Data Management in Agriculture



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The course raises awareness of the importance of data for farmers and the services that use data to improve agriculture. The course discusses the importance of data for farmers, such as data on crop yields, soil conditions, and weather patterns. The course also discusses how data can be used to improve the productivity of farms and the livelihoods of farmers.

The services that use data include e-extension which uses digital technologies to provide farmers with agricultural advice and training; precision agriculture that uses data to optimize the use of inputs, such as water and fertilizer; digital financial services that utilize data to provide farmers with access to credit and other financial services.

The course also discusses the shared data principles, such as FAIR and open data. FAIR stands for Findable, Accessible, Interoperable, and Reusable. Open data is data that is freely available to everyone to use and share. The course discusses how these principles can be used to make data more useful for farmers and other stakeholders in the agriculture sector.

Another key area that the course discusses is the legal and ethical considerations for data rights and protections. This includes issues such as data ownership, data privacy, and data security. The course discusses how these considerations can be balanced to ensure that data is used in a responsible and ethical way.

By the end of the course, participants will be able to:

  • Understand the value of data in agriculture, the different types and sources of data, and how data can be used to provide services to farmers.
  • Understand how data is used and generated in the agriculture value chain.
  • Understand the challenges and risks that smallholder farmers face when sharing data.
  • Understand the strategies for profiling farmers and collecting data about them.
  • Understand where to find open data and how to use it.
  • Apply data analysis and visualization techniques to understand and communicate data.
  • Understand the legal and policy aspects of data sharing in agriculture.
  • Understand the basics of licensing, copyright, and database rights.


This online course is designed for professionals who use or manage data services to help farmers and farmer organizations. These include professionals who work in international organizations, donor agencies, multilaterals, NGOs, academic and research institutions, universities, and national or local governments.

The main target audience for this course are:

  • Administrators and staff of farmers’ organizations  who collect and manage data about farmers and responsible for ensuring that the data is accurate and up-to-date.
  • Development practitioners and technology providers who provide technical expertise and support, as well as help farmers’ organizations to set up farmer profiling and create data services.


The course is conducted in English and comprises four modules, each containing a total of 15 lessons, as well as supplementary audiovisual learning materials.

Module 1: Data, Services and Data Applications

Delves into the following topics: the significance of data in agriculture for supporting farmers, enhancing their income, and advancing food production; the concept of digital farmer profiling and strategies for designing a business model for such profiling.

    • Lesson 1.1. Data for agriculture
    • Lesson 1.2. Farmer profiling
Module 2: Data Sharing Principles

Will primarily focus on the following themes: the principles and advantages of open data usage; the potential benefits of utilizing and publishing data in agriculture; responsible data sharing practices within the realm of farm data; the ethical and legal considerations surrounding data-driven services; and the safeguarding of data.

    • Lesson 2.1. Shared and open data
    • Lesson 2.2. Challenges for smallholders in data value chains
    • Lesson 2.3. Responsible data sharing in agricultural value chains
    • Lesson 2.4. Personal data protection
Module 3: Using Data

Is designed to guide participants on how to locate open data and understand the essential elements of data quality. It also covers the processes of data analysis and visualization.

    • Lesson 3.1. Discovering shared and open data
    • Lesson 3.2. Quality and provenance
    • Lesson 3.3. Data retrieval, analysis and visualization
    • Lesson 3.4. Open data in policy cycles
Module 4: Exposing Data

Will encompass discussions on conceptual frameworks for sharing data and the methods for ensuring data is findable, accessible, interoperable, and reusable.

    • Lesson 4.1. Managing data for reuse
    • Lesson 4.2. Guiding frameworks for data sharing
    • Lesson 4.3. Introduction to data interoperability
    • Lesson 4.4. Interoperability of farm data
    • Lesson 4.5. Open licensing for data


During the course delivery, participants are required to complete brief quizzes at the end of each unit. Once the course concludes, there will be a comprehensive course exam. An Online Certificate of Completion will be issued to participants who actively engaged in the course and achieve a success rate of 8.0 or higher. This certificate acknowledges their outstanding performance in the course. It’s important to note that the certificate will be provided exclusively in electronic format, as downloadable .pdf file, allowing participants to easily access and retain their certificate.