Food and Agriculture Organization of the United Nations
    FAO Data Lab

    About the Data Lab for Statistical Innovation

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    Background

    Official statistical systems are facing difficulties posed by reduced budgets, cultural changes and new competitors on the market, which create data gaps as a consequence. Such gaps are widened by emergency contexts, when having access to timely information is very important. The FAO Statistics Division (ESS) is adapting to this crisis of the traditional data collection systems by modernizing the statistical business process through the activities of the Data Lab for Statistical Innovation.

    More in particular, the Data Lab contributes to the Hand-in-Hand (HiH) Initiative, launched in September 2019 to enable “matchmaking” between countries with the highest poverty and hunger rates and the countries that are able to offer support. The HiH Initiative is characterised by data-intensive tasks like identifying bottlenecks and investment gaps, and developing a detailed monitoring and evaluation framework to assess the impact of its action by 2030. At the core of this initiative is the need to conduct complex analysis on cross-domain data, aggregating and enriching the existing information from non-conventional sources. Information needs to go from the global down to the granular level and timeliness becomes crucial.

    In a globalized ecosystem, food value chains can be easily and quickly disrupted by sudden crises, putting food security and food safety at risk. Information needs in times of crisis are intrinsically different from business-as-usual needs: timeliness of data as well as the capacity to quickly and automatically draw insights from data for policy making become essential. An example of such a crisis is the current COVID-19 pandemic, which is the first test bench for the Data Lab. This has generated an increased need for timely, possibly real-time, information from non-conventional sources and its automated analysis.

    Objectives and scope

    The objective of the Data Lab aligns with that of FAO Statistics, which is to support the design and monitoring of evidence-based policy decisions by member countries. The Data Lab will also support the Hand-in-Hand Initiative with the objective of accelerating progress on Sustainable Development Goals in 43 focus countries with the highest poverty and hunger rates.

    More in particular, the Data Lab will support the FAO's statistical system by addressing the specific challenges related to timeliness, granularity, data gaps and automation of analysis for quicker insights. To achieve these objectives, the Data Lab will:

    Data analysis
    • promote the use of non-official, unstructured data and data science methods to fill in data gaps in domains and geographical areas in which there is little official data available;
    • validate official data reported by countries, to identify areas of future collaboration and technical assistance;
    • identify relevant data sources and appropriate analysis techniques to produce evidence and build insights;
    • develop geospatial tools and tagging systems at sub-national level, to increase data granularity, especially in tropical and dryland areas where the most vulnerable populations live;
    • build data systems for the HiH Initiative that will facilitate the identification of target areas and will highlight aspects of their agricultural potential;
    • provide tailored text-mining tools to extract, summarize and categorize information on effective policy interventions that can be applied in similar situations.

    The Data Lab also aims at bridging gaps between different streams of work around data: it must be seen as a connecting point of different initiatives in FAO (where knowledge is shared and expanded) and beyond FAO (building partnerships at all levels).
    The Data Lab will provide a combination of skills depending on the needs and issues being addressed.

    Approach and methods

    See more details about the methods adopted in the "Methods" menu.