The FAOSTAT framework organises data into the following main data domains: Production, Trade,  SUA/FBS, Food Security, Prices, Investment, Inputs, Population, Emissions, Agri-environmental indicators, Forestry, ASTI R&D Indicators, Emergency Response. 
FAO's statistical database can provide data that maybe of relevance to family farming such as data on population including urban/rural, labour force, economically active population in the population module; agricultural land, area equipped for irrigation, fertilizers and pesticides in the inputs module.

The CountrySTAT member countries and regional partners are:  
Africa: Angola, Bénin, Burkina Faso, Burundi, Congo, Côte d'Ivoire, Cameroon, Ethiopia, Ghana, Gambia, Guiné-Bissau, Kenya, Malawi, Mali, Mozambique, Niger, Nigeria, Rwanda, Sénégal, Sierra Leone, Togo, Uganda, United Republic of Tanzania, Zambia. 
Asia: Afghanistan, Bhutan, Philippines. 
Americas: Haiti, Suriname
Region Partners present in CountrySTAT are: Union Economique et Monétaire Ouest Africaine (UEMOA) and East African Community (EAC).

The CountrySTAT framework organizes data into the following main areas:


a)The "National Core" area presents data per year at national level, corresponding to the concepts, definitions and other standard metadata by FAO.  These data relate to production of commodities, their trade and prices, use of land, farm machinery, fertilizers and pesticides, fisheries, food availability for consumption, population, labor force and forest production.


b)  The "Sub-National" area includes the same categories as the Core with disaggregated data at sub-national level. Data refers to Geographical Area (Administrative levels), Local Products and time (Year and/or Month).


c)  The "Thematic Modules" area include complex modules and relevant indicators for the national statistics (for example: Government Expenditure, SUA= Supply Utilization Accounts, Food Security, etc.). 


d)  The “National Institutions” area includes data coming from single national institutions as required by the country. 


e)  The “International Partners” area includes data coming from other international organizations, associations, etc. relevant to the country. 


f)  The “Food Balance Sheet” area includes data on food balance sheets. 


g)  The “Agricultural Censuses and Surveys” area includes data coming from censuses and surveys.


h)  The “Statistical Yearbooks” area includes data coming from the statistical yearbooks.


CountrySTAT has been since the beginning of its project a dissemination tool for facilitating access to official statistical data. The overall objective was to provide information support to scientists and national and regional policy makers. With the new version and approach, CountrySTAT will soon expand its scope and will help creating a common technical language across data owners, statisticians, analysts, academics, journalists and other users. Improved access to data will be strengthened, but, in addition, CountrySTAT will also explicitly provide key features and tools to interpret and understand the data, its reliability and exact meaning, using metadata.


The availability of such a system will be an asset for carrying out joint research and projects, producing better data, delivering evidence-based analyses and/or availing large quantity and variety of multi-sourced indicators. The network of CountrySTAT nodes (different installations of CountrySTAT) will acts as a cohesive element linking stakeholders with different backgrounds and allowing each one of them to play a role in the definition, evolution and use of the network resources (e.g. system platforms, statistical methodologies, data, etc.).


The new CountrySTAT will have a number of features through which several kinds of analysis can be performed, like the vulnerability analysis, the monitoring of prices volatility and the animal disease control. These analyses and monitoring systems will be scalable in order to monitor regional, national and local situations. In this context, Family Farmers can take advantage of the platform by accessing price information for discovering market opportunities, reporting on animal/plan diseases for ensuring an early response from the government, or raising awareness of actual or potential environmental or man-made risks and vulnerabilities.

The available products include global time series over 50 year time spans. Particularly relevant collections in the context of family farming are: employment data, fisheries commodities and trade data, fish and fishery products consumption data and national aquaculture sector and fishery sector overviews.

Data from each statistical collection are available through various formats, tools and information products, including among others:

• Yearbooks providing a full range of tables with detailed statistics.
• Online Query Panels to enable advanced users to extract customized information and reports.
• FishStatJ - Software for fishery statistical time series offering experts and scientists a stand-alone application for complex and sophisticated data exploration and extraction.
• At-a-glance overview:
• OVERVIEW: MAJOR TRENDS AND ISSUES
• Summary tables of fishery statistics: Capture, aquaculture, commodity and food balance sheets
  
  

The WCA 2000 round covered the period 1996-2005. Since the 1950 round of censuses, Statistics Division of FAO has published International Comparison Studies at the end of each round except for the 1980 round.  For the 2000 round a report covering selected items, considered important, was prepared. The 36 international comparison tables were prepared with data extracted from national reports on agricultural censuses.

The international tables of the WCA 2000 round summarises and compares information from 114 countries and territories whose reports have been made available to FAO till the time of finalization of tables. The 114 countries includes 25 countries in Africa, 29 countries each in Asia and Europe, 14 countries in North and Central America, 8 countries in South America, and 9 countries in Oceania region.  The international comparison tables provides selected data at national level on number and area of holdings, gender of the holder, farm population, employment, land tenure, land use, main crops, livestock, irrigation and machinery and equipment.  Several data maybe of relevance to family farming, including: number and area of holdings clasified by land size, gender of agricultural holders, legal status of the holder, demography of farms by sex. There are also other elements such as area under different land use type, holdings reporting irrigation and area irrigated, and number of animals. 

The WCA 2010 round covers the period 2006-2015. The website of the 2010 World Census of Agriculture facilitates the international exchange and sharing of knowledge and information on agricultural census taking, as well as provision of guidance to countries, and monitoring progress on the implementation of the Programme. A major component of the website is the census knowledge database that is a repository containing census methodology, reports and instruments of agricultural censuses conducted during the WCA 2010 round.
Family farming can take advantages of the platform by accessing census data directly from the national census reports that may be of their interest.

The Smallholder Farmers’Data Portrait has a number of attributes. First, it is Being developed to be as ‘global’ as possible. Second, it provides a clear picture of smallholder agriculture, bringing out its strengths and weaknesses: scale, productivity, technology, commercialization and well - being. Third, it Is designed in such a way as to reveal differences between countries and regions in terms of structural transformation; and fourth, it includes policies and programmes to any extent possible.

Click here to read an introduction to a dataset on small-scale agriculture.

The GLRD contains three main sections:
• 83 regularly-updated country profiles: they provide key facts about gender and land rights in constitutions, family law, succession law, land law, customary and religious law as well as policies and programmes.
• Gender and land-related statistics: they provide the most recent land-related statistics disaggregated by gender, including distribution of agricultural holders by sex and the incidence of landowners by sex, among others.
• Legislation Assessment Tool: this practical tool helps visualise the legal intricacies surrounding men and women’s access to land in selected countries and helps identify areas where legal reform is needed. Assessment results can be used to inform policy and law-making processes.
 
Gender equality is particularly important in the context of family farming where agricultural production is managed and operated by a family and is predominantly reliant on family labour, including both the work of women and men.
Gender-equitable land tenure is relevant to the sustainability of family farming. The GLRD is a useful policy support tool that can provide information on a number of key aspects for the successful development of family farming at the national level, including on the legal and policy environment, access to land and natural resources.

RIGA-H includes a comprehensive measure of household income presenting aggregated and disaggregated data on income from different sources such as crop and livestock production, household enterprises, wage employment, transfers, and non-labour earnings.

The RIGA-L database includes only one component of income, wage employment, which can be analyzed at both individual and job levels.

The "Income Aggregate Documentation" (for RIGA-H) and the “RIGA-L Methodology” (for RIGA-L) documents that accompany the surveys describe the approach in constructing the income and employment variables, giving information on the content of the main variables available through the RIGA-H and RIGA-L datasets. The documentation can be downloaded for each survey by clicking on the links in the documentation page. The original data comes from the institutions listed in this table and is not distributed by the RIGA project.

The Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) is a household survey project established with a grant from the Bill and Melinda Gates Foundation and implemented by the LSMS team. Recognizing that existing agricultural data in Sub-Saharan Africa suffers from inconsistent investment, institutional and sectorial isolation, and methodological weakness, the LSMS-ISA project collaborates with the national statistics offices of its eight partner countries in the region to design and implement systems of multi-topic, nationally representative panel household surveys with a strong focus on agriculture. The primary objective of the project is to foster innovation and efficiency in statistical research on the links between agriculture and poverty reduction in the region.
In each partner country, the LSMS-ISA supports multiple rounds of a nationally representative panel survey designed to improve the understanding of the links between agriculture, socioeconomic status, and non-farm income activities. The frequency of data collection is determined on a country-by-country basis, depending on data demand and the availability of complementary funding.

Working closely with the Bank’s regions and sectors, the group is guided by professional standards in the collection, compilation and dissemination of data to ensure that all data users can have confidence in the quality and integrity of the data produced.
Much of the data comes from the statistical systems of member countries, and the quality of global data depends on how well these national systems perform. The World Bank works to help developing countries improve the capacity, efficiency and effectiveness of national statistical systems. Without better and more comprehensive national data, it is impossible to develop effective policies, monitor the implementation of poverty reduction strategies, or monitor progress towards global goals.

The database is searchable by topic and by country. Specifically, it includes a section on ‘listening to the voices of rural people’, including many examples and stories from IFAD across developing regions of efforts to empower communities to innovate for rural development, generating considerable knowledge, experience and good practices, notably through their organisations and associations. There is a section on the use of community driven development approaches to fighting rural poverty, which has at its core an effort to enabling community organizations to play a broader role in the design and implementation of policies and programmes aimed at improving the livelihood of community members. There is also a section of the site devoted to rural institutions and rural poverty.”