The Data Lab collects data at the national (eventually filling any potential gaps of the National Statistical Systems) and sub-national (usually not collected by the FAO) levels to meet the need for more granular and more timely data in contexts where very little information is available, such as least developed countries, countries that lack territorial access to the sea, small island developing states, countries currently facing a food crisis, and highly populated countries.
The strategy for filling the data gaps consists mainly in the use of non-traditional sources, such as datasets, data catalogues on the web, and textual resources containing data. The methodology used is characterised by a blend of big data solutions (such as web scraping, crowdsourcing, etc.) and text-mining techniques (extracting data from documents).
The final objective of such activities is having more timely and detailed data that can support decision-making (and thus improving livelihood and food security levels for rural people in developing countries), monitoring progress under various SDGs, and monitoring food value chains. This can be done by collecting and analysing data, disseminating useful information and improving coordination with resource partners.
So far, this area of work has covered: