Digital Opportunities for Better Agricultural Policies

Foreword
Acknowledgements
Executive Summary
Chapter 1.    Overview of findings and recommendations
	1.1. How can governments best use digital technologies to improve agri-environmental policies?
		1.1.1. Making use of digital technologies in policy design and implementation
		1.1.2. Using digital technologies can improve monitoring and compliance for  agri-environmental and agricultural policies and programmes
	1.2. Governments should champion efforts to improve access to agricultural data
	1.3. Data infrastructures and data governance for agriculture: Potential roles  for government
		1.3.1. Governments can play an active role in future development of digital tools for policy and for agriculture more broadly
	Notes
		Part I. What’s new? Digital technologies and agriculture
Part I. What’s new? Digital technologies and agriculture
	Chapter 2.    Digital innovations and the growing importance of agricultural data
		2.1. Overview of recent and ongoing digital innovations for agriculture and food
			2.1.1. Global and local: Recent advances in remote sensing and edge-of-field monitoring
			2.1.2. Automating and accelerating analysis: The new capacity to harvest, combine and analyse data in agriculture and food
			2.1.3. Advances in encryption, data protection and data sharing technologies, and institutions for data sharing
			2.1.4. The drivers of digitalisation of the agriculture and food sectors
				On-farm drivers for digitalisation of agriculture
				Off-farm drivers for digitalisation of agriculture
			2.1.5. Adoption may be hampered by lack of skills; but what and whose skills?
		Notes
		References
			Part II. Making better policies with digital technologies
Part II. Making better policies with digital technologies
	Chapter 3.    Realising digital opportunities for better agri-environmental policies
		3.1. Digital opportunities for agricultural and agri-environmental policies: A conceptual framework
		3.2. Digital technologies throughout the policy cycle: Insights from agri-environmental policies
			3.2.1. Use of agricultural data and digital technologies for agri-environmental policies: OECD questionnaire
				Online surveys, aerial photography and satellite data key digital sources of data for agri-environmental policies, but traditional methods are still important
				Most organisations have a good awareness of the benefits of digital technologies, but also see new risks
				Most organisations have adopted digital strategies and data policies, and have appointed a Chief Information Officer
			3.2.2. Improving inputs into agri-environmental policy-making
			3.2.3. Connecting administrators with programme participants (farmers) and the general public
			3.2.4. Digital technologies for policy implementation
				Facilitating collective governance mechanisms for landscape approaches to agricultural sustainability
				Facilitating improved spatial targeting of agri-environmental policies
				Digital platforms for effective market-based agri-environmental instruments
			3.2.5. Digital technologies for monitoring and compliance
			3.2.6. Digital technologies for policy evaluation
		3.3. Digital technologies can open new options for agri-environmental instruments
			3.3.1. Technologies to enable new monitoring and compliance approaches
			3.3.2. Result-based agri-environmental policies and modelling versus measuring
			3.3.3. Digital networks, platforms, AI and machine learning for policy communication and extension
		Notes
		References
	Chapter 4.    Issues which may prevent digital opportunities from being realised
		4.1. Practical challenges for the use of digital technologies by policy makers and administrators
			4.1.1. How are organisations responding to these challenges?
		4.2. Institutional and policy settings can limit opportunities for policy from being realised
			4.2.1. Institutional constraints and lock-in
			4.2.2. A lack of trust can be a roadblock to using digital technologies to reform policies
		4.3. Using digital technologies for policies raises new challenges
			4.3.1. Social impacts and acceptance of increased monitoring
			4.3.2. Dynamic challenges of agri-environmental mechanisms which rely on models
				Monitoring and modelling should be viewed as complementary.
			4.3.3. Policy design elements can be a pull factor for technology adoption on-farm, but there is a risk of exclusion
		4.4. New challenges which may require a broader approach
			4.4.1. Potential pitfalls of “RegTech” for agriculture
				Technological progress and regulatory remit
			4.4.2. Access to farm-level agricultural data for policy-making
				Options to improve access to agricultural data held by public organisations to improve policy
		Notes
		References
			Part III. Data infrastructure and governance in agriculture
Part III. Data infrastructure and governance in agriculture
	Chapter 5.    Realising digital opportunities in agriculture requires a data infrastructure
		5.1. Realising digital opportunities in agriculture requires a data infrastructure
		5.2. Access to farm-level agricultural data held by governments
			5.2.1. Concluding recommendations about agricultural data held by governments
		5.3. Are there new roles for the government in the data infrastructure?
			5.3.1. Data quality and trusted algorithms
			5.3.2. From regulatory oversight to acting as an investor and co-ordinator
			5.3.3. Governments might need to rethink the way they are operating, as well as their role as a provider of public services.
			5.3.4. Path dependency, infrastructure and regulatory environment:  governments have to be aware of their starting point
			5.3.5. Governments should ensure there is co-operation and communication between stakeholders
		Notes
		References
			Part IV. Case studies
Part IV. Case studies
	Chapter 6.    Case Study 1. New Zealand Our Land and Water National Science Challenge
		Context: A new approach to sustainable, productive agriculture in New Zealand
		Use of digital technologies in the Innovative and Resilient Land and Water Use Research theme
			The problems
			Digital solutions
				Managing data and interaction between digital tools: a vision for a data ecosystem
		Lessons learned
			Lesson 1. Multi-dimensional integration of digital and other tools is needed to ensure efficiency and effectiveness
			Lesson 2. Monitoring and modelling should be viewed as complementary
			Lesson 3. Ensure new digital tools do not create new information asymmetries
			Lesson 4. Creation of dynamic, updatable digital tools can lessen the need to “reinvent the wheel” and better match users’ needs
			Lesson 5. Embrace different levels of Data Management Maturity to fit different contexts
			Lesson 6. Ensure initiatives generate “additional” benefits by using a mix of old and new technologies
			Lesson 7. Digital tools can be used to foster collaboration and overcome traditional roadblocks created by conflicting views and values
			Lesson 8. Digital tools can enable new information-rich policy paradigms rather than simply improving the granularity of existing information-poor paradigms
		Notes
		References
	Chapter 7.    Case Study 2. Digital technologies for Dutch agricultural collectives
		Context: The policy environment and the Dutch collective approach
		Use of digital technologies to support the effective and efficient operation of the collectives
			The problems
			The solutions: SCAN-ICT—an IT system for the collectives
				How was the system built?
				What does the SCAN-ICT system do?
				Ongoing developments
		Lessons learned
			Lesson 1. The SCAN-ICT system and related digital platforms assist pre-existing collective governance institutions to “go further”
			Lesson 2. The SCAN-ICT system can pave the way for result-oriented agri-environmental policies
			Lesson 3. The SCAN-ICT system facilitates confidence and trust between actors and across different administrative levels
			Lesson 4. The “Building Team” was essential to implementing well-functioning digital tools that met administrative and user requirements
			Lesson 5. The staged approach—first building SCAN-ICT and then the Mijnboerennatuur.nl and Schouwtool platforms—has worked well in the Dutch context
			Lesson 6. A mixture of old and new tools was the most cost-effective approach in the Dutch context
		Notes
		References
	Chapter 8.    Case Study 3. Gully erosion monitoring in Australia’s Great Barrier Reef catchments
		Context: Tackling water quality impacts of sediment transport in Great Barrier Reef catchments
		Use of digital technologies to improve gully erosion mapping
			The problems
			Digital solutions
				Gully mapping and drivers in the grazing lands of the Burdekin catchment (Project RP66G)
				Monitoring Gullying Processes in the Great Barrier Reef Catchments (Photogrammetry project)
		Lessons learned for the application of remote sensing and predictive modelling technologies for erosion mapping in agricultural lands
			Lesson 1. Use of advanced remote sensing techniques to map erosion processes over large spatial scales is technically feasible and yields improved results but is still relatively costly and challenging to undertake. Large knowledge gaps remain, and a...
			Lesson 2. Improved understanding of physical processes must be balanced by economic considerations
			Lesson 3. Benefits and challenges of collaboration across organisations and across projects
		Notes
		References
	Chapter 9.    Case Study 4. Earth Observation initiatives for administration of the European Union Common Agricultural Policy
		Context: Reforming the CAP’s administration
		Use of digital technologies to streamline CAP administration
			The problems
			Digital solutions: The RECAP initiative
				RECAP digital components
					Remote Sensing component
					Spatial component
					Business intelligence component
					Workflow component
					Software Development Kit
					The RECAP Digital Platform—Web and mobile application
				Implementing the RECAP pilot
				Future plans for RECAP and beyond
		Lessons learned
			Lesson 1. Earth-observation tools powering accessible, user-specific platforms offer the opportunity to substantially reduce transactions costs of administering the Common Agricultural Policy
			Lesson 2. By using spatially-explicit earth observation and other data on a wide range of agricultural and environmental variables, RECAP paves the way for more nuanced, targeted agri-environmental policies
			Lesson 3. Digital tools such as the RECAP platform can increase the transparency of inspections and the accountability of public organisations, resulting in greater robustness of, and trust in, public agencies
			Lesson 4. RECAP uses a co-operative approach to ensure the efficiency and effectiveness of its technical solutions, and interoperability with other solutions
			Lesson 5. Innovative digital solutions such as RECAP can underpin new private sector business models
		Notes
		References
	Chapter 10.    Case Study 5. Digital technologies applied by USEPA to achieve innovative compliance
		Context: The policy environment
		Use of digital technologies to support
			The problems
			The solutions
		How does innovative compliance apply to agriculture in the United States?
			Permitted agricultural operators and chemical input suppliers
			Agricultural operators participating in voluntary programmes and initiatives
		Lessons learned for the application of innovative compliance tools in agri-environmental contexts
			Lesson 1. Design principles for EPA’s innovative compliance
			Lesson 2. Good regulatory practices can be transferrable across different kinds of regulations
			Lesson 3. Technological change offers new possibilities for improved monitoring and compliance. However, there needs to be clear and fit-for-purpose processes for demonstrating suitability of advanced monitoring tools for regulatory purposes, which m...
			Lesson 4. Take a holistic approach: use of digital technologies complements non-digital, and regulatory efforts can work alongside voluntary efforts
		Notes
		References
	Chapter 11.    Case Study 6. Digital innovations to facilitate farm level data analysis while preserving data confidentiality
		Context: Farm-level data is crucial for policy analysis, but high confidentiality requirements limit the ability to use it
		Use of digital technologies to overcome the impasse
			The problems
			Digital solutions
				Existing approaches to improving data access and reuse while preserving confidentiality
				Recent technological advances: Confidential Computing, Multi-party Computation and Synthetic Data Release
					Confidential computing and multi-party computation
					Synthetic data release
		Lessons learned for the use of innovative digital technologies to improve access to and reusability of farm level data for policy-relevant analysis
			Lesson 1. Agricultural micro data, and the ability to “tie” farm level financial data to physical data, including location-specific attributes, are crucial for developing more efficient, spatially-targeted policies
			Lesson 2. Even though governments may be moving towards more open data approaches, access to farm level data collected by public agencies is generally limited by enabling legislation and is underpinned by trust
			Lesson 3. By facilitating analysis of the data without the analyst being able to see the data, confidential computing can solve the confidentiality-reuse dilemma
			Lesson 4. Improving access to agricultural micro data needs a coherent, tiered data dissemination strategy
		Notes
		References
	Chapter 12.    Case Study 7. Data transparency, digital technologies and California’s water quality coalitions
		Context: The policy environment
		Refining data transparency requirements and use of digital technologies to deliver better outcomes for agricultural producers and water quality
			The problems
			The solutions
				Recent review of monitoring and reporting regime
		Lessons learned
			Lesson 1. Well-constructed data transparency requirements can provide incentive for farmers to participate in collective mechanisms to improve water quality
			Lesson 2. Digital tools are only one part of a broader approach, and the approach shapes which digital tools are needed
			Lesson 3. Even with the declining cost of sensors, the “representative monitoring” approach is currently considered the most cost-effective
		Notes
		References
	Chapter 13.    Case Study 8: Estonia e-government and the creation of a comprehensive data infrastructure for public services and agriculture policies implementation
		Review of the e-Estonia initiative and its use for agriculture policy implementation
		The creation of a digital infrastructure in Estonia
		Application in the case of agriculture policy and regulations
		Lessons learned from the development of a government data infrastructure and use in agriculture
			Lesson 1. The implementation of Estonia data infrastructure required the government to rethink the way it was operating, as well as its role and what problems the previous government administration organisation was facing
			Lesson 2. The creation of a data infrastructure requires creating a setting and a regulatory environment guaranteeing trust in the new system
			Lesson 3. Providing the right incentives with flexibility to implement change and avoid barriers to adoption, both within the government and between the government and citizens
		Notes
		References
	Chapter 14.    Case Study 9: Connecting the dots to create a data infrastructure: The US National Soil Moisture Network
		Context: Disconnect between different layers of data about soil moisture in the United States prevents their reuse for comprehensive water policies
			Soil moisture matters to inform policy makers
			The history of the development of soil monitoring in the United States
		The use of digital technologies to improve the coordination and use of soil moisture data
			The problem
			Overview of the National Soil Moisture Network (NSMN) initiative
		Rationale and lessons learned from the development of a National Soil Moisture Network
			Lesson 1. There is path dependency from previous policy-making and infrastructure development on the data infrastructure and governance
			Lesson 2. There could be a role for the government to support the development of infrastructure
			Lesson 3. There might be a role for some regulatory oversight or central planners when there is a collective gain to coordination but no returns or private incentives
		Notes
		References
	Chapter 15.    Case Study 10. Data infrastructure and the potential role  of the government supporting the data infrastructure –  example of the Akkerweb in the Netherlands
		Context: Fostering capacities, good use of public data and support private sector services development in precision agriculture
			The problem
			The Akkerweb brings together public and private data to support precision agriculture
		Lessons learned
			Lesson 1. To be adopted and successful, digital technologies have to be designed based on expressed user needs
			Lesson 2. The success of the platform relies on the integration of all public and private sector stakeholders of precision agriculture
		Notes
		References
			Annex A.   Agri-environmental policy components and policy mechanisms
		Note
		References
			Annex B.   OECD Questionnaire on use of digital technologies  by agri-environmental policy administrators
Annex A. Agri-environmental policy components and policy mechanisms
Annex B. OECD Questionnaire on use of digital technologies by agri-environmental policy administrators