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Census tabulation , archiving and disemmination Technical session 18
1. Workshop on
World Programme for the Census of Agriculture 2020
Amman, Jordan
16-19 May 2016
Oleg Cara
Agricultural Census and Survey Team
FAO Statistics Division
Census Tabulation,
Archiving and
Dissemination
Technical Session 18
1
3. A set of statistical tables prepared to present the main census
results, based on the users’ primary needs
It is paramount for developing the census questionnaire and to
ensure that all relevant census information is included
Countries should produce basic standard tables using a wide
range of methods of dissemination and media to ensure the
widest dissemination of the census results
Tabulation programme
3
4. Coherence and comparability:
• with previous censuses (when available)
• other statistical data
• relevant and reliable administrative data sources (land cadaster
information, agricultural machinery, organic farming, etc.)
• International comparability (including the use of recommended
classifications/ tabulation classes)
Tabulation plan with main tables must be developed before
designing the census questionnaires
Tabulation programme (contd.)
4
5. Standard statistical tables
Totals for items collected, such as: total area of holdings according
to land use (or land tenure) types or number of animals for each
livestock type
Total number of units with certain characteristics, such as the number
of holdings with both agricultural land and livestock or only with
land, or just animals
Averages for items, such as the average area of the holding or
number of parcels per holding
Percentages (e.g. of holdings using organic fertilizers or with
animals)
5
6. 1. Administrative unit or agro-
ecological zone
2. Legal status of agricultural
holder (type of holder)
3. Total area of holding
4. Area of agricultural land (as well
as by main land use classes, e.g.
arable land, land under
permanent crops)
5. Number of livestock (for a
particular livestock type)
6. Main purpose of production of
the holding
7. Household size by sex and age
group
8. Sex of agricultural holder
9. Age of agricultural holder.
Classification variables
Classification variables are characteristics used for data tabulation. Nine
main classification variables have been identified for tabulations of the
essential items:
6
7. Tabulation classes
Often, classification variables need to be formed into suitable classes for
presentation in the tables.
FAO recommends to use census essential items for the tabulation classes.
Examples:
Essential item/classification variable Tabulation classes
Legal status of agricultural holder (type of holder) A civil person
Group of civil persons
Juridical person
Age of agricultural holder Holder is a civil person
• Under 25 years
• 25 – 34 years
• 35 – 44 years
• 45 – 54 years
• 55 – 64 years
• 65 years and over
Joint holders
7
8. Tabulation classes (contd.)
Consistency between statistical collections in the country (e.g. using
the same age groups (for ex. 25-34, 35-44, etc.)
International standards: countries should adhere to those wherever
possible to help in making comparisons between countries
To meet national reporting needs, more disaggregated classes are
encouraged (to allow for re-aggregation).
8
9. Tabulation classes (contd.)
Where countries wish to use different class groupings in their
standard reports, they should also report the results according to the
guidelines given in the WCA 2020 for international comparison
purposes.
For more details see WCA 2020, Table 10.1: Agricultural census
essential items: tabulation classes.
9
10. Territorial profile of census results
Different levels, by:
• administrative regions/rayons
• agro-ecological zones
• communities
• other small areas
Dissemination of data items which are relevant, meaningful for a
particular level and ensure data confidentiality
10
11. Territorial profile of census results
(contd.)
The level of administrative units to be presented in the tables could
be a decisive factor in designing:
• census methodologies (choosing between complete or sample
enumeration, defining agricultural holding within the border
of a region)
• census tools e.g. questionnaires with special sections or
annexes completed for each administrative unit where land
and/or livestock is located (e.g. Armenia, Italy, Romania,
etc.).
11
12. Cross-tabulations
Census data classified by two different items simultaneously, e.g.:
• the number of holdings classified by area of holding and
livestock (by each area/livestock number class)
• the number of holdings classified by age of holder and area of
holding (by each age/area class)
• useful for in-depth studies
For more details see WCA 2020, Table 10.2: Agricultural census
essential items: recommended cross-tabulations.
12
13. Tabulations: census scope and
coverage
Agricultural holdings: establishments engaged in agricultural production
activities
Aquaculture activities of agricultural holdings
Capture fisheries activities conducted at household level
Widened census (including both agricultural and non-agricultural
production households)
Community-level data
Tabulations with more details on some sub-populations of holdings (such
as “large or special holdings”).
13
14. Tabulations: community-level data
Community-level data in an agricultural census can be tabulated
in two ways:
• To summarize the characteristics of communities
• To use as classification variables for tabulations against holding-
level data, such as:
number and area of holdings
number of households and population.
14
15. Tabulations: community-level data
(contd.)
Typical community-level classification variables are:
• Access to urban centre
• Risk of natural disasters
• Economic status
• Occurrence of seasonal food shortages
• Presence of a periodic or permanent agricultural produce market
• Access to veterinary services
• Access to farm input trading centre
• Access to credit institutions
• Access to farmers’association
• Presence of specific development projects.
15
16. Administrative unit or agro-ecological zone
Legal status of holder
Area of holding
Area of aquaculture
Household size
Sex of holder
Age of holder
Aquaculture tabulations:
classification variables
16
17. Dissemination - key stage of a
census
Dissemination is one of key stages of the census process where the census data
are made available to users and long- term preservation is ensured
Main purpose of the census - meeting users needs for data through provision of
structural data on agriculture
Ensure access to a wide range of relevant data
International comparability (including the use of classifications/ tabulation
classes)
Explanation of inconsistencies between census results and other data sources
Contribute to users/ stakeholders’ extended use and trust in census results.
17
18. Dissemination - key stage of a
census (contd.)
Institution’s dissemination Policy
Dissemination plan
Large consultations with main stakeholders
Timely results
Supply a variety of products
Technologies/Dissemination Media
Quality Assurance (relevance, accuracy and relibility, coherence
and comparability (including international comparability),
timeliness and punctuality, accessibility and clarity,
confidentiality, etc.)
Census Metadata
18
19. Metadata
Metadata (“data about data”) provide information about one or more
aspects of the data
Should include quality measures
Metadata help users:
• understand what the data are measuring and how they have been created,
• prevent them from misunderstanding the data and helps to promote
appropriate use of the data
• understand the quality of data by providing information about the data
collection process
• better interpret and use the census results.
19
20. Dissemination products
1. Standard census tables and reports with census results for general
distribution:
• Summary report of key results
• Final report on the main results
• Brochure presenting the key results
• Thematic reports
• Detailed data tables (in electronic formats)
2. Maps
3. Graphs and charts
4. Technical report containing metadata and methodological and
operative actions along with census questionnaires and other
census forms
20
21. I. Printed publications
II. CD-ROMs
III. Pen drives
IV. Internet
Access to the public database so that users can generate their
own specific set of tables
Use of web-based mapping and GIS
V. Safe access to census microdata.
Methods of dissemination and media
21
22. Microdata
Microdata are the data recorded on the unit of enumeration, they
allow users to carry out a wider range of analysis than with
aggregate data.
Each set of information about a unit represents a microdata record.
Access to Census microdata:
Allows users to carry out a wider range of analyses than is
possible with aggregate data
Legal framework
Organizational and technical framework
Confidentiality of the information recorded from respondents
must be strictly preserved.
22
23. Methods for access to microdata
1. Public Use Files (PUFs): these files undergo a rigorous statistical
disclosure control (SDC) process so that the chance of re-
identification of respondents is minimal.
2. Licensed Files: licensed files are also anonymised but with the
possibility of fewer SDC procedures being applied. Researchers
are asked by NSO to be explicit about the research that they are
doing and to sign a license on the conditions of microdata’s use.
23
24. Access to microdata (contd.)
3. Remote Access Facilities (RAFs): with a service window
provided by NSOs which allow researchers to supply the
algorithm and tools they will be using. NSO’s staff can run the
job against the actual data set before returning the output to the
user.
4. Data enclaves: a facility within the premises of the NSOs to
which researchers can come in order to perform their research
on detailed files.
24
25. Access to microdata (contd.)
5. Deemed Employee: a researcher may be sworn in to work with
the agency as a temporary staff member. In this case the researcher
would be subject to the same secrecy and ethical provisions and as
the regular staff.
Providing Access to Agricultural Microdata: A Guide’ (Global Strategy, 2014).
25
26. Data archiving
• A means of ensuring long term preservation of data.
• Assists users in understanding and interpreting the data.
• Ensures the continued access to the census data by users over long
periods of time.
• Primarily relates to digital data.
• Digital data can be vulnerable to obsolescence of enabling
technologies, from hardware and software used to store and access
the data to physical damage and to loss due to the passage of time.
26
27. Data archiving (contd.)
Should include:
• raw microdata
• edited microdata,
• macrodata
• the appropriate metadata
• census dissemination products
• census tools such as computational programs, conversion tables,
enumeration manuals, training manuals, supervision manuals,
questionnaires, cartography, etc.
27
28. Data archiving (contd.)
• Safe storage of the data in a sustainable environment:
with appropriate policies and procedures
ensuring that the archived census data can be made available
over time to authorised users.
• More detail in International Household Survey Network. Working Paper 3:
Principles and Good Practices for Preserving Data (IHSN 2009).
28
29. Public events to disseminate the
main census results
Important national events performed in accordance with
Dissemination Strategy and Plan, such as:
National seminars to disseminate the main census results along
with regional dissemination seminars.
Press conferences.
The events organized to present:
Preliminary census results
Final census results.
29
30. Country examples
Results are available from:
• printed reports and brochures,
• CD-ROM’s, the website of CountrySTAT-Niger
(http://countrystat.org/home.aspx?c=NER&tr=55)
• the website of the National Institute of Statistics (http://www.stat-
niger.org/NigerInfo/rgac/indexe.html)
• upon request.
Niger, General Census of Agriculture and Livestock 2004-2008:
30
31. Country examples (contd.)
There are three major releases (online and free of charge):
• Basic counts and totals for all farm and farm operator variables
tabulated at the national, provincial and three sub-provincial areas. All
these data are also available in a dynamic format for self-serve user-
defined tables. These data were also later made available in Statistics
Canada online main database (CANSIM).
• Selected historical farm and farm operator data (some series
covering 1921-2011). Available in CANSIM.
• Selected data on social characteristics of farm operators, census farm
families and the farm population, based on the agriculture-population
linkage database. Data are available in CANSIM.
Canada, 2011 Census of Agriculture:
31
32. Country examples (contd.)
Publications on:
• “The 2011 Census agricultural regions boundary file and
reference guide and reference maps”
• “The Agricultural ecumene boundary file and reference
guide”
• “Canadian Agriculture at a Glance”
• Maps, full-colour photos, graphs and charts give its diverse
array of subjects an eye-catching and informative visual
interpretation to complement the articles.
All publications are available from Statistics Canada’s
website free of charge.
Canada, 2011 Census of Agriculture:
32
Statistical table – a primary form of presentation of statistical data
International comparisons require standard tables (the use of Classification variables and classes) for all countries
International comparisons require standard tables (the use of Classification variables and classes) for all countries
Establishments engaged in agricultural production activities (of agricultural goods). ISIC (Rev. 4) Groups:
Group 011: Growing of non - perennial crops;
Group 012: Growing of perennial crops
Group 013: Plant propagation
Group 014: Animal production
Group 015: Mixed farming
Summary report of key preliminary census data
Tabulations and reports in electronic format with online distribution
statistical releases/publications with predefined queries /
Standard tables (charts and maps) - a set of pre-designed basic tables (charts and maps) for all main topics of the census (hard copy, CD, web site)
Publications with preliminary and final census results
Preliminary results: In some cases, preliminary results are delivered prior to the presentation of final figures. These preliminary results can be produced either by sampling from census databases or by filling special forms during the field work.