Proposal Description

The global statistical system is undergoing radical transformations due to new scientific developments and innovations brought about by advances in new technologies, particularly the use of satellite imagery, big data, and artificial intelligence. The digitalization of operations is the major challenge facing the agricultural statistics system in order for it to keep pace with the changes imposed by this wave of modernization, particularly in developing countries.

In parallel with these concerns, extensive scientific discussions, sponsored by the Food and Agriculture Organization of the United Nations, have been initiated on the transformation of global food systems on one hand, and on agricultural statistics and food security, notably its new vision of collection and dissemination on the other hand. Furthermore, the opportunity to review midway the indicators of the Sustainable Development Goals by the United Nations Statistics Division during its future ordinary work in 2025 provides an opportunity to reconsider certain indicators that national statistical offices have not been able to provide information on, particularly those related to sustainable agriculture.

It is within this global context that this scientific workshop is situated. It aims to open a discussion among scientists, experts, international statisticians, and representatives of national statistical offices to provide their readings and comments on the results and recommendations of the relevant expert committee, as well as the recommendations of the World Forum on Statistical Data.

This workshop aims to present examples of the implementation of these recommendations, as well as the obstacles that hinder them, especially in developing countries.

A group of academics, experts, and representatives from relevant United Nations agencies (FAO, UNICEF, ESCWA, ECA, UNSD, WHO, etc.), as well as representatives from international organizations (World Bank, African Development Bank, Islamic Development Bank, etc.), are invited to provide insights into their expectations.

Keywords: Big data, agriculture, indicator, technology, artificial intelligence.