Orchard (orch)

National Reference Metadata in ESS Standard for Orchard survey Quality Report Structure (esqrsor)

Compiling agency: MINISTRY OF AGRICULTURE, FOOD AND FORESTRY

Eurostat metadata

Reference metadata

1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)

For any question on data and metadata, please contact: Eurostat user support

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1. Contact

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1.1. Contact organisation

MINISTRY OF AGRICULTURE, FOOD AND FORESTRY

1.2. Contact organisation unit

AGROSTATISTICS DEPARTMENT

1.5. Contact mail address

BULGARIA, SOFIA 1040, 55 HRISTO BOTEV BLVD

2. Statistical presentation

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2.1. Data description

Main characteristics

2.1.1 Describe shortly the main characteristics of the statistics	Structural orchard statistics provide data on the area, age and density of apple, pear, peach, nectarine, apricot, citrus fruit and olive orchards and vineyards producing table grapes. The statistics are collected from surveys. Data are collected on national level and for some variables also at NUTS1 level. The data collection concerns countries with more than 1000 ha of area for any single fruit tree type.
2.1.2 Which of the fruit tree types are covered by the data collection?	Dessert apple trees Apple trees for industrial processing Dessert pear trees Pear trees for industrial processing Apricot trees Dessert peach and nectarine trees Peach and nectarine trees for industrial processing (including group of Pavie) Table grape vines Other
2.1.3 If Other, please specify	The fruits inclided in item OTHERS: plums, sweet cherry, sour cherry, walnuts, hazelnuts, almonds and raspberries.

Reference period

2.1.4 Reference period of the data collection	2017
2.1.5 When was the data collection done (month(s) and year)	December 2017 - February 2018

National legislation

2.1.6 Is there a national legislation covering these statistics?	Yes
If Yes, please answer all the following questions.
2.1.7 Name of the national legislation	Ordinance on the statistical survey on plantations of certain species of fruit trees in Bulgaria
2.1.8 Link to the national legislation	http://www.mzh.government.bg/bg/statistika-i-analizi/izsledvane-rastenievadstvo/normativna-uredba/
2.1.9 Responsible organisation for the national legislation	MAFF
2.1.10 Year of entry into force of the national legislation	2006
2.1.11 Please indicate which variables required under EU regulation are not covered by national legislation, if any.	None
2.1.12 Please indicate which national definitions differ from those in the EU regulation, if any.	None
2.1.13 Please indicate which additional variables have been collected if compared to Regulation (EU) 1337/2011, if any?	The addiditional variables are plums, sweet cherry, sour cherry, walnuts, hazelnuts, almonds and raspberries.
2.1.14 Is there a legal obligation for respondents to reply?	Yes

Additional comments on data description

2.2. Classification system

Species and variety group classification, age and density classifications available in RAMON

2.3. Coverage - sector

Growing of perennial crops (NACE A01.2)

2.4. Statistical concepts and definitions

See: Orchard statistics Handbook

2.4.1 Do national crop item definitions differ from the definitions in the Handbook (D-flagged data)?	No
2.4.2 If Yes, please specify the items and the differences
2.4.3 If the fruits for industrial processing are not separately surveyed, are they included in dessert fruit categories?	No
2.4.4 If yes, for which fruit tree types?
In case data are delivered for one of the items below, describe the 10 biggest varieties included in the item:
2.4.5 Other dessert apples n.e.c.	FLORINA, MUTSU/CRIPPSPINK, MELROSE, JONAGOL, DAYVANIYA, GOLDEN RESISTENT, SHARDEN, KARASTOYANKA, RED CHIF, GOLDEN PARMENA
2.4.6 Other dessert pears n.e.c.	POPSKA PEAR, WILLIAM'S, SANTA MARIA, PASSE CRASSANE, BOSKOVA MASLOVKA, HARDLAND, BEUREE GIFFARD, HARDIEVA MASLOVKA, STARKRIMSON, HARDEPONTOVA MASLOVKA
2.4.7 Other oranges n.e.c.
2.4.8 Other small citrus fruits, including hybrids

2.5. Statistical unit

Utilised agricultural area used for the cultivation of permanent crops mentioned in point 2.1, cultivated by an agricultural holding producing entirely or mainly for the market.

2.6. Statistical population

All agricultural holdings growing entirely or mainly for the market permanent crops mentioned in point 2.1.

2.7. Reference area

2.7.1 Geographical area covered	The entire territory of the country.
2.7.2 Which special Member State territories are included?

2.8. Coverage - Time

The first data collection took place in 2012. And the coverage time : 2012-2017.

2.9. Base period

not applicable

3. Statistical processing

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3.1. Source data

Overall summary

3.1.1 Total number of different data sources used	1
The breakdown is as follows:
3.1.2 Total number of sources of the type "Census"	1
3.1.3 Total number of sources of the type "Sample survey"	0
3.1.4 Total number of sources of the type "Administrative source"	0
3.1.5 Total number of sources of the type "Experts"	0
3.1.6 Total number of sources of the type "Other sources"	0

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 3.1 of the annexed Excel file
3.1.7 Name/Title	Structure of certain species of fruit trees in Bulgaria in 2017
3.1.8 Name of Organisation responsible	Ministry of agriculture, food and forestry
3.1.9 Main scope	The main scope of the statistical survey on the structure of certain fruit species in Bulgaria in 2017 is to obtain data on: - the number of holdings, cultivating fruit plantation in the country; - the density classes, the varieties and the age structure and the harvest period of the surveyed fruit trees.
3.1.10 Target fruit tree types	Dessert apple trees Dessert pear trees Apricot trees Dessert peach and nectarine trees Table grape vines Apple trees for industrial processing Pear trees for industrial processing Peach and nectarine trees for industrial processing (including group of Pavie)
3.1.11 List used to build the frame	Census2010, and new holdings found in the following fruit surveys, Structure of certain species of fruit trees in Bulgaria, Fss. The new holdings have been added to the lists, which declared in the IACS areas of observed permanent crops.
3.1.12 Any possible threshold values	Bulgaria exludes holdings below a threshold of 0,1 ha.
3.1.13 Population size	45728
3.1.14 Additional comments	In the population size ( 45728 units) are included holdings which observed fruits for national needs, as well as holdings with a closed activity and holdings below the threshold.

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 3.1 of the annexed Excel file
3.1.15 Name/Title
3.1.16 Name of Organisation responsible
3.1.17 Main scope
3.1.18 Target fruit tree types
3.1.19 List used to build the frame
3.1.20 Any possible threshold values
3.1.21 Population size
3.1.22 Sample size
3.1.23 Sampling basis
3.1.24 If Other, please specify
3.1.25 Type of sample design
3.1.26 If Other, please specify
3.1.27 If Stratified, number of strata
3.1.28 If Stratified, stratification criteria
3.1.29 If Other, please specify
3.1.30 Additional comments

Administrative source

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 3.1 of the annexed Excel file
3.1.31 Name/Title
3.1.32 Name of Organisation responsible
3.1.33 Contact information (email and phone)
3.1.34 Main administrative scope
3.1.35 Target fruit tree types
3.1.36 Geospatial Coverage
3.1.37 Update frequency
3.1.38 Legal basis
3.1.39 Are you able to access directly to the micro data?
3.1.40 Are you able to check the plausibility of the data, namely by contacting directly the units?
3.1.41 How would you assess the proximity of the definitions and concepts (including statistical units) used in the administrative source with those required in the EU regulation?
3.1.42 Please list the main differences between the administrative source and the statistical definitions and concepts
3.1.43 Is a different threshold used in the administrative source and statistical data?
3.1.44 If Yes, please specify
3.1.45 Additional comments

Experts

If there is more than one Expert source, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.46 Name/Title
3.1.47 Primary purpose
3.1.48 Target fruit tree types
3.1.49 Legal basis
3.1.50 Update frequency
3.1.51 Expert data supplier
3.1.52 If Other, please specify
3.1.53 How would you assess the quality of those data?
3.1.54 Additional comments

Other sources

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.55 Name/Title
3.1.56 Name of Organisation
3.1.57 Primary purpose
3.1.58 Target fruit tree types
3.1.59 Data type
3.1.60 If Other, please specify
3.1.61 How would you assess the quality of those data?
3.1.62 Additional comments

3.2. Frequency of data collection

The data collection of structure of certain species of fruit trees in Bulgaria is every 5 years under Regulation (EU) 1337/2011. The first data collection took place in 2012.

3.3. Data collection

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 3.3 of the annexed Excel file
3.3.1 Name/Title	Structure of certain species of fruit trees in Bulgaria in 2017.
3.3.2 Methods of data collection	Face-to-face interview Telephone interview
3.3.3 If Other, please specify
3.3.4 If face-to-face or telephone interview, which method is used?	Paper questionnaire
3.3.5 Data entry method, if paper questionnaires?	Manual
3.3.6 Please annex the questionnaire used (if very long: please provide the hyperlink)
3.3.7 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 3.3 of the annexed Excel file
3.3.8 Name/Title
3.3.9 Methods of data collection
3.3.10 If Other, please specify
3.3.11 If face-to-face or telephone interview, which method is used?
3.3.12 Data entry method, if paper questionnaires?
3.3.13 Please annex the questionnaire used (if very long: please provide the hyperlink)
3.3.14 Additional comments

Administrative source

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 3.3 of the annexed Excel file
3.3.15 Name/Title
3.3.16 Extraction date
3.3.17 How easy is it to get access to the data?
3.3.18 Data transfer method
3.3.19 Additional comments

Experts

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.3 of the annexed Excel file
3.3.20 Name/Title
3.3.21 Methods of data collection
3.3.22 Additional comments

Annexes:
BG_QuestionnaireStructureOrchards2017

3.4. Data validation

3.4.1 Which kind of data validation measures are in place?	Automatic
3.4.2 What do they target?	Completeness
3.4.3 If Other, please specify

3.5. Data compilation

3.5.1 Describe the data compilation process	not available
3.5.2 Additional comments

3.6. Adjustment

not available

4. Quality management

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4.1. Quality assurance

4.1.1 Is there a quality management system used in the organisation?	Yes
4.1.2 If yes, how is it implemented?	The individual data is checked through series of logical and mathematical controls. The completeness of the records is checked for the obligatory fields of the questionnaire. The completeness of the units from the list to be surveyed is also checked. Tools used for data validation: - manual for interviewers; - online computer system. Validation is done at district (local collection centre) and central level (final collection centre) of the MAFF.
4.1.3 Has a peer review been carried out?	No
4.1.4 If Yes, which were the main conclusions?
4.1.5 What quality improvements are foreseen?	Further automation
4.1.6 If Other, please specify
4.1.7 Additional comments

4.2. Quality management - assessment

Development since the last quality report

4.2.1 Overall quality	Improvement
4.2.2 Relevance	Stable
4.2.3 Accuracy and reliability	Stable
4.2.4 Timeliness and punctuality	Stable
4.2.5 Comparability	Stable
4.2.6 Coherence	Stable
4.2.7 Additional comments	The collected data for pears are 668 ha. The data are not sent because they are under the reported treshhold of 1000 ha.

5. Relevance

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5.1. Relevance - User Needs

5.1.1 If certain user needs are not met, please specify which and why	All questions concerning the content of the questionnaire were discussed on a meeting with experts from MAFF and different organizations.
5.1.2 Please specify any plans to satisfy needs more completely in the future	The permanent crop with national importance were included in the questiionnaire and surveyed. The addiditional variables are plums, sweet cherry, sour cherry, walnuts, hazelnuts, almonds and raspberries.
5.1.3 Additional comments

5.2. Relevance - User Satisfaction

5.2.1 Has a user satisfaction survey been conducted?	Yes
If Yes, please answer all the following questions
5.2.2 Year of the user satisfaction survey	2017
5.2.3 How satisfied were the users?	Satisfied
5.2.4 Additional comments	Yes, at the end of 2017 was conducted a meeting with data users to explore their needs. At their request, irrigation areas are included in the questionnaire.

5.3. Completeness

5.3.1 Data completeness - rate	All data was sent with the exception of the data for pears. The collected data for pears are 668 ha.
5.3.2 If not complete, which characteristics are missing?	The collected data for pears are 668 ha.
5.3.3 Additional comments

6. Accuracy and reliability

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6.1. Accuracy - overall

6.1.1 How good is the accuracy?	Good
6.1.2 What are the main factors lowering the accuracy?	Coverage error
6.1.3 If Other, please specify
6.1.4 Additional comments

6.2. Sampling error

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.2 of the annexed Excel file

6.2.1 Name/Title

6.2.2 Methods used to assess the sampling error

6.2.3 If Other, please specify

6.2.4 Methods used to derive the extrapolation factor

6.2.5 If Other, please specify

6.2.6 If coefficients of variation are calculated, please describe the calculation methods and formulas

6.2.7 Sampling error - indicators

Please provide the coefficients of variation in %

	CV (%)
Dessert apple trees
Apple trees for industrial processing
Dessert pear trees
Pear trees for industrial processing
Apricot trees
Dessert peach and nectarine trees
Peach and nectarine trees for industrial processing (including group of Pavie)
Orange trees
Small citrus fruit trees
Lemon trees
Olive trees
Table grape vines

6.2.8 Additional comments

6.3. Non-sampling error

See sections below.

6.3.1. Coverage error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.1 Name/Title	Structure of certain species of fruit trees in Bulgaria in 2017
Over-coverage
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope?	No
6.3.1.3 What methods are used to detect the out-of scope units?
6.3.1.4 Does the sample frame include units that do not exist in practice?	No
6.3.1.5 Over-coverage - rate
6.3.1.6 Impact on the data quality
Under-coverage
6.3.1.7 Does the sample frame include all units falling within the scope of this survey?	Yes
6.3.1.8 If Not, which units are not included?
6.3.1.9 How large do you estimate the proportion of those units? (%)
6.3.1.10 Impact on the data quality	None
Misclassification
6.3.1.11 Impact on the data quality	None
Common units
6.3.1.12 Common units - proportion
6.3.1.13 Additional comments	The holdings cultivating fruit plantations crops have a dinamic structure. A lot of new holdings arised.

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.14 Name/Title
Over-coverage
6.3.1.15 Does the sample frame include wrongly classified units that are out of scope?
6.3.1.16 What methods are used to detect the out-of scope units?
6.3.1.17 Does the sample frame include units that do not exist in practice?
6.3.1.18 Over-coverage - rate
6.3.1.19 Impact on the data quality
Under-coverage
6.3.1.20 Does the sample frame include all units falling within the scope of this survey?
6.3.1.21 If Not, which units are not included?
6.3.1.22 How large do you estimate the proportion of those units? (%)
6.3.1.23 Impact on the data quality
Misclassification
6.3.1.24 Impact on the data quality
Common units
6.3.1.25 Common units - proportion
6.3.1.26 Additional comments

Administrative data

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.27 Name/Title of the administrative source
Over-coverage
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope?
6.3.1.29 What methods are used to detect the out-of scope units?
6.3.1.30 Does the administrative source include units that do not exist in practice?
6.3.1.31 Over-coverage - rate
6.3.1.32 Impact on the data quality
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey?
6.3.1.34 If Not, which units are not included?
6.3.1.35 How large do you estimate the proportion of those units? (%)
6.3.1.36 Impact on the data quality
Misclassification
6.3.1.37 Impact on the data quality
6.3.1.38 Additional comments

6.3.2. Measurement error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.2.1 Name/Title	Structure of certain species of fruit trees in Bulgaria in 2017
6.3.2.2 Is the questionnaire based on usual concepts for respondents?	Yes
6.3.2.3 Number of censuses already performed with the current questionnaire?	0
6.3.2.4 Preparatory testing of the questionnaire?	Yes
6.3.2.5 Number of units participating in the tests?	28
6.3.2.6 Explanatory notes/handbook for surveyors/respondents?	Yes
6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents?	Yes
6.3.2.8 Are there pre-filled questions?	No
6.3.2.9 Percentage of pre-filled questions out of total number of questions	0
6.3.2.10 Other actions taken for reducing the measurement error?	Yes
6.3.2.11 Additional comments	One (2012) with a slightly amended version. In structure of certain species of fruit trees in Bulgaria in 2017 more permanent crops were included in the research.

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.2.12 Name/Title
6.3.2.13 Is the questionnaire based on usual concepts for respondents?
6.3.2.14 Number of surveys already performed with the current questionnaire?
6.3.2.15 Preparatory testing of the questionnaire?
6.3.2.16 Number of units participating in the tests?
6.3.2.17 Explanatory notes/handbook for surveyors/respondents?
6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents?
6.3.2.19 Are there pre-filled questions?
6.3.2.20 Percentage of pre-filled questions out of total number of questions
6.3.2.21 Other actions taken for reducing the measurement error?
6.3.2.22 Additional comments

6.3.3. Non response error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.3.1 Name/Title of the survey	Structure of certain species of fruit trees in Bulgaria in 2017
6.3.3.2 Unit non-response - rate	<0.1%
6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context?	Very low
6.3.3.4 Measures taken for minimising the unit non-response	Follow-up interviews
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate	In case of unit non-response the holder is contacted again in order to obtain response. In case the second attempt for interview is not successful the available data is imputed.
6.3.3.7 Item non-response rate - Minimum	min
6.3.3.8 Item non-response rate - Maximum
6.3.3.9 Which items had a high item non-response rate?
6.3.3.10 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.3.11 Name/Title of the survey
6.3.3.12 Unit non-response - rate
6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context?
6.3.3.14 Measures taken for minimising the unit non-response
6.3.3.15 If Other, please specify
6.3.3.16 Item non-response rate
6.3.3.17 Item non-response rate - Minimum
6.3.3.18 Item non-response rate - Maximum
6.3.3.19 Which items had a high item non-response rate?
6.3.3.20 Additional comments

6.3.4. Processing error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.4.1 Name/Title	Structure of certain species of fruit trees in Bulgaria in 2017
6.3.4.2 Imputation - rate
6.3.4.3 Imputation - basis
6.3.4.4 If Other, please specify
6.3.4.5 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.4.6 Name/Title
6.3.4.7 Imputation - rate
6.3.4.8 Imputation - basis
6.3.4.9 If Other, please specify
6.3.4.10 How do you evaluate the impact of imputation on Coefficients of Variation?
6.3.4.11 Additionnal comments

6.3.5. Model assumption error

6.4. Seasonal adjustment

6.5. Data revision - policy

6.6. Data revision - practice

6.6.1 Data revision - average size	None
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions) carried out since the last quality report?	No
6.6.3 What was the main reason for the revisions?	The individual data is checked through series of logical and mathematical controls. The completeness of the records is checked for the obligatory fields of the questionnaire.
6.6.4 How do you evaluate the impact of the revisions?
6.6.5 Additional comments

7. Timeliness and punctuality

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7.1. Timeliness

7.1.1 When were the first results for the reference period published?	The first results are still not published.
7.1.2 When were the final results for the reference period published?	The results will be published at the end of 2018.
7.1.3 Reasons for possible long production times?	The final results are not published due to need of further analysis and control.

7.2. Punctuality

7.2.1 Were data released nationally according to a pre-announced schedule (Release Calendar)?	No
7.2.2 If Yes, were data released on the target date?
7.2.3 If No, reasons for delays?	A preliminary publication of basic data on 13 crops was published at the end of January 2019. The main reason for the delay of publication was due to technical reasons.
7.2.4 Number of days between the national release date of data and the target date	A preliminary publication of basic data was published at the end of January 2019. So the number of days between the national release date of data and the target date is 30 days.

8. Coherence and comparability

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8.1. Comparability - geographical

8.1.1. Asymmetry for mirror flow statistics - coefficient

8.2. Comparability - over time

8.2.1 Length of comparable time series	Same NUTS0 region. The extent of CROP statistics ( production of fruits) is comparable to this survey. Or Structure of plantation of certain species of fruits trees in Bulgaria on 2012.
8.2.2 Have there been major breaks in the time series?	No
8.2.3 If Yes, please specify the year of break and the reason
8.2.4 Additional comments

8.3. Coherence - cross domain

8.3.1 With which other national data sources have the data been compared?

Annual crop statistics 2017
FSS 2016
IACS

8.3.2 If Other, please specify

8.3.3 Describe briefly the results of comparisons

Results should be expressed as percentage deviation from the corresponding areas in the orchard survey.

	Annual Crop Statistics (2017)	FSS (2016)	IACS	Other source
Dessert apple trees	3973	5376.4	3898.6
Apple trees for industrial processing	-	-	-
Dessert pear trees	449	571.2	549.5
Pear trees for industrial processing	-	-	-
Apricot trees	2898	2822.2	2898.4
Dessert peach and nectarine trees	3893	3701	3020.9
Peach and nectarine trees for industrial processing (including group of Pavie)	-	-	-
Orange trees	0	0	0
Small citrus fruit trees	0	0	0
Lemon trees	0	0	0
Olive trees	0	0	0
Table grape vines	2126	2339.9	2184

The data for Annual Crop Statistics (2017) concern production area of the variables.

8.3.4 If no comparisons have been made, explain why

8.3.5 Additional comments

8.4. Coherence - sub annual and annual statistics

8.5. Coherence - National Accounts

8.6. Coherence - internal

9. Accessibility and clarity

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9.1. Dissemination format - News release

9.1.1 Do you publish a news release?	No
9.1.2 If Yes, please provide a link

9.2. Dissemination format - Publications

9.2.1 Do you produce a paper publication?	No
9.2.2 If Yes, is there an English version?	Yes
9.2.3 Do you produce an electronic publication?	Yes
9.2.4 If Yes, is there an English version?	Yes
9.2.5 Please provide a link	http://www.mzh.government.bg/bg/statistika-i-analizi/izsledvane-rastenievadstvo/danni/

9.3. Dissemination format - online database

9.3.1 Data tables - consultations	Not available
9.3.2 Is an on-line database accessible to users?	No
9.3.3 Please provide a link

9.4. Dissemination format - microdata access

9.4.1 Are micro-data accessible to users?	No
9.4.2 Please provide a link

9.5. Dissemination format - other

9.6. Documentation on methodology

9.6.1 Are national reference metadata files available?	No
9.6.2 Please provide a link	in process of preparation
9.6.3 Are methodological papers available?	No
9.6.4 Please provide a link	in process of preparation
9.6.5 Is a handbook available?	Yes
9.6.6 Please provide a link	in process of preparation

9.7. Quality management - documentation

9.7.1 Metadata completeness - rate	100%
9.7.2 Metadata - consultations
9.7.3 Is a quality report available?	No
9.7.4 Please provide a link

10. Cost and Burden

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10.1 Efficiency gains if compared to the previous quality report	Further automation
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report	More user-friendly questionnaires
10.4 If Other, please specify

11. Confidentiality

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11.1. Confidentiality - policy

11.1.1 Are confidential data transmitted to Eurostat?	Yes
11.1.2 If yes, are they confidential in the sense of Reg. (EC) 223/2009?	Yes
11.1.3 Describe the data confidentiality policy in place	Individual data are confidential and not disseminated as such.

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination	No dissemination of the confidential cells. Results for less than 3 holdings or when a holding owns 85 % of the published characteristics are not published.
11.2.2 Additional comments

12. Comment

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Annexes