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Country-specific approach is required for managing agricultural data

Supporting facts:

• The concept of a National Agricultural Data Infrastructure

• Proposed that there should be policies for data usage by private sector

• Suggested creation of a new technology framework to bridge existing data systems

Topics: Data Management, Agriculture, Policy-making

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A neutral entity is required to manage the National Agricultural Data Infrastructure

Supporting facts:

• If handled by government or private sector, trust may be an issue

• A neutral entity would ensure the trust of both private and public sectors

Topics: Agriculture, Data Management, Policy-making

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Need for a monetizable model with part of infrastructure open and part monetized

Supporting facts:

• The revenue model should be such that data contributors get a share

• Monetization would incentivize more comprehensive data collection and sharing

Topics: Data Monetization, Agriculture, Business Model

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The infrastructure being developed would pull standardized data points from various databases about Ghana if the databases are made discoverable

Supporting facts:

• There is a duplication in efforts by various development organizations, with each building different types of data about Ghana

• Some databases may not even be widely known thus leading to more investments in creating similar databases

• The infrastructure will enable Ghana to have some sovereignty over macro-level data which would be useful in responding quickly to crises.

Topics: Data Collection, Data Sharing, Data Standardization

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The steward or the custodian of data in a country should be a neutral entity

Supporting facts:

• The entity can be an entity constituted by both public and private NGO research that represent all of them

• It's not government

Topics: Data stewardship, Data economics, Digital sovereignty

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Government should drive the process of data stewardship, but not to be the custodian of the data

Supporting facts:

• All data holders or data owners, companies may be data holders

• The data is the cash, is the currency that they are bringing

Topics: Data stewardship, Government role, Data protection

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Individual farmers don't have the right to their data for development.

Topics: Digital Democracy, Data Rights, Data for Development

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Report

Multiple stakeholders are collecting the same type of data from farmers, resulting in data duplication and inconsistencies. This issue highlights the need for a country-specific approach to effectively manage agricultural data. To address this, a National Agricultural Data Infrastructure is proposed, which will serve as a centralized system for collecting, storing, and managing agricultural data.

One key aspect of this infrastructure is the involvement of a neutral entity to oversee its management. This neutral entity will gain the trust of both the private and public sectors, ensuring fair and unbiased data management practices. By having a central authority, the duplication of efforts and inconsistencies in data can be avoided, leading to more accurate and reliable information.

To incentivize comprehensive data collection and sharing, a monetizable model is suggested. This model will allow data contributors to receive a share of the revenue generated from the use of their data. This approach not only encourages data sharing but also promotes a more comprehensive understanding of agricultural practices and trends.

Furthermore, the control and sovereignty of agricultural data should be in the hands of individual countries. National data infrastructures offer a solution by providing a centralized system that allows countries to have greater control over their own data. This control enables them to respond quickly to crises and make informed policy decisions.

The ongoing development of an infrastructure in Ghana is a notable example. The infrastructure aims to pull standardized data points from various databases, increasing discoverability and accessibility of information about the country. While datasets from different organizations will still be maintained independently, a portion of the data will feed into the central system, ensuring its integration and overall data integrity.

Regarding the custodian of data, it is suggested that a neutral entity, consisting of both public and private NGO research entities, should be responsible. This approach ensures that data stewardship is carried out impartially, without undue influence from any specific organization or the government.

While the government is expected to play a vital role in driving data stewardship, it is important that it does not become the custodian of the data. Instead, the government should focus on creating policies and regulations that promote data management and protection.

It is crucial to note that individual farmers currently do not have the right to their data for development. This lack of ownership hinders the potential for farmers to utilize their own data effectively. However, there is a growing understanding of the importance of individual data rights for development, and it is an area that requires further exploration and refinement.

In conclusion, the management of agricultural data requires a country-specific approach, including the establishment of a National Agricultural Data Infrastructure. This infrastructure should be overseen by a neutral entity and incorporate a monetizable model to ensure comprehensive data collection and sharing.

Countries should have control and sovereignty over their agricultural data, and national data infrastructures provide a means to achieve this. The ongoing development in Ghana serves as an example of how standardized data can be leveraged from various databases. The custodian of data should be a neutral entity, while the government drives the process of data stewardship.

Individual farmers currently lack ownership of their data for development, highlighting the need for further attention in this area.

Arguments

The role of a data steward is vital in shaping the value derived from data

Supporting facts:

• A data steward makes important decisions about who can access the data and for what purpose

• Access to data is vital to drive value and new technologies such as AI rely on it

• Data stewardship role is still evolving and needs to be iterative due to changing context and technologies

Topics: Data Stewardship, Power Imbalances, Public Benefit

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There is no universal type of good data steward, it depends on the context

Supporting facts:

• Elea mentioned that governments might be good data stewards if they recognize the value of data and invest in data stewardship

• In a context where there's a lot of extractive practices, data stewardship might not make sense

Topics: Data Stewardship, Government, Companies

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Individuals could be data stewards

Supporting facts:

• participatory model where the individual is the data steward

• it's sustainable in form of a kind of engagement of the individual in this data ecosystem

Topics: Data Stewardship, Data Ownership, Data Sharing, Data Ecosystem

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Report

Data stewardship plays a vital role in shaping the value derived from data. Data stewards are responsible for making important decisions about data access and usage, considering power imbalances and prioritising the public benefit. Access to data is crucial for driving innovation and technological advancements, particularly with the rise of AI.

The role of data stewardship is evolving and needs to be adaptable to changing contexts and technologies. However, data stewardship goes beyond access and must address power imbalances in data sharing. Collaboration between public and private entities is necessary to ensure the public benefit and avoid potential harms and structural inequalities caused by poor data stewardship.

Governments can be effective data stewards if they recognise the value of data and invest in data stewardship. However, in environments with extractive practices, the relevance and effectiveness of data stewardship may be diminished. An exemplary case of successful data stewardship is the UK Biobank.

They have managed sensitive data without any leaks, providing significant value for public research in health and well-being. Individuals can also participate as data stewards in a participatory data ecosystem, where they manage their own data. This model promotes sustainability and engagement, but it has limitations and may not be feasible for everyone.

In summary, the role of a data steward is crucial in shaping the value derived from data. They make important decisions about data access and usage, addressing power imbalances and prioritising the public benefit. Effective data stewardship requires collaboration between public and private entities.

Governments, like the UK Biobank, can be effective stewards if they invest in data stewardship. Additionally, individuals can participate in a participatory data ecosystem, but limitations exist. Data stewardship must continue to evolve and adapt to navigate the complex landscape of data sharing and usage.

Arguments

The discussion is centered around the question what does an actor in a developing economic context need as rights to contribute to and benefit from the digital economy

Supporting facts:

• It is important for individuals in developing economies to establish their body of data in the digital economy.

• This digital data is increasingly required along with the product that the farmer creates in supply chain.

Topics: Data Rights, Economic Development, Digital Economy

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The value of data to the economy of a developing country or situation has to be emphasized.

Supporting facts:

• Data provides insights into the economic framework of a community.

• This session will discuss how research, policy making, open data ecosystems, and data infrastructure can be leveraged to create shared wealth.

Topics: Data Value, Economic Development, Digital Economy

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Decoupling the data as a separate product from the cotton product.

Supporting facts:

• The data created at each tier of the supply chain can be transmitted further, allowing adding of information and deriving benefits.

Topics: Agriculture, Data Management, Supply Chain

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Data is not free; it's very valuable and can be costed

Supporting facts:

• Sourcery has demonstrated that data is not free but holds significant value.

Topics: Data valuation, Information asymmetry

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Information or data asymmetry in the value chain needs to be addressed

Supporting facts:

• Data remains the property of the ones who created it

Topics: Data ownership, Fair Trade

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Significance of robust data collection and management in agri-food sector

Supporting facts:

• The speaker, Andrea, highlights the importance of a robust data environment for crop production and how poor data can lead to damaging consequences

• CIMMYT has been developing responsible data systems for crop production that include robust crop monitoring systems and research-based protocols for data collection and analysis

• Efficient use of data leads to optimized agricultural practices, enhanced yields, increased access to financial services and improved sustainability

• CIMMYT's data management environment, Agrology, incorporates several tools for data collection, management, analysis, and visualization

Topics: Innovation, Data monitoring and systems, Data-driven agronomy, Crop production

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Puvan Selvanathan raises a concern about the creation of numerous national data systems leading to new data silos

Supporting facts:

• Puvan observes that if each country develops its own national data systems, it could result in the creation of 192 different data silos, thus becoming an additional barrier to data integration and sharing.

Topics: Data Management, Agriculture, National Data Systems, Data Sovereignty

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Puvan Selvanathan expresses concern about the ownership and responsibility of data once it's made public

Supporting facts:

• All Ghana's data sets are being made public and published

• The data is sitting in servers in Mexico

Topics: Data Ownership, Data Responsibility, Public Data

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Puvan Selvanathan unpacks the idea of national data sovereignty and the need for standardized data-sharing mechanisms

Supporting facts:

• He talks in the context of duplication of data collection and storage efforts by development organizations

• Suggests that at least having viewership access to various databases might be a significant step towards a cohesive data landscape

Topics: Data sharing, National sovereignty, API

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Puvan Selvanathan believes that companies in the textile industry, like Ruchita Chhabra's, may lead in the race for local and regional data collection and usage

Supporting facts:

• Companies in the textile industry, according to Ruchita Chhabra, have been lagging behind in data collection, relying on life cycle assessments or generic regional data

• Puvan suggests that these companies may quickly move to the forefront as they redefine the market mechanisms involved.

Topics: Textile Industry, Data Collection, Market Mechanism

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Different types of data stewards needed once the concept is accepted

Supporting facts:

• Different roles different data stewards can take in UK Biobank has been good steward by giving responsible access to important data

Topics: Data Stewardship, Data Economy, Digital Sovereignty

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Custodian or steward of the data in a country should be a neutral entity

Supporting facts:

• This entity could consist of both public and private NGOs, research bodies

Topics: data management, data ownership, data stewardship

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Avoid duplicative and redundant data

Supporting facts:

• Redundancy of multiple silos of the same data is considered wasteful

• The fatigue associated with constantly reproducing data should be avoided

• Data should not be treated in an analog fashion

Topics: Data stewardship, Data use

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Creation and use data steward role

Supporting facts:

• A new type of actor, possibly a 'unicorn-type' data steward is required

• Existing actors might be limited as their role is beyond their current boundary

• This new role will lead the path of transformation

Topics: Data steward, Data handling

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Questioning the need for institutions in data stewardship

Supporting facts:

• Individuals, not institutions, may be capable of stewarding data as data creators and owners

• Data gains value when shared and transacted, a function that individuals could fulfill

Topics: Data steward, Data Institutions

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Report

The discussion centers around the rights and value of data in the digital economy, particularly in developing economies. It emphasizes the need for individuals to establish their presence in the digital data landscape and highlights the increasing importance of data in the supply chain.

Farmers entering the digital economy should have a say in the rules and regulations governing data ecosystems. The value of data to a developing country's economy is emphasized, along with the need to monetize and source additional income through data.

Data literacy and understanding are crucial to address information asymmetry and ensure fair participation in the digital economy. In the agricultural sector, robust data collection and management are essential for optimizing practices, enhancing yields, and increasing sustainability. The decentralization of data benefits both the community and the economy, allowing for traceability and provenance claims.

Concerns are raised about the creation of national data systems and the need for effective cross-border data flow. Data protectionism is cautioned against, and the textile industry is seen as having the potential to lead in data collection and usage.

There is optimism about the outcomes of current conversations surrounding data usage, with a focus on setting farm data standards. The need for different types of data stewards is highlighted, and the redundancy and duplication of data are seen as wasteful.

In conclusion, the discussion emphasizes the importance of data rights and value in the digital economy, the need for data literacy and understanding, and the significance of robust data collection and management. The potential of the textile industry, concerns about national data systems, and the role of data stewards are also discussed.

Arguments

Smallholder farmers are becoming providers of free data to businesses

Supporting facts:

• Data has been helpful for farmers in terms of agri-inputs, services, finance information and market linkages

• Companies use farmer's data to add value to their own business and derive benefits

Topics: Data Economy, Smallholder Farmers, Agriculture

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Sourcery's direct to grow program makes farmers data entrepreneurs

Supporting facts:

• Program integrates trade facilitation with verification and assurance, making farmers not just data providers but controllers and owners of their data

• Farmers can lease their data to other partners and get fair compensation

Topics: Agriculture, Data Economy, Digital Economy

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Decoupling of data from cotton product, allowing it to be transmitted through the supply chain

Supporting facts:

• Different tiers in supply chain can add information to data

• The decoupling can open a new source of income

Topics: Data decoupling, Supply chain, Cotton industry

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The textile industry is behind in terms of utilizing data

Supporting facts:

• Most companies are making claims based on life cycle assessments or generic data

• Local regional data collection is being promoted

Topics: Textile Industry, Data Utilization

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Discussions on applying farm data standards at a national level are emerging

Supporting facts:

• The topic has only just begun

Topics: Farm Data Standards, Agriculture Industry

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Ruchita Chhabra believes that farmers becoming data stewards would give them more visibility and upgrade their status

Supporting facts:

• Sourcery is working on a new initiative to make farmers data stewards

• Currently, farmers feel ignored and left out of the data collection process

Topics: Data Stewardship, Farmers, Data Brokering, Agricultural Data

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Farmers do not currently have the right to sell their data, but this is changing

Topics: Farmers' Rights, Data Management

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Report

The debate centers around whether smallholder farmers should be included in the data economy and be compensated for the data they provide. One argument states that smallholder farmers are essentially giving away their data for free, becoming providers of free data to businesses.

This can be seen in the fact that data has been helpful for farmers in terms of agri-inputs, services, finance information, and market linkages. Companies use this data to add value to their own business and derive benefits from it.

The sentiment regarding this argument is negative, implying that farmers are disadvantaged in this scenario. On the other hand, there is an argument that proposes a different perspective. It suggests that smallholder farmers have the potential to become data entrepreneurs and lease their data to other partners, receiving fair compensation for their contributions.

One program that supports this viewpoint is Sourcery's direct-to-grow program, which aims to transform farmers into data entrepreneurs. By integrating trade facilitation with verification and assurance, this program enables farmers not only to provide data but also to control and own it.

The sentiment regarding this argument is positive. Legislation that aims to make supply chains traceable and transparent is also placing pressure on brands. This development is significant because it can benefit farmers. Mounting legislation requires brands to know the origins of their products and demonstrate that they have been produced ethically and sustainably.

As a result, brands are using environmental data provided by farmers to avoid hefty levies and appeal to their ethical consumer base. This serves as evidence that farmers' data can have a real impact and value in the marketplace. The sentiment regarding this argument is positive.

Moreover, the decoupling of data from cotton products has emerged as another topic of discussion. This decoupling allows data to be transmitted through the supply chain and presents an opportunity for farmers to generate an additional source of income. This argument, which supports the decoupling, is viewed positively.

Ruchita Chhabra, in particular, supports the idea of data decoupling and sees it as a means to empower farmers by providing them with another source of income. Her stance aligns with the sentiment expressed in this argument. Despite the potential benefits, certain sectors, such as the textile industry, have been slower to embrace the opportunities provided by data.

Many companies in the textile industry still rely on claims based on generic data or life cycle assessments, rather than utilizing more specific local or regional data. This implies that there is still progress to be made in terms of utilizing data effectively within the textile industry.

The sentiment surrounding this argument is negative. Discussions on applying farm data standards at a national level have also begun. While the supporting facts for this argument are minimal, it suggests that there is recognition for the need to establish standards for handling agricultural data.

These discussions could potentially lead to greater regulation and protection for farmers' data. The sentiment regarding this argument is neutral. Additionally, it is highlighted that farmers currently feel ignored and left out of the data collection process. Ruchita Chhabra believes that making farmers data stewards would give them more visibility and upgrade their status.

By becoming data stewards, farmers would have a more active role in the data collection and analysis process, leading to increased recognition and potentially improved outcomes for farmers within the data economy. The sentiment towards this argument is positive. Lastly, it is noted that farmers do not currently have the right to sell their data, but this is changing.

The sentiment regarding this argument is neutral. It suggests that there is a shift happening in terms of farmers' rights to their data, although it is not an immediate change. Instead, it is a process that is starting to take shape.

In conclusion, the debate surrounding smallholder farmers' involvement in the data economy and their right to be compensated for their data contributions is complex. One viewpoint argues that farmers are currently providing data for free, while another suggests that they have the potential to become data entrepreneurs and earn fair compensation.

Mounting legislation and initiatives like data decoupling present opportunities to empower farmers and provide them with additional income sources. However, certain sectors, such as the textile industry, are lagging behind in effectively utilizing data. The discussions on farm data standards, farmers' rights to sell their data, and making farmers data stewards further highlight the ongoing evolution in this space.

Overall, change is a gradual process that is beginning to take shape, and recognition for farmers' contributions and rights in the data economy is gaining momentum.