In response to a growing demand for high-quality and internationally-comparable statistics, FAO develops, implements and promotes methods and standards to guide national data producers in generating and using sound statistics. In particular, the Organization is committed to provide national statistical systems with internationally recognized definitions, concepts and classifications as well as methodological guidance for the production of high quality statistics related to food and agriculture.
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Abstract: This e-learning course provides an overview of the System of Environmental Economic Accounting (SEEA) Central Framework, the statistical standard to measure the relationship between the economy and the environment. The System of Environmental-Economic Accounting 2012—Central Framework is a multipurpose conceptual framework for measuring the interactions between the environment and the economy. By providing an internationally agreed standard with agreed concepts, definitions and classifications, the SEEA is an invaluable tool for compiling integrated statistics on the economy and the environment and deriving coherent and comparable indicators to measure progress towards sustainable development.
Lead authoring unit/office: United Nations Statistics Division (UNSD)
Abstract: The methodological work required to develop the 5.a.1 protocol was carried out by the Evidence and Data for Gender Equality (EDGE) project, an initiative jointly executed by the United Nations Statistics Division and the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) in collaboration with National Statistical Offices, the Asian Development Bank, the Food and Agriculture Organization of the United Nations, the Organization for Economic Co-operation and Development (OECD) and the World Bank.
Lead authoring unit/office: FAO
Abstract: The objective of this course is to learn about the Enhanced Transparency Framework (EFT) under the Paris Agreement. It will be useful to those wishing to understand the importance of forest-related data collection, analysis and dissemination in meeting the Enhanced Transparency Framework requirements.
Lead authoring unit/office: Forestry Division (NFO)
Abstract: This course has been developed to support countries in the analysis and reporting for Indicator 2.4.1 of the 2030 Sustainable Development Goals (Proportion of agricultural area under productive and sustainable agriculture), and to facilitate the understanding of the main concepts underpinning the methodology. Audience The course is primarily intended for those who play a role in data collection, analysis and reporting for SDG Indicator 2.4.1, including agronomists, statisticians, enumerators and data analysts, as well as policy makers and people with an interest in the process. You will learn about The concept of sustainable agriculture and the importance of SDG Indicator 2.4.1 The key features of the Indicator, with a focus on its 11 themes that span economic, social and environmental dimensions The use of the farm survey and alternative options for data collection The methodology for analyzing, computing and reporting this SDG Indicator Course structure The course consists of 4 lessons, ranging from approximately 25 to 40 minutes duration each: Lesson 1 – Introduction to SDG Indicator 2.4.1 Lesson 2 – Key features of SDG Indicator 2.4.1 Lesson 3 – Collecting the data Lesson 4 – Analysing and reporting
Lead authoring unit/office: Statistics Division (ESS)
Abstract: These guidelines are intended to assist countries to participate in the assessment of SDG 6.4.2 on water stress by contributing data and information on environmental flows (EF). These data are necessary for calculation of the SDG 6.4.2 (UNSD, 2017) indicator on water stress, for which countries are required to submit information to FAO who is custodian of this SDG indicator. This guideline provides a minimum standard method, principally based on the Global Environmental Flows Information System (GEFIS), which is accessible via http://eflows.iwmi.org, and is the approach that will be used to generate the country EF data that will make up the global 6.4.2 report. Countries that have more comprehensive and accurate EF data will be able to make use of that data when checking the global dataset produced by FAO and also to add additional details to their Voluntary National report on SDG 6.4.2.
Lead authoring unit/office: Land and Water Division (NSL)
Abstract: This course focuses on SDG Indicator 14.4.1 - Fish stocks sustainability: “Proportion of fish stocks within biologically sustainable levels”. It introduces basic fisheries concepts and definitions, illustrates some technical aspects of classical and data-limited stock assessment and provides detailed guidance on process and tools for the analysis and reporting of the Indicator.
Lead authoring unit/office: FAO
Abstract: This course has been developed to support countries in computing and monitoring Indicators 2.3.1 and 2.3.2 of the 2030 Sustainable Development Goals (Labour Productivity and Income of Small-scale Food Producers), and to facilitate the understanding of the main concepts underpinning the methodology.
Lead authoring unit/office: FAO
Abstract: The course provides guidance on the rationale and the main characteristics of Indicator 6.4.1, and on how to compute the two dimensions constituting the indicator: the hydrologic and the economic component. It also highlights possible challenges related to data availability, and the impact that monitoring results may have on national decision-making and identification of development policies.
Lead authoring unit/office: FAO
Abstract: Through the UN-Water Integrated Monitoring Initiative for SDG 6 (IMI-SDG6), the United Nations seeks to support countries in monitoring water- and sanitation-related issues within the framework of the 2030 Agenda for Sustainable Development, and in compiling country data to report on global progress towards SDG 6. This document serves as a step-by-step monitoring methodology for SDG Indicator 6.4.1 "Change in water use efficiency over time". It explains how to monitor the change in water use efficiency over time, including definitions, computational steps, and recommendations on spatial and temporal resolutions. Last updated: July 2019.
Lead authoring unit/office: Land and Water Division (NSL)
Abstract: Through the UN-Water Integrated Monitoring Initiative for SDG 6 (IMI-SDG6), the United Nations seeks to support countries in monitoring water- and sanitation-related issues within the framework of the 2030 Agenda for Sustainable Development, and in compiling country data to report on global progress towards SDG 6. This document serves as a step-by-step monitoring methodology for SDG Indicator 6.4.2 "Level of water stress: freshwater withdrawal as a proportion of available freshwater resources". The guidelines intend to assist countries in the assessment on water stress by contributing data on environmental flows (EF) which are necessary for the calculation of SDG 6.4.2, indicator on water stress. Assessing environmental flows improves water management by ensuring a sustainable water supply that meets the needs of people, agriculture, energy, industry and the environment within the limits of availability. Last updated: February 2019.
Lead authoring unit/office: Land and Water Division (NSL)
