Jeremy de Beer
I shape ideas about technology innovation, intellectual property, and global trade & development. I am a Full Professor in the Faculty of Law at the University of Ottawa, as well as a practicing lawyer and expert consultant.
Find me and all of my scholarship online at www.JeremydeBeer.ca.
Find me and all of my scholarship online at www.JeremydeBeer.ca.
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DATA-DRIVEN AGRICULTURE – OPPORTUNITIES FOR FARMERS
Beyond the technological developments, data – on, by, of and for farmers and their products – has become a growth area, driving expectations and investments in big data, blockchain technology, precision agriculture, farmer profiling and e-extension. Investing in data-driven agriculture is expected to increase agricultural production and productivity, help adapt to or mitigate the effects of climate change, bring about more economic and efficient use of natural resources, reduce risk and improve resilience in farming, and make agri-food market chains much more efficient. Ultimately, it will contribute to worldwide food and nutrition security. Data-driven agriculture uses big data to supplement on-farm precision agriculture – using the right farm data, at the right time and in the right formats to make better decisions. It is already being applied, big time, in many developed countries and market-oriented agri-food chains. It is being tested in many developing countries to see where data yields can be highest.
ACCESS AND SHARING – TWO MAJOR CHALLENGES
Data-driven digital agriculture offers many opportunities across the sector. It is not, however, a panacea, especially for developing-country smallholders who must overcome challenges and risks to ensure that digital investments generate dividends. For the smallholders, the two main challenges are, first, to gain access to relevant data and services provided by others and, second, to make sure that any data they share does not actually weaken their positions.
FOUR STREAMS OF DATA – BY AND FOR FARMERS
Four streams of data that farmers typically use (access or share) are identified: The first stream is ‘localized’ data Executive Summary generated and collated on the farm for use only on the farm. The second stream is ‘imported’ data generated and collated off the farm, for use on the farm. The third stream is ‘exported’ data generated and collated on the farm for use off the farm. The fourth stream is ‘ancillary’ data generated and collated (on and) off the farm, mainly for use off the farm. The opportunities, challenges and risks for farmers are different in each stream. Localized and imported data, when clearly focused to on-farm situations underpin and drive good decision making on farms. From a farmer perspective, data shared (exported) by farmers locally and globally should provide ‘win-win’ results in terms of more relevant services and products (from forecasts to logistics to advice) they a farmer can access. ‘Localized’ and ‘ancillary’ data streams don’t present special access challenges to farmers as they are either completely inside the farm or completely outside. ‘Imported’ data presents all the challenges of availability, accessibility and usability, with data and services offered needing to be adjusted to what farmers need and can handle. ‘Exported’ data streams present all the risks and benefits around sharing, with added safeguards necessary to avoid exploitation of what the farmers share.
DATA INTERMEDIARIES AND INTEGRATION
The providers, enablers and handlers of data-driven services for and with farmers are critical actors in agri-food data systems. They find and transform raw data into actionable information and decision-making tools. They need to know the real needs of the farmers on the one hand and to find and understand the necessary data on the other. They must understand the standards, formats and licenses as well as the data collection practices including measurements and biases and make it useful. They need to win the trust of data providers and users, safeguarding ownership and striving for equitable access. Data standardization is one of the biggest challenges these data intermediaries face and different pathways to developing standards can be followed.
CHALLENGES FOR SMALLHOLDERS
Smallholders are tough to reach and thus many initial data service offerings have been designed for larger and more commercial operations. Following a ‘bottom of the pyramid’ logic, smallholders have much to offer any service providers and intermediaries like farmer organizations who are able to design and deliver data-driven services at large scale. Smallholders also have much to gain from data – small improvements in their operations are likely to provide larger gains at household level, proportionally, and, if the improvements are widely adopted, the whole agricultural sector in many countries that depend on smallholder agri-food systems can be transformed. However, for smallholders to benefit from data-driven agriculture, tools and applications need to be designed for their specific situations and capacities; they – and the organizations that support them – need to grow their capacities to become smart data users and managers; measures are needed to ensure that farmer-generated data is not exploited or misused; and smallholders, usually the least powerful parts of a value chain, must grasp every opportunity to be included in the collective data flows within agri-food systems.
FACILITATING DATA USE BY SMALLHOLDERS – DRIVERS FOR CHANGE
Data-driven agriculture offers opportunities and poses threats to smallholder farmers. Making data-driven agriculture smallholder-friendly should be guided by two sets of drivers. Important agri-food system drivers that determine the effectiveness of data-driven improvements that need to be tackled include: developing appropriate policies and related institutions and structures; devising incentives that deliver benefits to smallholders; developing capacities of farmers and small and medium entrepreneurs and institutional capacities to manage support systems for data and information sharing and exchange; extending the availability and affordability of hardware, software and data; developing needs-based data and software; and providing necessary infrastructure and connectivity within the reach of smallholders. Important data system drivers that need to be factored into investments in this area include: developing ‘apps’ for farmers that enable localized and specific solutions; using open agricultural data and standards that facilitate transparent, equitable and wide use and re-use of data; using ICTs and data to create jobs and make agriculture attractive to young people; investing in new data handling technical developments like big data, blockchain and Internet of Things that will make data value chains more powerful and transparent; strengthening institutions that enable equitable governance of data, locally to globally; and promoting joint actions on data by smallholders and their representatives through farmer organizations, cooperatives, associations, enterprises, etc.
DEVELOPING SMALLHOLDER-FRIENDLY DATA ECOSYSTEMS
The final section of the paper presents three priority actions to help develop a data ecosystem to support smallholders. • First, farmer data and services based around data should be aggregated through joint action that empowers and gives voice to farmers; • Second, trust centers, platforms and mechanisms that enable open data sharing should be established at different levels; • Third, international agreements to facilitate data access, ownership and flows should be developed. While many different actors need to be involved in these action areas, there are especially clear and present opportunities for groups (associations, federations, cooperatives, social enterprises, etc.) that represent and aggregate smallholders to step up their digital investments and capabilities so their members can grasp the opportunities offered by data-driven agriculture.
The chapter begins with a contextualization of PPPs in global governance generally and their evolution within sustainable development efforts. It then introduces Open AIR. The following section links various elements of Open AIR to potential characteristics of PPPs, emphasizing six features that have resulted in successful interventions: Cross-sector representation; novel approaches to problem-solving; cross-regional approaches; complex methods; networking of networks; interdisciplinary analysis; and a shared vision. The chapter then discusses the nexus of partnerships such as Open AIR to sustainable development, and reflects on policy ramifications, practical lessons, and limitations of the cross-regional research partnership model applicable to development PPPs.
Following an introduction in Part I, Part II of this article explores Canada’s new legal framework for the recreational cannabis market in light of the current political and legal environment. Part III surveys intellectual property regimes that may be most relevant to recreational cannabis, including plant breeders’ rights, patents, and trademarks. Part IV superimposes these regimes to reveal the issues likely to shape this industry. We consider legal- scientific issues, such as whether it is technically feasible to breed cannabis with protectable traits. And, we consider legal-commercial issues, such as whether restrictions on cannabis- related advertising might impact the use of cannabis trademarks.
We conclude, in Part V, that the use of IPRs to control the breeding, production, and distribution of recreational cannabis could lead to two plausible scenarios. A craft-based industry would have little use for patents or plant breeders’ rights, instead using trademarks to provide quality assurance in a market with simple and direct supply chains. A commodity-based industry would rely more heavily on patents and plant breeders’ rights to protect significant investments in cannabis breeding, and likely see separation between the roles of breeders and growers. We anticipate seeing elements of both markets in the near future. In the longer term, which type of cannabis industry materializes will depend, in part, on answers to the key legal questions we raise in this article.
The chief policy lesson from this paper is that moving to a model where data is open as default requires change in legal, social and technological norms, which all influence ownership of agriculture and nutrition data. Copyrights are not the only, nor even most important, legal rights establishing ownership of data. Relevant legal rights that facilitate access to and use of data at the international, national and subnational level include copyrights, database rights, technical protection measures, trade secrets, and patents and plant breeders’ rights, privacy and even tangible property rights. The open data community must broaden its engagement in all these areas to address emerging challenges."
DATA-DRIVEN AGRICULTURE – OPPORTUNITIES FOR FARMERS
Beyond the technological developments, data – on, by, of and for farmers and their products – has become a growth area, driving expectations and investments in big data, blockchain technology, precision agriculture, farmer profiling and e-extension. Investing in data-driven agriculture is expected to increase agricultural production and productivity, help adapt to or mitigate the effects of climate change, bring about more economic and efficient use of natural resources, reduce risk and improve resilience in farming, and make agri-food market chains much more efficient. Ultimately, it will contribute to worldwide food and nutrition security. Data-driven agriculture uses big data to supplement on-farm precision agriculture – using the right farm data, at the right time and in the right formats to make better decisions. It is already being applied, big time, in many developed countries and market-oriented agri-food chains. It is being tested in many developing countries to see where data yields can be highest.
ACCESS AND SHARING – TWO MAJOR CHALLENGES
Data-driven digital agriculture offers many opportunities across the sector. It is not, however, a panacea, especially for developing-country smallholders who must overcome challenges and risks to ensure that digital investments generate dividends. For the smallholders, the two main challenges are, first, to gain access to relevant data and services provided by others and, second, to make sure that any data they share does not actually weaken their positions.
FOUR STREAMS OF DATA – BY AND FOR FARMERS
Four streams of data that farmers typically use (access or share) are identified: The first stream is ‘localized’ data Executive Summary generated and collated on the farm for use only on the farm. The second stream is ‘imported’ data generated and collated off the farm, for use on the farm. The third stream is ‘exported’ data generated and collated on the farm for use off the farm. The fourth stream is ‘ancillary’ data generated and collated (on and) off the farm, mainly for use off the farm. The opportunities, challenges and risks for farmers are different in each stream. Localized and imported data, when clearly focused to on-farm situations underpin and drive good decision making on farms. From a farmer perspective, data shared (exported) by farmers locally and globally should provide ‘win-win’ results in terms of more relevant services and products (from forecasts to logistics to advice) they a farmer can access. ‘Localized’ and ‘ancillary’ data streams don’t present special access challenges to farmers as they are either completely inside the farm or completely outside. ‘Imported’ data presents all the challenges of availability, accessibility and usability, with data and services offered needing to be adjusted to what farmers need and can handle. ‘Exported’ data streams present all the risks and benefits around sharing, with added safeguards necessary to avoid exploitation of what the farmers share.
DATA INTERMEDIARIES AND INTEGRATION
The providers, enablers and handlers of data-driven services for and with farmers are critical actors in agri-food data systems. They find and transform raw data into actionable information and decision-making tools. They need to know the real needs of the farmers on the one hand and to find and understand the necessary data on the other. They must understand the standards, formats and licenses as well as the data collection practices including measurements and biases and make it useful. They need to win the trust of data providers and users, safeguarding ownership and striving for equitable access. Data standardization is one of the biggest challenges these data intermediaries face and different pathways to developing standards can be followed.
CHALLENGES FOR SMALLHOLDERS
Smallholders are tough to reach and thus many initial data service offerings have been designed for larger and more commercial operations. Following a ‘bottom of the pyramid’ logic, smallholders have much to offer any service providers and intermediaries like farmer organizations who are able to design and deliver data-driven services at large scale. Smallholders also have much to gain from data – small improvements in their operations are likely to provide larger gains at household level, proportionally, and, if the improvements are widely adopted, the whole agricultural sector in many countries that depend on smallholder agri-food systems can be transformed. However, for smallholders to benefit from data-driven agriculture, tools and applications need to be designed for their specific situations and capacities; they – and the organizations that support them – need to grow their capacities to become smart data users and managers; measures are needed to ensure that farmer-generated data is not exploited or misused; and smallholders, usually the least powerful parts of a value chain, must grasp every opportunity to be included in the collective data flows within agri-food systems.
FACILITATING DATA USE BY SMALLHOLDERS – DRIVERS FOR CHANGE
Data-driven agriculture offers opportunities and poses threats to smallholder farmers. Making data-driven agriculture smallholder-friendly should be guided by two sets of drivers. Important agri-food system drivers that determine the effectiveness of data-driven improvements that need to be tackled include: developing appropriate policies and related institutions and structures; devising incentives that deliver benefits to smallholders; developing capacities of farmers and small and medium entrepreneurs and institutional capacities to manage support systems for data and information sharing and exchange; extending the availability and affordability of hardware, software and data; developing needs-based data and software; and providing necessary infrastructure and connectivity within the reach of smallholders. Important data system drivers that need to be factored into investments in this area include: developing ‘apps’ for farmers that enable localized and specific solutions; using open agricultural data and standards that facilitate transparent, equitable and wide use and re-use of data; using ICTs and data to create jobs and make agriculture attractive to young people; investing in new data handling technical developments like big data, blockchain and Internet of Things that will make data value chains more powerful and transparent; strengthening institutions that enable equitable governance of data, locally to globally; and promoting joint actions on data by smallholders and their representatives through farmer organizations, cooperatives, associations, enterprises, etc.
DEVELOPING SMALLHOLDER-FRIENDLY DATA ECOSYSTEMS
The final section of the paper presents three priority actions to help develop a data ecosystem to support smallholders. • First, farmer data and services based around data should be aggregated through joint action that empowers and gives voice to farmers; • Second, trust centers, platforms and mechanisms that enable open data sharing should be established at different levels; • Third, international agreements to facilitate data access, ownership and flows should be developed. While many different actors need to be involved in these action areas, there are especially clear and present opportunities for groups (associations, federations, cooperatives, social enterprises, etc.) that represent and aggregate smallholders to step up their digital investments and capabilities so their members can grasp the opportunities offered by data-driven agriculture.
The chapter begins with a contextualization of PPPs in global governance generally and their evolution within sustainable development efforts. It then introduces Open AIR. The following section links various elements of Open AIR to potential characteristics of PPPs, emphasizing six features that have resulted in successful interventions: Cross-sector representation; novel approaches to problem-solving; cross-regional approaches; complex methods; networking of networks; interdisciplinary analysis; and a shared vision. The chapter then discusses the nexus of partnerships such as Open AIR to sustainable development, and reflects on policy ramifications, practical lessons, and limitations of the cross-regional research partnership model applicable to development PPPs.
Following an introduction in Part I, Part II of this article explores Canada’s new legal framework for the recreational cannabis market in light of the current political and legal environment. Part III surveys intellectual property regimes that may be most relevant to recreational cannabis, including plant breeders’ rights, patents, and trademarks. Part IV superimposes these regimes to reveal the issues likely to shape this industry. We consider legal- scientific issues, such as whether it is technically feasible to breed cannabis with protectable traits. And, we consider legal-commercial issues, such as whether restrictions on cannabis- related advertising might impact the use of cannabis trademarks.
We conclude, in Part V, that the use of IPRs to control the breeding, production, and distribution of recreational cannabis could lead to two plausible scenarios. A craft-based industry would have little use for patents or plant breeders’ rights, instead using trademarks to provide quality assurance in a market with simple and direct supply chains. A commodity-based industry would rely more heavily on patents and plant breeders’ rights to protect significant investments in cannabis breeding, and likely see separation between the roles of breeders and growers. We anticipate seeing elements of both markets in the near future. In the longer term, which type of cannabis industry materializes will depend, in part, on answers to the key legal questions we raise in this article.
The chief policy lesson from this paper is that moving to a model where data is open as default requires change in legal, social and technological norms, which all influence ownership of agriculture and nutrition data. Copyrights are not the only, nor even most important, legal rights establishing ownership of data. Relevant legal rights that facilitate access to and use of data at the international, national and subnational level include copyrights, database rights, technical protection measures, trade secrets, and patents and plant breeders’ rights, privacy and even tangible property rights. The open data community must broaden its engagement in all these areas to address emerging challenges."
• How are criteria of protectability formulated and construed?
• What types of works and other productions are protected?
• What special cases to consider: titles, designs, software, etc.?
• How are performances, recordings, databases, etc., covered?
• How long do rights last? What durations for foreign works?
• Who first owns rights? What rules govern diverse transfers?
• What procedures govern registration, royalty rates, etc.?
• What conditions must be satisfied to protect foreign claims?
• What moral and economic rights apply? How are they infringed?
• Who may be liable: infringers, dealers, facilitators, hosts, etc.?
• What exceptions, legal licenses, etc., may serve as defenses?
• How to obtain civil, criminal, and administrative remedies?