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Agriculture
Training Course on Data Governance and Ethics in Digital Agriculture
Introduction
As digital technologies revolutionize agriculture, the ethical governance and responsible handling of data have emerged as critical priorities. Training Course on Data Governance and Ethics in Digital Agriculture equips participants with the knowledge and tools to address complex issues surrounding data privacy, ownership, interoperability, and trust in agri-data ecosystems. By focusing on emerging trends like big data, AI, blockchain, and smart farming, this course empowers stakeholders to create sustainable and equitable digital agriculture systems.
Designed for agriculture professionals, policymakers, data scientists, and development practitioners, this intensive training bridges the gap between technology and ethics. It emphasizes the importance of fair data policies, regulatory compliance, stakeholder rights, and transparent data sharing in agriculture. The course promotes a human-centric approach to digital innovation, ensuring that technology serves both productivity and ethical stewardship in agricultural transformation.
Programme Curriculum
Training Course on Data Governance and Ethics in Digital Agriculture
Introduction
As digital technologies revolutionize agriculture, the ethical governance and responsible handling of data have emerged as critical priorities. Training Course on Data Governance and Ethics in Digital Agriculture equips participants with the knowledge and tools to address complex issues surrounding data privacy, ownership, interoperability, and trust in agri-data ecosystems. By focusing on emerging trends like big data, AI, blockchain, and smart farming, this course empowers stakeholders to create sustainable and equitable digital agriculture systems.
Designed for agriculture professionals, policymakers, data scientists, and development practitioners, this intensive training bridges the gap between technology and ethics. It emphasizes the importance of fair data policies, regulatory compliance, stakeholder rights, and transparent data sharing in agriculture. The course promotes a human-centric approach to digital innovation, ensuring that technology serves both productivity and ethical stewardship in agricultural transformation.
Course Objectives
Understand the fundamentals of data governance in digital agriculture.
Explore ethical issues in the collection, sharing, and use of agricultural data.
Evaluate global data protection laws (e.g., GDPR) and their relevance to agriculture.
Design ethical and inclusive data sharing frameworks.
Analyze the role of big data and AI in agricultural decision-making.
Develop policy recommendations for ethical data governance.
Address gender and inclusion in agri-data systems.
Examine the implications of blockchain and digital IDs in agriculture.
Learn how to implement data traceability and transparency systems.
Integrate FAIR (Findable, Accessible, Interoperable, Reusable) data principles.
Promote data sovereignty and local ownership of agricultural data.
Identify risks and mitigation strategies in digital agricultural innovations.
Foster cross-sectoral partnerships to support ethical data ecosystems.
Target Audiences
Agriculture Extension Officers
ICT/AgTech Professionals in Agriculture
Policymakers and Regulatory Authorities
Researchers and Academics in Agri-Tech
Development Agencies and NGOs
Digital Platform Developers and Engineers
Data Scientists working in Agriculture
Private Sector Agribusiness Professionals
Course Duration: 5 days
Course Modules
Module 1: Introduction to Data Governance in Agriculture
Understanding data ecosystems in digital farming
Core principles of agricultural data governance
Key stakeholders and their roles
Legal and institutional frameworks
Risks and opportunities in digital transformation
Case Study: India’s AgriStack Digital Ecosystem
Module 2: Data Ethics and Responsible Innovation
Foundations of digital ethics
Bias, discrimination, and exclusion in datasets
Consent and informed participation
Ethical AI applications in agriculture
Building inclusive data cultures
Case Study: Ethical Dilemmas in Kenyan Farm Data Collection
Module 3: Global Legal Frameworks and Policy Compliance
Overview of data protection laws (e.g., GDPR, AUDA-NEPAD guidelines)
National vs international data governance
Policy harmonization for cross-border data flow
Institutional responsibilities and accountability
Legal case examples from Africa, Europe, and Asia
Case Study: EU-GDPR Adoption in East African Agritech Projects
Module 4: Data Ownership, Sovereignty, and Farmers’ Rights
Defining data ownership in agriculture
Farmers’ digital rights and control
Indigenous data governance models
Addressing power imbalances
Consent frameworks for smallholder data
Case Study: Latin American Movement for Data Sovereignty
Module 5: Interoperability and FAIR Data Principles
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to FINESKILL TRAINING CENTER account, as indicated in the invoice so as to enable us prepare better for you.