The FAO Data Lab on statistical innovation and the use of big data for the production of international statistics

• Published in: Statistical journal of the IAOS 2022, Vol.38 (3), p.995-1007
• Main Authors: Fabi, Carola, Mongeau Ospina, Christian A., Rosero Moncayo, José, Silva e Silva, Luís G.
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Big Data; Data analysis; Data collection; Data mining; Data science; Data sources; Innovations; Modernization; Spatial data
• ISSN: 1874-7655; 1875-9254
• DOI: 10.3233/SJI-220052

Data is an extremely important intangible good, but official data is not always available. It may be scarce for many reasons, among which: low statistical capacities, poor funding for data and statistics, weak data dissemination and use culture. A solution to fill data gaps needs to consider that there is data made available on the web, usually coming in an unstructured way, that can be combined with innovative methods to generate relevant information. National and international organisations need to engage with new data sources and methods considering the crisis of traditional data collection systems that causes data gaps. In this light, FAO created in 2019 the “Data Lab for statistical innovation” to fill such gaps by modernising the Organization’s statistical business, which means improving the timeliness and granularity of data collection, providing automated analysis, and capturing early warning signals. It does so through the use of cutting-edge technologies (such as web scraping, text mining, geo-spatial data analysis and artificial intelligence) and by introducing nonconventional data sources (social media, online newspaper articles). This article summarises the experience of the FAO Data Lab and how it has been useful for the Organization to fulfil its mandate.