Global Forum on Food Security and Nutrition (FSN Forum)

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Contribute to shaping the design of the Agrifood System Technologies & Innovations Outlook (ATIO) Knowledge Base

Discussing a prototype and a Draft Concept Note of ATIO Knowledge Base

The Office of Innovation at the Food and Agriculture Organization of the United Nations (FAO) is organizing this consultation to understand use cases and users’ preferences to guide the current design of the Agrifood systems Technologies and Innovations Outlook (ATIO) Knowledge Base (KB).

The ATIO KB is conceived as a qualitative-information catalog of agrifood-systems technologies and innovations developed by actors across the full spectrum of stakeholders, including grassroots innovations. Its coverage is going to be global and span the whole innovation life cycle and all relevant use cases in the agrifood system. It will be neutral, partnership-driven, participatory, and open access. The content will be both federated from trustworthy relevant sources (and when necessary curated), and crowdsourced, with intensive but controlled use of Artificial Intelligence (AI) to enrich and categorize the records. Its objective is to assist policy makers and other agrifood systems stakeholders in making informed decisions to support the prioritization and upscaling of technologies and innovations to accelerate agrifood systems transformation.

At this early stage, when we are developing a design document and have an early prototype, it is the right time to consult potential users. We follow a participatory approach: we want our design to be co-developed, shared and widely endorsed.

DRAFT CONCEPT NOTE AND QUESTIONS TO GUIDE THIS E-CONSULTATION

This consultation seeks suggestions and input from diverse actors: policy makers, investors, farmers’ representatives, agripreneurs, researchers, extension agents.

You can read the Draft Concept Note and consider the prototype1, and the Questions below will guide you provide your recommendations and share your experiences. You can choose which question you want to answer. 

Please also note that FAO’s Office of Innovation has held a similar discussion on the Digital Agri Hub platform in December 2024. The first question is a continuation of the conversation, but the other questions are new. You can read a summary on the outputs here.

The relevant inputs received in this consultation will become part of the ATIO KB design document, and some of the recommendations will have been implemented ideally by July 2025 and others planned for later. In addition, we will be glad to invite participants who are particularly interested and involved to take part in an expert consultation that should take place in February 2025.

The first version of the platform will be published in July 2025. Proceedings of the contributions received will be made publicly available on this consultation webpage.

1. Given the description of the ATIO KB, how do you think it can help you and users like you? Describe one or more specific use cases that you wish the KB would address, like “I imagine I would be able to find innovative products that support farmers with access to credit and insurance specifically for one country, and I would be able to see information on their readiness and how they fare against adoptability criteria” or “I would like to use statistics to show a correlation between level of inclusivity / co-design of the solutions and their levels of adoption”.
2. What do you make of concepts like policy innovation and social innovation? Can you think of examples? Is it useful for you to be able to find such content? In which form do you expect to find them? How would you use them?
3. How important is it to feature grassroots innovations? Looking at some records of grassroots innovations in the prototype, what would you like to see in the descriptions that you don’t see? Which dimension should we capture? What is most useful for grassroots use/application of innovations?
4. How do you think branded commercial products should be featured on the ATIO KB? Data sources of technology-related information often feature individual models of technologies (for instance, different models of solar-powered irrigation pumps). Should the ATIO KB feature models? What is the “innovation” unit you expect to find?
5. Here are two of the main taxonomies used in the prototype: types of innovations and use cases.  Considering that there is no agreed standard for these categorizations, and that we are aligning them to those used in similar projects, are these “good enough” to start? Which major problems do you see? Please suggest changes or volunteer to help us improve them in the next months. Other taxonomies are here.
6. We are developing a chatbot-like search capability. Do you prefer the classic filter-based search or the chatbot search? Or the possibility of choosing either? Tell us how we can improve the search experience.
7. We use Artificial Intelligence (AI) to enrich and automatically categorize the records: you will see an AI stamp at the end of descriptions that have been generated by AI: how good is the text generated? Is AI enriching the records in a meaningful way?

This consultation is open until 10 February 2025.

Alternatively, you can also share your views on the design of the ATIO KB by taking part in a short survey here: https://forms.office.com/e/9S1wF98yMT.

We thank in advance all the contributors for reading, commenting and providing feedback on this draft concept note and guiding questions, and look forward to a productive consultation. 

Co-facilitator: 

Valeria Pesce, Agricultural Science and Innovation Data Specialist, Office of Innovation (OIN), FAO

Athira Aji, Innovation analyst, OIN, FAO

Martina Miracapillo, Support to agrifood systems technologies and Innovations Outlook, OIN, FAO

 

REFERENCES

FAO. 2022. Introducing the Agrifood Systems Technologies and Innovations Outlook. Rome. https://doi.org/10.4060/cc2506en 

Please note that the prototype is not to be considered a FAO official product; it demonstrates the basic functionalities and contains only sample records.

How to take part in the e-consultation

To take part in this consultation, please register to the FSN Forum, if you are not yet a member, or “sign in” to your account. Please read the draft Concept Note of ATIO KB and respond to the relevant guiding questions in the box “Post your contribution” on this webpage. For any technical support, please send an email to [email protected].

 

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Given the description of the ATIO KB, how do you think it can help you and users like you? 

I would like your ATIO KB to provide information on what fruit tree nursery stock is available for each variety of tropical fruit tree. I would like to start a "Replant the Jungle" initiative in African countries.  The "Replant the Jungle" initiative facilitates the planting of a wide variety of tropical fruit trees nursery stock by small farmers in tropical areas. I expect small farmers will want to plant 10 varieties of fruit trees in a small part of their land following the concepts described in the two books listed below.

Will your ATIO KB provide information on where NGOs as well as individuals can obtain nursery stock for the top 20 most common trees grown in Cameroon, for example.  See https://www.picturethisai.com/region/tree/Cameroon.html

See Richard R "Hardwood Small Farm Development: Understanding And Improving Farming Systems In The Humid Tropics" and "Booker T. Whatley's Handbook on How to Make $100,000 Farming 25 Acres": 

 

Introduction

This submission provides input and recommendations regarding the draft concept note and prototype of the Agrifood System Technologies and Innovations Outlook (ATIO) Knowledge Base (KB). The feedback reflects the perspectives of potential users, including policymakers, researchers, agripreneurs, extension agents, and grassroots organizations, as identified in the consultation.

1. Use Cases for the ATIO KB

The ATIO KB has the potential to fill knowledge gaps by providing a centralized, structured, and open-access repository of agrifood systems technologies and innovations. Below are specific use cases illustrating its value:

  • For Policymakers: Policymakers could leverage the KB to identify and compare technologies based on readiness, contextual appropriateness, scalability, and impact. For example, a policymaker may search for sustainable irrigation systems suitable for low-income regions. The KB could provide details on adoption rates, readiness levels, environmental impacts, and cost-effectiveness.
  • For Extension Agents: Extension agents could use the KB to identify grassroots innovations tailored to small-scale farmers’ needs. For instance, they might search for low-cost, farmer-led solutions for pest control, complete with implementation guides and field-tested results.
  • For Agripreneurs and Investors: Entrepreneurs and investors could use the KB to discover scalable innovations in food processing technologies, complete with data on market readiness and adoption trends.
  • For Researchers: Researchers could analyze correlations between inclusivity or co-design of solutions and their adoption levels, using KB-provided metadata on user demographics, participatory development processes, and implementation success stories.

2. Policy Innovation and Social Innovation

Including policy and social innovations will enhance the KB’s relevance. Examples include:

  • Policy Innovation: A case study from Kenya where policies incentivized smallholder adoption of solar-powered irrigation systems. The KB could provide policy details, adoption metrics, and lessons learned.
  • Social Innovation: Documentation of farmer cooperatives creating shared water harvesting systems. The KB could include the social structure, funding mechanisms, and resulting productivity improvements.

Such content should be presented in case-study format with key takeaways, implementation guidance, and links to further resources. These examples could serve as templates for replication or adaptation in other regions.

3. Importance of Grassroots Innovations

Grassroots innovations are critical to ensuring inclusivity and addressing localized challenges. To enhance their representation, the KB should:

  • Include detailed descriptions of the origin, context, and impact of grassroots innovations. For example, “A farmer-developed drip irrigation system in Rajasthan, India, which reduced water use by 40%.”
  • Document key dimensions such as cost, required resources, scalability potential, and cultural acceptability.
  • Provide multimedia content (e.g., videos, diagrams) to facilitate understanding and adoption.

4. Featuring Branded Commercial Products

Branded products should be featured in a way that maintains neutrality and supports comparison. Suggested approaches:

  • Categorization by Innovation Type: Group branded products under broader innovation categories (e.g., solar-powered irrigation systems).
  • Comparative Tables: Provide side-by-side comparisons of product specifications, costs, and performance metrics.
  • Innovation Unit: Balance granularity by featuring both individual product models and broader innovation units (e.g., categories of technology).

5. Taxonomies

The proposed taxonomies for innovation types and use cases are sufficient to start but should be modular and subject to iterative refinement. Specific recommendations:

  • Involve stakeholders in reviewing and updating taxonomies regularly.
  • Ensure taxonomies cover non-technical dimensions such as gender, inclusivity, and environmental sustainability.
  • Align with existing systems like AGROVOC for interoperability.

6. Search Capability

Both filter-based and chatbot-style searches should be available to cater to diverse user preferences:

  • Chatbot Search: Useful for handling complex queries, e.g., “Find grassroots innovations in Sub-Saharan Africa addressing post-harvest losses for maize.”
  • Filter-Based Search: Ideal for refining broader searches, with filters such as region, innovation stage, and use case.
  • Hybrid Option: Allow users to toggle between both options based on their needs.

7. AI Contributions

AI-generated descriptions add value but should be transparently marked and editable. Recommendations:

  • Clearly label AI-enriched records with an “AI stamp.”
  • Enable users to suggest edits, ensuring accuracy and contextual relevance.
  • Regularly audit AI-generated content to maintain quality.

Dr. Malak Elbasyouny

National Food Safety Authority of Egypt/Dr_Fruita Academy/Environmental Institute of Research and Studies
Egypt

1. Use Cases for the ATIO KB

ATIO KB has the potential to address a range of critical needs in agrifood systems. Key use cases include:

  • Policy support and decision-making:
    Policymakers could use the KB to identify technologies and innovations tailored to specific geographic, economic, or cultural contexts. Example: Finding solutions that address climate-resilient farming in arid regions.
  • Facilitating Technology Adoption:
    Providing comprehensive comparisons of innovations, including readiness levels, scalability, and barriers to adoption, for instance, comparing solar irrigation technologies based on cost-efficiency, energy requirements, and maintenance.
  • Monitoring and Evaluation:
    Using statistics and evidence to correlate innovation adoption rates with parameters such as co-design, inclusivity, or capacity-building efforts.
  • Knowledge sharing for researchers and entrepreneurs:
    The KB could serve as a one-stop platform for learning about new market trends, grassroots innovations, and best practices for agripreneurs seeking to scale sustainable solutions.

  • 2. Policy and Social Innovation

  • Importance and Examples:

  • Policy Innovation: The KB could feature case studies or summaries of innovative policies, such as subsidy reforms for sustainable farming or public-private partnerships that fund agri-tech adoption.
  • Social Innovation: Highlighting cooperative models, digital farmer collectives, or gender-sensitive agricultural programs that have improved outcomes.

  • 3. Grassroots Innovations

  • Importance:

  • Grassroots innovations are critical as they often address localized challenges with practical, low-cost solutions. Their inclusion ensures inclusivity and encourages bottom-up innovation.

  • Additional Dimensions:

  • Cultural and Social Context: Include details on how the innovation aligns with local traditions or practices.
  • Scalability and Replicability: Highlight pathways for scaling the innovation or adapting it to other regions.
  • Community Impact: metrics on adoption, productivity improvement, or environmental benefits.

  • Challenges Faced: Real-world barriers that grassroots innovators encountered, such as funding gaps or policy obstacles.

    4. AI-Generated Content

  • AI-generated content must add meaningful value without compromising accuracy.
  • The AI-generated summaries should be reviewed for technical depth and regional contextualization.

  • Suggestions for Improvement:

  • Allow users to flag inaccuracies or submit corrections for AI-generated text.
  • Include a confidence score or brief explanation of how AI categorized or enriched the record.