Orchard (orch)

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

Compiling agency: Statistical Office of the Slovak Republic

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

Download

1. Contact

Top

1.1. Contact organisation

Statistical Office of the Slovak Republic

1.2. Contact organisation unit

Department of the Agricultural statistics

1.5. Contact mail address

Miletičova 3, 824 67 Bratislava, Slovakia

2. Statistical presentation

Top

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 and administrative data sources. 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
2.1.3 If Other, please specify

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)	October 2017

National legislation

2.1.6 Is there a national legislation covering these statistics?	No
If Yes, please answer all the following questions.
2.1.7 Name of the national legislation
2.1.8 Link to the national legislation
2.1.9 Responsible organisation for the national legislation
2.1.10 Year of entry into force of the national legislation
2.1.11 Please indicate which variables required under EU regulation are not covered by national legislation, if any.
2.1.12 Please indicate which national definitions differ from those in the EU regulation, if any.
2.1.13 Please indicate which additional variables have been collected if compared to Regulation (EU) 1337/2011, if any?
2.1.14 Is there a legal obligation for respondents to reply?

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?	Yes
2.4.4 If yes, for which fruit tree types?	Apple trees
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.	Jonathan 76,9 ha Topaz 72,8 ha Rubinola 38,8 ha Spartan 27,9 ha Melodie 27,2 ha Ontario 25,2 ha Prima 24,6 ha
2.4.6 Other dessert pears n.e.c.
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?	None

2.8. Coverage - Time

2012-

2.9. Base period

not applicable

3. Statistical processing

Top

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"	0
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"	1
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
3.1.8 Name of Organisation responsible
3.1.9 Main scope
3.1.10 Target fruit tree types
3.1.11 List used to build the frame
3.1.12 Any possible threshold values
3.1.13 Population size
3.1.14 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 3.1 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	Register ovocných sadov / Orchards register
3.1.32 Name of Organisation responsible	Ústredný kontrolný a skúšobný ústav poľnohospodársky (ÚKSÚP) / Central Control and Testing Institute in Agriculture
3.1.33 Contact information (email and phone)	ÚKSÚP, Bratislava Matúškova 21 813 66 Bratislava Phone: +421 2 59 880 200 Email: uksup@uksup.sk
3.1.34 Main administrative scope	Register of orchards
3.1.35 Target fruit tree types	Dessert apple trees
3.1.36 Geospatial Coverage	National
3.1.37 Update frequency	Annual
3.1.38 Legal basis	National legislation - Act No. 597/2006 on the competence of the state administration authorities in the field of registration of varieties of cultivated plants and marketing of propagating material of cultivated plants
3.1.39 Are you able to access directly to the micro data?	No
3.1.40 Are you able to check the plausibility of the data, namely by contacting directly the units?	Yes
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?	Good
3.1.42 Please list the main differences between the administrative source and the statistical definitions and concepts	Differences are described bellow (see points 3.1.43 , 3.1.44 and 3.1.45)
3.1.43 Is a different threshold used in the administrative source and statistical data?	Yes
3.1.44 If Yes, please specify	According to the national law (Act No 597/2006) there is an obligation for orchard users to register the orchard with the area at least 0,3 ha. In the statistical survey (questionnaire "Osev") are collected the data on the orchards with area at least 0,15 ha.
3.1.45 Additional comments	Since 2009 the Statistical Office of the Slovak Republic does not collect the data on the orchards. The register of orchards has been established on the basis of results of the statistical surveys from the year 2008. The statistical data and data from the registered are compared twice a year (after sowing and harvest). Based on these comparisons, the Statistical Office of the Slovak Republic and ÚKSÚP exchange information on data quality.

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

Every 5 years

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
3.3.2 Methods of data collection
3.3.3 If Other, please specify
3.3.4 If face-to-face or telephone interview, which method is used?
3.3.5 Data entry method, if paper questionnaires?
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	Register ovocných sadov / Orchards register
3.3.16 Extraction date	November 2017
3.3.17 How easy is it to get access to the data?	Access granted upon a simple request
3.3.18 Data transfer method	Data transferred by FTP (file transport protocol).
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

3.4. Data validation

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

3.5. Data compilation

3.5.1 Describe the data compilation process

After extraction data on orchards from the register and obtaining data from the statistical surveys (annual survey Poľ 18-01 on crop production and livestock numbers and annual survey Osev 3-01 on sown areas by agricultural crops as of 20 May performed by the Statistical Office of the Slovak Republic) are both data sources compared. Next step is to confirm the data and find differences between register and statistical data. In some cases, it is necessary to contact directly the survey unit (orchards user) to definitively eliminate the problems.

3.5.2 Additional comments

3.6. Adjustment

Not applicable.

4. Quality management

Top

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?	ISO 9001
4.1.3 Has a peer review been carried out?	Yes
4.1.4 If Yes, which were the main conclusions?	To develop a comprehensive conceptual material on the acquisition, management and use of the administrative sources while respecting the requirements of the Code of Practice, as amended by the QAF, with an emphasis on reducing the burden on respondents. To analyze variables from statistical surveys to replace data with data from administrative sources. To propose framework agreements on provision of administrative sources with all administrative sources providers.
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	Stable
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

5. Relevance

Top

5.1. Relevance - User Needs

5.1.1 If certain user needs are not met, please specify which and why	There are no user needs unmet.
5.1.2 Please specify any plans to satisfy needs more completely in the future	No plans.
5.1.3 Additional comments

5.2. Relevance - User Satisfaction

5.2.1 Has a user satisfaction survey been conducted?	No
If Yes, please answer all the following questions
5.2.2 Year of the user satisfaction survey
5.2.3 How satisfied were the users?
5.2.4 Additional comments

5.3. Completeness

5.3.1 Data completeness - rate	100 %
5.3.2 If not complete, which characteristics are missing?
5.3.3 Additional comments

6. Accuracy and reliability

Top

6.1. Accuracy - overall

6.1.1 How good is the accuracy?	Good
6.1.2 What are the main factors lowering the accuracy?	Other
6.1.3 If Other, please specify	At the time of the preparation of the file with orchards data we found in the Register small area of 12 ha, which was not removed from the Register.
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
Over-coverage
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope?
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?
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?
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
Misclassification
6.3.1.11 Impact on the data quality
Common units
6.3.1.12 Common units - proportion
6.3.1.13 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
6.3.1.14 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	Register ovocných sadov / Orchards register
Over-coverage
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope?	No
6.3.1.29 What methods are used to detect the out-of scope units?	Mutual comparison between administrative sources and statistical surveys.
6.3.1.30 Does the administrative source include units that do not exist in practice?	Yes
6.3.1.31 Over-coverage - rate
6.3.1.32 Impact on the data quality	Low
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey?	Yes
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	None
Misclassification
6.3.1.37 Impact on the data quality	None
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
6.3.2.2 Is the questionnaire based on usual concepts for respondents?
6.3.2.3 Number of censuses already performed with the current questionnaire?
6.3.2.4 Preparatory testing of the questionnaire?
6.3.2.5 Number of units participating in the tests?
6.3.2.6 Explanatory notes/handbook for surveyors/respondents?
6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents?
6.3.2.8 Are there pre-filled questions?
6.3.2.9 Percentage of pre-filled questions out of total number of questions
6.3.2.10 Other actions taken for reducing the measurement error?
6.3.2.11 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
6.3.2.12 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
6.3.3.2 Unit non-response - rate
6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context?
6.3.3.4 Measures taken for minimising the unit non-response
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate
6.3.3.7 Item non-response rate - Minimum
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
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

Not applicable

6.4. Seasonal adjustment

Not applicable

6.5. Data revision - policy

The official data revison policy is laid down in the Decision of the President of the Statistical Office of the SR issuing the revision policies of the Statistical Office of the SR. It describes the reasons for revisions, type of revisions, calendar of revisions and dividing of revisions by the statistical domains.

6.6. Data revision - practice

6.6.1 Data revision - average size	There is no data revision.
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?	No revision.
6.6.4 How do you evaluate the impact of the revisions?	Not important
6.6.5 Additional comments

7. Timeliness and punctuality

Top

7.1. Timeliness

7.1.1 When were the first results for the reference period published?	We do not plan to publish first results.
7.1.2 When were the final results for the reference period published?	We do not plan to publish final results of this particular orchards survey. The data on orchards are regularly published at the web site of UKSUP and in publications of the Statistical Office of the Slovak Republic. In case of interest from the side of users we can prepare final output concerning orchards in the requested structure.
7.1.3 Reasons for possible long production times?

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?	The results of the orchard survey are not in the Release Calendar.
7.2.4 Number of days between the national release date of data and the target date	0

8. Coherence and comparability

Top

8.1. Comparability - geographical

To be assessed by Eurostat

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable

8.2. Comparability - over time

8.2.1 Length of comparable time series	from 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

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
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

8.3.4 If no comparisons have been made, explain why

8.3.5 Additional comments

We are not able to make comparison by the fruit species. As regards the Annual Crop statistics or FSS 2016, we have at our disposal only the total areas of orchards without any classification by the fruit species.

8.4. Coherence - sub annual and annual statistics

Not applicable

8.5. Coherence - National Accounts

Not applicable

8.6. Coherence - internal

Not applicable

9. Accessibility and clarity

Top

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?
9.2.3 Do you produce an electronic publication?	No
9.2.4 If Yes, is there an English version?
9.2.5 Please provide a link

9.3. Dissemination format - online database

9.3.1 Data tables - consultations	None
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
9.6.3 Are methodological papers available?	No
9.6.4 Please provide a link
9.6.5 Is a handbook available?	Yes
9.6.6 Please provide a link	https://circabc.europa.eu/sd/a/b8afa138-c1bd-4b3b-9557-3a9e0a130b4b/Orchards_Handbook_2017.pdf

9.7. Quality management - documentation

9.7.1 Metadata completeness - rate	There is no metadata available.
9.7.2 Metadata - consultations	None
9.7.3 Is a quality report available?	No
9.7.4 Please provide a link

10. Cost and Burden

Top

10.1 Efficiency gains if compared to the previous quality report	Increased use of administrative data
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report	Easier data transmission
10.4 If Other, please specify

11. Confidentiality

Top

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	The Statistical Office of the SR has adopted its own Directive on the protection of confidential statistical data, where the issue of confidentiality is described in detail.

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination	The Statistical Office of the Slovak Republic usually uses 2 rules: 1. Minimum Frequency Rule - the cell is sensitive if the number of reporting units responding to it is less than a predetermined value (3); 2. Rule p% - the cell is sensitive if any respondent contributing to it estimates the value of another respondent's contribution in that cell with an error less than p%.
11.2.2 Additional comments

12. Comment

Related metadata

Annexes