Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Ulf Svensson: Administrative officer. Responibility within organic farming statistics;Methodology, data collection, dissemination
1.5. Contact mail address
Jordbruksverket
SE-551 82 Jönköping
Sweden
1.6. Contact email address
ulf.svensson@jordbruksverket.se
1.7. Contact phone number
+4636155074
1.8. Contact fax number
2.1. Metadata last certified
5 July 2023
2.2. Metadata last posted
5 July 2023
2.3. Metadata last update
5 July 2023
3.1. Data description
The collected statistics for the country cover the following data:
Certified registered organic operators (referring to their main or secondary activity) (expressed in number of operators)
Certified registered organic processors who manufacture organic products (as their main or secondary activity) (expressed in number of processors)
Certified organic crop area (under conversion and fully converted) (expressed in hectares)
Certified organic crop production from fully converted area (expressed in 1 000 kg)
Certified organic livestock (expressed in heads of live animals)
Production of certified organic products of animalorigin (expressed in 1 000 kg of carcass weight and in thousand eggs)
Production of certified organic milk products (Produced on farms or Processed on farms or by dairy enterprises) and Honey and products of bee-keeping (expressed in 1 000 kg of products obtained)
Certified organic aquaculture sold by producers (expressed in 1 000 kg live weight)
Total utilized agricultural area of certified organic farming are availble from 2005 and onwards.
For most of the other variables, data is available from 2009 and onwards.
3.9. Base period
Not applicable.
Certified registered organic operators (referring to their main or secondary activity) (expressed in number of operators)
Certified registered organic processors who manufacture organic products (as their main or secondary activity) (expressed in number of processors)
Certified organic croparea (under conversion and fully converted) (expressed in hectares)
Certified organic cropproduction from fully converted area (expressed in 1 000 kg)
Certified organic livestock (expressed in heads of live animals)
Production of certified organic products of animal origin (expressed in 1 000 kg of carcass weight and in thousand eggs)
Production of certified organic milk products (Produced on farms or Processed on farms or by dairy enterprises) and Honey and products of bee-keeping (expressed in 1 000 kg of products obtained)
Certified organic aquaculture sold by producers (expressed in 1 000 kg live weight)
Data on operators and manufacture: End of 2022
For areas and crop production: Crops grown and harvested during 2022
Number of animals: 2 July 2022
Animal production and Aqualculture: Production during 2022
6.1. Institutional Mandate - legal acts and other agreements
According to the national ordinance (2013:1059) on controls of organic production, the Swedish Board of Agriculture and the Swedish Food Agency is authorized to put in force provisions on, amongst other things, data collection on organic farming.
With the authorization from the national ordinance, mentioned above, the Swedish Board of Agriculture has established a provision (SJVFS 2021:47) on organic production. According to this regulation, the control bodies are obliged to send micro-data, for all their clients which are agricultural/aquaculture producers, to the Swedish Board of Agriculture in March the year after the reference year. The control bodies are also obliged to send data covering the data requirements for Operators (dataset_1A) and Processors (dataset_1B) according to the provision (LIVSFS 2021:12) established by the Swedish Food Agency.
According to the national ordinance (2001:100) on official statistics, the Swedish Board of Agriculture is the responsible authority for producing and disseminating official statistics on agriculture and aquaculture within the Swedish statistical system. This also gives the Swedish Board of Agriculture legal right to access data from other agencies for the production and dissemination of official statistics.
6.2. Institutional Mandate - data sharing
According to the national ordinance (2001:100) on official statistics, the SBA is the responsible authority for producing and disseminating official statistics on agriculture and aquaculture within the Swedish statistical system. This also gives the SBA legal right to access data from other agencies for the production and dissemination of official statistics.
7.1. Confidentiality - policy
According to the national law (2001:99) on official statistics, the ordinance 2001:100 on official statistics and the Public access to information and secrecy act (2009:400) data collected for the purpose of producing official statistics is treated as confidential when it comes to information about individuals or companies. Researchers have access to de-identified micro data on individual level.
The staff at the Statistic unit at the Swedish Board of Agriculture workes under the acts mentioned above. They are well informed about their obligations in treating confidential data. The Statistic unit is separated from other activities at the Board of Agriculture in that the staff are directed to separate premises.
7.2. Confidentiality - data treatment
The main principles are that there should be at least three respondents behind the information in one cell to make it possible to disseminate the results. But if one of the respondent have a large influence on the results the number of respondents might be increased. This part of the procedure is done automatically. The tables for dissemination is also checked manually to detect cases where users might have the possibility to detect confidential data by e.g. summing upp rows and columns. In this cases cells are suppressed manually.
Researchers who want to have access to microdata must present a summary of the research project including a description on why the microdata is important. The head of the Statistics unit then take a decision on access to de-identified microdata. The decision also includes rules of conduct which normally sets out which persons who can have access to the data, during what time period, intstructions to delete microdata when the time period has passed.
8.1. Release calendar
There is a release calender and it is public accessable at the webbsite of the Swedish Board of Agriculture as well as the website of Statistics Sweden.
The dissemination is done at 08:00 at the stated date in the release calender. The statistical report and the datsbase tables are available to all users at the same time. No users can have access to the data before it is released. The dissemination is followed by a press release.
Data on areas, crop production, number of animals, slaughter is disseminated annualy in statistical reports and in our statistical database. Data on organic horticultural production is only disseminated in the statistical database.
Data on cows milk from farm, dairy production and eggs for consumption are disseminated in our statistical database on a monthly basis. A yearly statistical report is produced.
10.1. Dissemination format - News release
There are annual press releases for the following statistical reports
Organic crop areas
Number of organic reared animals
Organic animal production
Organic crop production (harvests)
10.2. Dissemination format - Publications
The following statistical reports are disseminated annually and have been published for 2022. Only in swedish with a short summary i english.
The chart below shows the number of database views. There is a possibility that a user has downloaded more than one table from the database in the same session.
The sharp increase between 2019 and 2020 is probably explained by a change in our dissemination of the statistical reports. From 2020 and onwards there is a section in the html-report with links to specific database tables. This probably made it easier, for users not so familiar with extracting data from the database, to download data from the database.
10.4. Dissemination format - microdata access
Microdata is not disseminated. Researchers can have access to de-identified microdata, se 7.2
10.5. Dissemination format - other
None
10.5.1. Metadata - consultations
Metadata is available to all users. Number of consultations is not availble.
10.6. Documentation on methodology
In connection with the disseminated statistical reports mentioned in 10.2 there are two metadata reports for each publication; one declaration on the quality and one describing how the statistics in produced.
10.6.1. Metadata completeness - rate
Not applicable.
10.7. Quality management - documentation
The Swedish Board of Agriculture has established a general production process for official statistics at the Board. It is available at our webbsite but only in Swedish. It follows the UNECE production process but it is adapted to cover all parts of the European statistics Code of Practice.
11.1. Quality assurance
The Swedish Board of Agriculture has implemented a statistical process used for all official statistics produced. The process follows in principle the statistical process of the UNECE (Generic statistical business process model) but is adapted to cover all parts of the European statistics Code of Practice.
Qyality management is assessed by Statisics Sweden's provisions on quality in official statistics (SCB-FS 2021:26). Results are reported by Statistics Sweden to the Ministry of finance every year.
When disseminating the statistical results we also disseminate an assessemnent of the quality of the statistics according to the following criteria:
Relevance
Accuracy
Timeliness and punctuality
Coherence and comparability
12.1. Relevance - User Needs
Users of the statistics
There is a wide spectrum of users. The following is an attempt to categorize them.
Governmental agencies
Ministry of Rural Affairs and Infrastructure
County Administrative Boards
Swedish Environmental and Protection Agency
Statistics Sweden
Swedish Board of Agriculture
Municipalities
Media
Agricultural business sector
Swedish farmers association and other organisations within the sector
Education
Swedish University of Agricultural Science
Other Universities and college students
Others
Advisors in organic farming
Consultants
Interest organization and private individuals
Main uses
There are a lot of uses, some exampels
Follow-up of goals in the field of organic farming
Decisionmaking
Evaluate effects of subsidies for organic farming
Evaluate environmental impact of organic farming
Research
Disseminating information in general
Key outputs and shortcomings
As there is a wide spectrum of users there is a wide spectrum of output requested, e.g.
Organic cultivated areas and share of organic area out of the total agricultural area for the entier country as well as by county and municipalities
Organic crop production, yield per hectare an total harvests
Number of organic reared animals and share of organic reared animals out of the total number of animals for the entier country as well as by county and municipalities
Slaughtered animals in heads and metric tons
Production of organic animal prouducts (dairy production and production of egg)
Import/export of organic products
Unmet user needs
We believe that most user needs are fulfilled. One example were the user needs are not fulfilled is data on import and export. We do not collect any data on import and export. However our assessement is that collecting data on imports and exports would be very costly and the burden of the respondents would be huge.
12.2. Relevance - User Satisfaction
There is no specific user satisfaction survey implemented for organic farming. But the Swedish Board of Agriculture is responsible for agricultural statistics within the statistical system in Sweden. This responsibility also includes an obligation to have a yearly meeting with a council, composed by the main users of agricultural statistics in general. During the meetings of the council the users have the possibility to comment also on the organic farming statistics. In addition to questions received by telephone, mail etc., this is our main channel to check the user satisfaction. The last meeting of the council was held in november 2022.
12.3. Completeness
Sweden transmit data for almost all mandatory fields required according to the ESS-agreement, except for those fields that are considered as non-significant for Sweden.
The data was transmitted within the deadline with the exception of data for aquaculture. Data for aquaculture will be transmitted to Eurostat in august 2023.
12.3.1. Data completeness - rate
Disregarding mandatory data cells which are considered non-significant for Sweden, the completeness rate in 100 %.
13.1. Accuracy - overall
A brief overview of data sources used in relation to accuracy
Data collected from the control bodies
The main source of errors are probably measurement errors. Coverage errors are also detected but are not as common as measurement errors. Even if errors are detected and corrected, there are probably still undetected errors at micro-level. See section 18 for actions undertaken to minimize the errors. On an aggregated level, the assessement is that accuracy is good.
Statistical Farm Register
The Farm register is based on both administrative data from several registers and surveys. These registers and surveys might contain coverarage errors, measurement errors, sampling errors etc. All in all, tha assessment is that the accuracy of the different sources are good and this also applies to the Farm Register as a whole.
Crop production survey
The main sources of errors is assessed to be sampling errors and measurement errors. The assessment is that the overall accuracy is very good. The data is checked carefully. See section 18 for actions undertaken to minimize different types of errors.
Horticultural areas and production
All areas are based on data from the control bodies. The main source of errors for areas are probably measurement errors. Coverage errors are also detected but are not as common as measurement errors. Even if errors are detected and corrected, there are probably still undetected errors at micro-level. See section 18 for actions undertaken to minimize the errors. On an aggregated level, the assessement is that accuracy is very good.
Horticultural production is based on census data every third year (last time 2020). For the years in between, data on production is based on a model using relative yields on organic and conventional production from the last census year. The main source of errors for areas are probably measurement errors from the control bodies and the census data. On an aggregated level, the assessement is that accuracy is very good.
Register of slaughtered animals
Administrative register. It is mandatory for the slaughterhouses to report their slaughter on a weekly basis according to provisions issued by the Swedish Board of Agriculture. Both physical and administrative checks are carried out. The assessment is that the accuracy is very good. Measurement errors and coverage errors should be negligible.
Data collected from Dairies and Svenska ägg (wholesaler for egg)
The main sources of errors is assessed to be measurement errors and model assumptions. In the case of data from dairies there is a model for estimate production of some dairy products for one of the dairies. In the case of egg production, the whole market is not covered by Svenska ägg but there is an estimate on the market share of Svenska ägg which is used to estimate the total production.
Aquaculture survey
The main source of errors is assessed to be measurement errors and non-response. there are coverage errors but is assessed to have very low impact on the quality of the results. See section 18 for actions undertaken to minimize the errors. There are very few organic aquaculture producers in Sweden and data from the aquaculture surevey and data from the controlbodies can easily be compared which is an extra check of the accuracy of the data.
13.2. Sampling error
Crop production survey
A probability sample where the base is area
The stratifiction is based on location and the number of strata are different for different crops:
Cereals, dry pulses and oilseeds - 101
Table potatoes - 6
From the frame of holdings applying for subsidies for organic production and cultivating more than 5 hectares of arable land a sample was taken:
For cereals, dry pulses and oilseeds - sample size 1 862 holdings
Table potatoes - sample size 137 holdings
13.2.1. Sampling error - indicators
Standard errors in percent for total harvests 2022. Estimates for the whole country:
Winter wheat
0,6
Spring Wheat
1,5
Rye
2,4
Winter barley
3,2
Spring barley
1,3
Oats
1,5
Winter triticale
1,1
Spring triticale
6,3
Spring cereal mixtures
3,3
Cereals total
0,7
Field peas
1,6
Field beans
1,3
Winter rape
1,3
Winter turnip rape
5,9
Spring turnip rape
1,7
Green maize
2,1
Table potatoes
1,4
13.3. Non-sampling error
Data from Control bodies
Coverage errors, measurement errors and processing errors can exist. For actions undertaken to reduce these errors, se Annex 1 (section 18) and the headings 18.1 data collection and 18.4 data validation for the different datasets. For the statistics on number of animals and slaugtering model assumption errors could also exist.
Statistical Farm Register
See section 13.1
Data from the crop production survey
Coverage errors, measurement errors, non-respons errors, processing errors and model assumptions can exist. For actions undertaken to reduce the errors, see Annex 1 (section 18) and the headings 18.1 data collection and 18.4 data validation for dataset 2.
Horticultural areas and production
All areas are based on data from the control bodies. The main source of errors for areas are probably measurement errors. Coverage errors are also detected but are not as common as measurement errors. For actions undertaken to reduce these errors, se Annex 1 (section 18) and the headings 18.1 data collection and 18.4 data validation for dataset 2.
Register of slaughtered animal
See section 13.1
See section 13.1
Aquaculture survey
See section 13.1
13.3.1. Coverage error
See section 13.1 and 13.3
13.3.1.1. Over-coverage - rate
See section 13.1 and 13.3
13.3.1.2. Common units - proportion
See section 13.1 and 13.3
13.3.2. Measurement error
See section 13.1 and 13.3
13.3.3. Non response error
See section 13.1 and 13.3
13.3.3.1. Unit non-response - rate
See section 13.1 and 13.3
13.3.3.2. Item non-response - rate
See section 13.1 and 13.3
13.3.4. Processing error
See section 13.1 and 13.3
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
See concepts below.
14.1.1. Time lag - first result
Firs results are equal to final results. There are no dissemination of preliminary data.
The dissemination of the results are done in separate statistical reports. Counting from the end of 2022, except organic dairy production and egg production the time lags are as follows
Organic utilised agricultural area/crop areas - 4,5 months
Number of organic reared animals - 5,5 months
Organic crop production -5,5 months
Organic products with animal origin - organic dairy production and egg production is dissemninated on a montly basis with a time lag of 2 months. The dissemination of data on slaughter of organic reared animals are published annually with a time lag of 6 months.
14.1.2. Time lag - final result
First results are equal to final results. There are no dissemination of preliminary data. Se section 14.1.1
14.2. Punctuality
See concepts below.
14.2.1. Punctuality - delivery and publication
For the national publications, the dissemination was done at the target date according to the release calender, that is, the release was on time.
The transmission to Eurostat was on time for all datasets except Dataset_5, Aquaculture production. Aquaculture production data will be transmitted to Eurostat in august 2023.
15.1. Comparability - geographical
The data is comparable between regions.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
15.2. Comparability - over time
There are no major breaks in time series during the last 5 year.
15.2.1. Length of comparable time series
The disseminated time series are comparable over time since 2009.
15.3. Coherence - cross domain
In general the statistics on organic farming is comparable with the following statistics
There are some minor differences for agricultural areas. In producing the statistics on organic agricultural areas w use microdata from the control bodies. The control bodies submits areas per client divided by crop. The concept of client is not the same as holding in the statistical farm register. But if we link the registers from the control bodies with the statistical farm register there are only few clients that can´t be linked to the statistical farm register. If we apply the thresholds for the farm register on the registers from the control bodies very few clients are under the thresholds. The conclusion is that the data on cultivated areas in dataset_2 are very much in line with other related official statistics on areas, despite the differences in the concept of holdings.
15.3.1. Coherence - sub annual and annual statistics
Not applicable.
15.3.2. Coherence - National Accounts
Not applicable.
15.4. Coherence - internal
Each set of output is internally consistent.
Costs for collection and production of the statisticl products
The exact cost is difficult to calculate. A lot of the organic production data is for example based on registers and data extracted from surveys not only refering to organic production. Our estimate is based on costs that can be more directly attributed to the collection, production and dissemination of organic production data.
In national currecy, a rough estimate of cost is 1 000 000 SEK on an annual basis for producing and disseminating statistics on organic productioon .
Burden of respondents
It is not possible to provide a total burden of the respondents. However, we try to minimize the burden as much as possible using administrative data, statistical surveys and combination of both. In som cases, for example, crops cultivated on small areas we use expert estimates for the yield per hectare to estimate the total harvests.
In Sweden we use data from the control bodies, the statistical farm register and administrative registers held at the Swedish Board of agriculture (Register of slaughtering) to produce statistics on organic farming. We collect data on organic animal production from dairies in connection to the ordinary collection of data from the dairies. Data on organic crop production is produced in a survey that’s been ongoing for many years. And we use our yearly horticultural survey in combination with data from the control bodies to estimate the production of organic horticultural products. The yearly aquaculture survey is used in combination with data from the control bodies to produce organic aquaculture production.
It should be mentioned that when we started to build up the collection system for organic production in 2009, the burden of the respondents was one of our main concerns. At an early stage we realised that the control bodies already collected data on certified organic production in a system to be able to report data to the organisation KRAV (private organic label in Sweden). This data reporting system could be reused to send data also for the official statistics on organic farming. Using an existing reporting system in combination with administrative data and other statistical surveys made the burden of the respondents less burdensome from the start.
Except fulfilling the requirements according to the ESS-agreement and national need for data, the microdata collected from the control bodies, in combination with our Farm Register, is used to fulfil the requirements for data on organic farming according to the IFS regulation. So using data from the control bodies in the IFS we can minimize the questions on organic farming i the IFS which means lowering the burden of the respondents.
17.1. Data revision - policy
We do not have any preliminary data, that later on will be revised. The data disseminated is treated as final.
We do have a policy/routine for unplanned revisions in the case of errors in disseminated data. Se 17.2
17.2. Data revision - practice
We do not have any planned revisions of data. Data has not been revised during the last 3 years.
There is a policy/routine for unplanned revisions due to errors in data that has been disseminated. A form, containing the following, should be filled out:
Date when the error was discovered
A description of the error
Categorization of the error with a scale from minor errors as spelling errors etc, not affect the interpretation of the statistics, to serious errors where incorrect data has been disseminated.
Is the error in the statistical database or in the statistical report or in both?
Description of how the error was found. Was it found by staff at the Statistics unit or was it someone "external" who found it?
What are the correct data?
Other information in connection to the detected error
The head of the Statistic unit is informed an decides which measures are to be taken based on the above-mentioned information. In case of serious errors the data is removed immediatetly from the database/report.
17.2.1. Data revision - average size
Not applicable.
18.1. Source data
See Annex 1 describing the statistical processing for the different data sets
18.2. Frequency of data collection
See Annex 1 describing the statistical processing for the different data sets
18.3. Data collection
See Annex 1 describing the Statistical processing for the different data sets
18.4. Data validation
See Annex 1 describing the statistical processing for the different data sets
18.5. Data compilation
See Annex 1 describing the statistical processing for the different data sets
18.5.1. Imputation - rate
See Annex 1 describing the statistical processing for the different data sets.
18.6. Adjustment
See Annex 1 describing the statistical processing for the different data sets
The collected statistics for the country cover the following data:
Certified registered organic operators (referring to their main or secondary activity) (expressed in number of operators)
Certified registered organic processors who manufacture organic products (as their main or secondary activity) (expressed in number of processors)
Certified organic crop area (under conversion and fully converted) (expressed in hectares)
Certified organic crop production from fully converted area (expressed in 1 000 kg)
Certified organic livestock (expressed in heads of live animals)
Production of certified organic products of animalorigin (expressed in 1 000 kg of carcass weight and in thousand eggs)
Production of certified organic milk products (Produced on farms or Processed on farms or by dairy enterprises) and Honey and products of bee-keeping (expressed in 1 000 kg of products obtained)
Certified organic aquaculture sold by producers (expressed in 1 000 kg live weight)
For areas and crop production: Crops grown and harvested during 2022
Number of animals: 2 July 2022
Animal production and Aqualculture: Production during 2022
A brief overview of data sources used in relation to accuracy
Data collected from the control bodies
The main source of errors are probably measurement errors. Coverage errors are also detected but are not as common as measurement errors. Even if errors are detected and corrected, there are probably still undetected errors at micro-level. See section 18 for actions undertaken to minimize the errors. On an aggregated level, the assessement is that accuracy is good.
Statistical Farm Register
The Farm register is based on both administrative data from several registers and surveys. These registers and surveys might contain coverarage errors, measurement errors, sampling errors etc. All in all, tha assessment is that the accuracy of the different sources are good and this also applies to the Farm Register as a whole.
Crop production survey
The main sources of errors is assessed to be sampling errors and measurement errors. The assessment is that the overall accuracy is very good. The data is checked carefully. See section 18 for actions undertaken to minimize different types of errors.
Horticultural areas and production
All areas are based on data from the control bodies. The main source of errors for areas are probably measurement errors. Coverage errors are also detected but are not as common as measurement errors. Even if errors are detected and corrected, there are probably still undetected errors at micro-level. See section 18 for actions undertaken to minimize the errors. On an aggregated level, the assessement is that accuracy is very good.
Horticultural production is based on census data every third year (last time 2020). For the years in between, data on production is based on a model using relative yields on organic and conventional production from the last census year. The main source of errors for areas are probably measurement errors from the control bodies and the census data. On an aggregated level, the assessement is that accuracy is very good.
Register of slaughtered animals
Administrative register. It is mandatory for the slaughterhouses to report their slaughter on a weekly basis according to provisions issued by the Swedish Board of Agriculture. Both physical and administrative checks are carried out. The assessment is that the accuracy is very good. Measurement errors and coverage errors should be negligible.
Data collected from Dairies and Svenska ägg (wholesaler for egg)
The main sources of errors is assessed to be measurement errors and model assumptions. In the case of data from dairies there is a model for estimate production of some dairy products for one of the dairies. In the case of egg production, the whole market is not covered by Svenska ägg but there is an estimate on the market share of Svenska ägg which is used to estimate the total production.
Aquaculture survey
The main source of errors is assessed to be measurement errors and non-response. there are coverage errors but is assessed to have very low impact on the quality of the results. See section 18 for actions undertaken to minimize the errors. There are very few organic aquaculture producers in Sweden and data from the aquaculture surevey and data from the controlbodies can easily be compared which is an extra check of the accuracy of the data.
Certified registered organic operators (referring to their main or secondary activity) (expressed in number of operators)
Certified registered organic processors who manufacture organic products (as their main or secondary activity) (expressed in number of processors)
Certified organic croparea (under conversion and fully converted) (expressed in hectares)
Certified organic cropproduction from fully converted area (expressed in 1 000 kg)
Certified organic livestock (expressed in heads of live animals)
Production of certified organic products of animal origin (expressed in 1 000 kg of carcass weight and in thousand eggs)
Production of certified organic milk products (Produced on farms or Processed on farms or by dairy enterprises) and Honey and products of bee-keeping (expressed in 1 000 kg of products obtained)
Certified organic aquaculture sold by producers (expressed in 1 000 kg live weight)
See Annex 1 describing the statistical processing for the different data sets
See Annex 1 describing the statistical processing for the different data sets
Data on areas, crop production, number of animals, slaughter is disseminated annualy in statistical reports and in our statistical database. Data on organic horticultural production is only disseminated in the statistical database.
Data on cows milk from farm, dairy production and eggs for consumption are disseminated in our statistical database on a monthly basis. A yearly statistical report is produced.
See concepts below.
The data is comparable between regions.
There are no major breaks in time series during the last 5 year.
