SE122 Information & Predictive Analytics 4 Innovation in Food Security and Agriculture: Partnering to enhance access to research and open data for Development and to harness the power of predictive analytics for food security monitoring

Organizers

  • FAO
  • WFP
  • Nielsen
  • Chinese Academy Of Agricultural Sciences (CAAS)
  • Technical Centre for Agricultural and Rural Cooperation ACP-EU (CTA)

Access to research and publication of data are vital resources for food security and nutrition, driven by farmers, farmer organisations, researchers, extension experts, policy makers, governments, and other private sector and civil-society stakeholders participating in "innovation systems" and along value chains. Lack of institutional, national and international policies and openness of data limit the effectiveness of agricultural and nutritional data from research and innovation. With the objective to increase the accessibility and visibility of research products in its member countries, FAO has been promoting the exchange of scientific and technical information related to all aspects of agriculture since the early 1970s.

Moving from paper to digital and from processing to partnerships, FAO has established a series of programmes to support these efforts with the objective to make information about agriculture and nutrition available, accessible and usable. Many see higher education as a critical frontline in improving the development environment in lower income countries, where tomorrow's leaders in the public and private sectors are trained and new ideas are advanced. In addition, access to agricultural research through online platforms becomes crucial to facilitate innovation transfer and to assure the generation of new ideas, products and services worldwide. It changes the way processes in organizations are done.

Data plays a key role to take fast decisions on where and when to deliver food and other life-saving supplies and services. With this regard access to real-time information on the number of people, suffering from insufficient food intake in accessible and hard to reach areas of the world, is key for WFP and the humanitarian community. Lacking this information would result in the rapid deterioration of emerging crisis situations and the onset of famine. First-hand survey data is currently the main tool that WFP uses to monitor the food security situation worldwide. However, this data may not always be available on a regular basis and about all hard-to-reach areas. To bridge this gap, WFP's is developing predictive analytics solutions that allow to estimate food insecurity in places where no ground-truth data is currently available, as well as to eventually forecast how the situation may change in the future.

The first prototype was built in 2017 by Nielsen data scientists who used WFP data to create a model to predict monthly changes in food security in Yemen and Nigeria. Today WFP is scaling these solutions and a global predictive model is currently being developed with Alibaba Cloud. This side-event aims to provide an overview of the current initiatives supported by FAO and WFP through public and private sector partnerships on promoting access and exchange of knowledge and information - as a critical step to achieving the SDGs - and the fundamental role that having good available data plays for predictive analysis.

Key speakers/presenters

  • Imma Subirats, FAO of the United Nations
  • Anwen Chung, UN World Food Programme
  • Chris Addison, Technical Centre for Agricultural and Rural Cooperation ACP-EU (CTA)
  • Onan Mulumba, Makerere University, Uganda
  • Sarah Cummings, Manager, Nielsen & The Demand Institute
  • Vladimir Tsaganov, Alibaba Cloud

Main themes/issues discussed

This side event provided an overview of the current initiatives supported by FAO and WFP through public and private sector partnerships on:

Information 4 Innovation in Food Security and Agriculture: Partnering to Enhance Digital Access to Research and Open Data for Development. An overview of the current programmes and services provided by FAO to support the exchange of digital information, knowledge and data in food security and nutrition.

Working in partnership to develop the data ecosystem through capacity building to support smallholder agriculture in Africa, the Caribbean and the Pacific. An overview about CTA and FAO collaboration in developing and delivering online training activities for developing skills in data management supporting agriculture with a particular focus on smallholders.

Information support to Food Security and Nutrition in Uganda: The role of FAO. An overview of some key aspects relating to Uganda’s profile, with a focus on the extent to which FAO has supported research and academics in Uganda and particularly at Makerere University.

Predictive analytics as an innovation in food security monitoring. WFP provided an overview of how it is using predictive analytics – a type of advanced analytics that uses a variety of statistical techniques such as predictive modelling and machine learning – to estimate food insecurity in areas where limited data is available. This can help bridge the information gap and better inform humanitarian decisions. 

Summary of key points

Information 4 Innovation in Food Security and Agriculture:

Access, visibility and exchange of digital information, knowledge and data in food security and nutrition is being materialized through four objectives and programmes:

  • knowledge exchange through the provision of services and online platforms that support member states to make their scientific literature and data in agriculture visible and accessible (AGRIS);
  • access to paywalled scientific literature to organizations in low and middle-income member countries (AGORA & Research4Life)
  • uptake, use and dissemination of data interoperability principles through the promotion of standards, vocabularies and good practices for knowledge, information and data exchange (AGROVOC);
  • effective use of data in tackling the food security and nutrition challenges by building the capacity of stakeholders to understand the potential of open data for agriculture and nutrition and to engage with it practically.


Predictive analytics for innovation in food security monitoring:

  • WFP is developing predictive analytics solutions to estimate food insecurity in areas with limited data.
  • In 2017, Nielsen data scientists created a predictive model to estimate monthly changes in the Food Consumption Score (FCS) in Yemen and Nigeria.
  • Today, WFP is scaling these solutions and a global predictive model has been developed with Alibaba Cloud. Designed based on machine learning algorithms, the predictive model analyses historical data  and produces daily estimates on food security. The resulting analysis is displayed on an interactive platform called “Hunger Map LIVE” – WFP’s new global hunger monitoring system that provides near real-time information on food security in over 90 countries.

Key take away messages

Partnering has been a key element to be more effective and efficient to achieve these objectives, partnering with a range of actors to exchange knowledge & expertise

FAO actively engages with various types of partners such as the UnitedNations’ sister agencies, development agencies, international and intergovernmental organizations, private sector, academic and research institutions to foster an innovative environment to maximize the outreach of FAO’s programmes, as well as enhance awareness about the principles of data, information and knowledge sharing
Predictive analytics is a powerful tool that can help shed light on the food security situation in areas with limited data. These data driven insights will enable global decision makers to quickly identify changes in the food security situation and make more informed and timely decisions.

WFP’s new global hunger monitoring system – “Hunger Map LIVE” – will be publicly accessible in early November 2019 on hungermap.wfp.org. The platform pulls together key metrices – such as food security information, weather, population size, conflict, hazards, nutrition information and macro-economic data – to monitor and predict the food security situation in close to real-time in over 90 countries. For more information, follow @WFPVAM or @mobileVAM on Twitter.

CFS 46 Side Event: SE122 Information & Predictive Analytics 4 Innovation in Food Security and Agriculture

 

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