The Food and Agriculture Microdata (FAM) Catalogue by the Food and Agriculture Organization of the United Nations (FAO) is a prominent platform for promoting research and analysis by disseminating microdata sets, thus maximizing their value for evidence-based decision making. This platform plays a pivotal role in enhancing data credibility and transparency by hosting and sharing information.
The Food and Agriculture Microdata (FAM) Catalogue compiles datasets from farm and household surveys on agriculture, forests, food security and nutrition. The FAM Catalogue aims to be a comprehensive resource for data collected directly by FAO or with the support of FAO. With microdata already available in the public domain, the FAM Catalogue disseminates the metadata and relevant documentation of the study in line with relevant international standards and provides the link to redirect users to the webpage or platform hosting the microdata. Continuously updated, it welcomes submissions from organizations with relevant data. The FAM Catalogue serves as a one-stop destination for accessing and disseminating crucial forest related data, enhancing transparency and informed decision-making.
The catalog contains 1 427 surveys with over 500 000 variables, 184 countries (November 2024). This platform already contains data from Bangladesh, Brazil, Guatemala, Lao DPR, Mexico and Uganda.
Informed policymaking largely relies on data and information accessibility to potential users. Transparent and reliable information supports forest monitoring processes in countries. Data and analysis need to be technically sound and credible while their interpretation needs to be respective of associated uncertainties. The FAM Catalogue ensures accessibility, credibility and transparency for decision making.
Access to transparent forest data has yielded tangible benefits, transforming forestry practices and decision-making processes worldwide. The following real-world examples showcase various benefits from maximizing the use of accessible and transparent forest data: