Orchard (orch)

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

Compiling agency: Statistical Service of Cyprus (CYSTAT)

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

Statistical Service of Cyprus (CYSTAT)

1.2. Contact organisation unit

Agricultural Statistics

1.5. Contact mail address

Michalaki Karaoli Street, 1444 Nicosia, Cyprus

2. Statistical presentation

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2.1. Data description

Main characteristics

2.1.1 Describe shortly the main characteristics of the statistics	For the purpose of the orchard statistics 2017, the structural orchard statistics provide information on the area, age and density of apple, pear, peach, nectarine, apricot, citrus fruit and olive orchards. The statistics are collected from a sample survey.
2.1.2 Which of the fruit tree types are covered by the data collection?	Dessert apple trees Dessert pear trees Apricot trees Dessert peach and nectarine trees Orange trees Small citrus fruit trees Lemon trees Olive 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)	SEPTEMBER 2017-DECEMBER 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?	Yes

Additional comments on data description

The Survey on Fruit and Olive plantations 2017 was carried out in Cyprus based on the Regulation No 1337/2011 of the European Parliament and of the Council.

The legal basis for the conduct of all Statistical Surveys carried out by CYSTAT, is the National Statistics Law of 2000.
The law is very explicit in terms of the obligation of agricultural holders in providing the requested information. (Statistics Law No 15(I) 2000). The Law specifies the following:
Article 11.(2) The officers or the other persons referred to in subsection (1) have the obligation to inform the person from whom the provision of data is required about the conduct of a survey or work by virtue of Law, the purpose of the survey or work, statistical confidentiality and the penalties imposed in case of refusal of provision of data or of provision of false data, incomplete or inaccurate data.
Article 11.(3) Any person who refuses to provide data or who provides false, incomplete or inaccurate data is guilty of an offence and in case of conviction is liable to a fine not exceeding one thousand pounds or to imprisonment not exceeding six months or to both such fine and imprisonment.

2.2. Classification system

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

2.3. Coverage - sector

The survey covers all agricultural holdings with utilised agricultural area used for the cultivation of permanent crops.

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 Pear trees Peach and nectarine 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.
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

The statistical unit is represented by the agricultural holding with utilised agricultural area used for the cultivation of permanent crops, producing entirely or mainly for the market.

2.6. Statistical population

All the agricultural holdings growing permanent crops entirely or mainly for the market, which are included in the Agricultural Register of the Statistical Service.

2.7. Reference area

2.7.1 Geographical area covered	The data refer to agricultural activities in the Goverment controlled area of the Republic of Cyprus.
2.7.2 Which special Member State territories are included?

2.8. Coverage - Time

Results of the Orchard survey are available for 2007 based on the Directive 2001/109/EC and for years 2012 and 2017 based on the Regulation (EU) No 1337/2011.

2.9. Base period

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"	0
3.1.3 Total number of sources of the type "Sample survey"	1
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
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	SURVEY ON FRUIT AND OLIVE PLANTATIONS
3.1.16 Name of Organisation responsible	STATISTICAL SERVICE OF CYPRUS
3.1.17 Main scope	The main scope of the survey is to provide data on the area, age and density of apple, pear, peach, nectarine, apricot, citrus fruit and olives.
3.1.18 Target fruit tree types	Dessert apple trees Dessert pear trees Apricot trees Dessert peach and nectarine trees Orange trees Small citrus fruit trees Lemon trees Olive trees
3.1.19 List used to build the frame	The Agricultural Register, which was created from the Agricultural Census 2010 and was updated based on the surveys that occurred between 2010 and 2016. A list frame was used including all holders, based on the holding’s identification number.
3.1.20 Any possible threshold values
3.1.21 Population size	The total number of holdings was 30257.
3.1.22 Sample size	The sample taken was 26586 holdings
3.1.23 Sampling basis	Area
3.1.24 If Other, please specify
3.1.25 Type of sample design	Stratified
3.1.26 If Other, please specify
3.1.27 If Stratified, number of strata	3 strata
3.1.28 If Stratified, stratification criteria	Unit specialization
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

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	SURVEY ON FRUIT AND OLIVE PLANTATIONS
3.3.9 Methods of data collection	Telephone interview
3.3.10 If Other, please specify
3.3.11 If face-to-face or telephone interview, which method is used?	Paper questionnaire
3.3.12 Data entry method, if paper questionnaires?	Manual
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

3.4. Data validation

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

3.5. Data compilation

3.5.1 Describe the data compilation process

The questionnaire for the Survey on fruit and olive plantations 2017 was designed based on the characteristics as these are set by the Commission Regulation (EC) No. 1337/2011. The Handbook was also used in order to define the characteristics included in the questionnaire. Then the training of the employees took place and each person was given clear instructions relating to their duties and responsibilities. After the sample was taken, the enumerators were responsible for collecting and filling the questionnaires and the checkers would then perform checks on each questionnaire. After the completion and checking of the questionnaires, there was the data entry process, which was monitored and checked weekly for errors, missing items, changes and any inaccuracies in general. By the end of the survey and the finalization of the data, all errors were eliminated. Then data are analyzed using several tools of the Access program. The different tables are extracted, analyzed again and are finalized using Excel. Finally, all tables are filled in with the results of the survey and are send to Eurostat through eDamis.

3.5.2 Additional comments

3.6. Adjustment

No adjustments were made.

4. Quality management

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4.1. Quality assurance

4.1.1 Is there a quality management system used in the organisation?	No
4.1.2 If yes, how is it implemented?
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	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

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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 user needs are met.
5.1.2 Please specify any plans to satisfy needs more completely in the future
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

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6.1. Accuracy - overall

6.1.1 How good is the accuracy?	Very good
6.1.2 What are the main factors lowering the accuracy?	Coverage error Measurement error Non-response error Sampling 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

SURVEY ON FRUIT AND OLIVE PLANTATIONS

6.2.2 Methods used to assess the sampling error

Relative standard error

6.2.3 If Other, please specify

6.2.4 Methods used to derive the extrapolation factor

Basic weight

6.2.5 If Other, please specify

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

The standard error for each variable is estimated by:

Se = √Σ^H_i=1 N_hi (W_hi - 1) S²_i

where:

N_hi is the total number of holdings in stratum i
W_hiis the weight of each holding in stratum i and
S²_i is the variance within stratum i

6.2.7 Sampling error - indicators

Please provide the coefficients of variation in %

	CV (%)
Dessert apple trees	1.5%
Apple trees for industrial processing
Dessert pear trees	1.9%
Pear trees for industrial processing
Apricot trees	1.8%
Dessert peach and nectarine trees	2%
Peach and nectarine trees for industrial processing (including group of Pavie)
Orange trees	2.7%
Small citrus fruit trees	0.9%
Lemon trees	1.2%
Olive trees	0.6%
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	SURVEY ON FRUIT AND OLIVE PLANTATIONS
Over-coverage
6.3.1.15 Does the sample frame include wrongly classified units that are out of scope?	Yes
6.3.1.16 What methods are used to detect the out-of scope units?	Coverage was limited to interviewing the holders who appeared in the sample. This implies that there could be no over-coverage. However, 618 cases no longer belonged to the target population leading to an over-coverage rate of 2.3%. These 618 units were holdings with ceased activities because of two main reasons. First reason is that they changed the use of the holding in the sense that the land was no longer agricultural but became land plots for building and last the agricultural activities were abandoned. These cases led to an insignificant over-coverage error. However, the cases were subtracted from the frame and the weights were recalculated.
6.3.1.17 Does the sample frame include units that do not exist in practice?	No
6.3.1.18 Over-coverage - rate	2.3%
6.3.1.19 Impact on the data quality	None
Under-coverage
6.3.1.20 Does the sample frame include all units falling within the scope of this survey?	No
6.3.1.21 If Not, which units are not included?	The large volume of information that was provided from the farm register assisted in minimizing the number of cases lost. From the initial sample taken from the register, 71 cases were not possible to be included because they were new units, because of real birth or demergers.
6.3.1.22 How large do you estimate the proportion of those units? (%)	This leads to a statistically insignificant under-coverage rate of 0.3%.
6.3.1.23 Impact on the data quality	None
Misclassification
6.3.1.24 Impact on the data quality	None
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
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	SURVEY ON FRUIT AND OLIVE PLANTATIONS
6.3.2.13 Is the questionnaire based on usual concepts for respondents?	Yes
6.3.2.14 Number of surveys already performed with the current questionnaire?	2
6.3.2.15 Preparatory testing of the questionnaire?	No
6.3.2.16 Number of units participating in the tests?
6.3.2.17 Explanatory notes/handbook for surveyors/respondents?	Yes
6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents?	No
6.3.2.19 Are there pre-filled questions?	No
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?	When cases of measurement errors were found, they were corrected at the very moment they were found, therefore by the end of the survey the measurement errors in the data were minimized. Errors were checked by checking the data against the prior information available in the existing register and in many cases by contacting the holder again through the telephone. Follow-up interviews were carried out during the data collection process in those cases where the checking process suggested that these should be done.
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	SURVEY ON FRUIT AND OLIVE PLANTATIONS
6.3.3.12 Unit non-response - rate	1.5%
6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context?	Very low
6.3.3.14 Measures taken for minimising the unit non-response	Follow-up interviews Reminders Weighting
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	Not applicable
6.3.3.18 Item non-response rate - Maximum	Not applicable
6.3.3.19 Which items had a high item non-response rate?
6.3.3.20 Additional comments	Non-response is measured as the agricultural holdings that did not provide any information (i.e. the holder was too busy or refused to give information, the holder was unable to give information because of illness or the holder was abroad during the survey period). Hence, non response does not apply to items included in the survey, but to the whole questionnaire.

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	SURVEY ON FRUIT AND OLIVE PLANTATIONS
6.3.4.7 Imputation - rate	Not available
6.3.4.8 Imputation - basis	Same unit in previous data Other sources
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

A data revision policy is in place at CYSTAT. It is published on CYSTAT’s website, at the following link:

http://www.mof.gov.cy/mof/cystat/statistics.nsf/dissemination_en/dissemination_en?OpenDocument

CYSTAT also publishes a list of scheduled revisions (regular or major revisions), also published on its website.

In the case of the SURVEY ON FRUITS AND OLIVE PLANTATIONS, no revisions are made.

Annexes:
Revision Policy of CYSTAT

6.6. Data revision - practice

6.6.1 Data revision - average size	No revisions were made
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions) carried out since the last quality report?
6.6.3 What was the main reason for the revisions?
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?	10/8/2018
7.1.2 When were the final results for the reference period published?	10/8/2018
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?	Results of the Survey on Fruit and olive plantations are not posted in the website of CYSTAT but they are available upon request.
7.2.4 Number of days between the national release date of data and the target date

8. Coherence and comparability

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8.1. Comparability - geographical

To be assessed by Eurostat

8.1.1. Asymmetry for mirror flow statistics - coefficient

8.2. Comparability - over time

8.2.1 Length of comparable time series	This kind of data are available for the years 2007, 2012 and 2017
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	-10,30%	-12,18%
Apple trees for industrial processing
Dessert pear trees	-0,21%	-10,32%
Pear trees for industrial processing
Apricot trees	-10,15%	-14,69%
Dessert peach and nectarine trees	-12,88%	-15,83%
Peach and nectarine trees for industrial processing (including group of Pavie)
Orange trees	-4,92%	-7,07%
Small citrus fruit trees	-11,13%	-26,29%
Lemon trees	-22,17%	-27,92%
Olive trees	1,66%	1,68%
Table grape vines

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?
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	Not applicable
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?	No
9.6.6 Please provide a link

9.7. Quality management - documentation

9.7.1 Metadata completeness - rate	Not applicable
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 Further training
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report	Multiple use of the collected data Easier data transmission
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?	No
11.1.2 If yes, are they confidential in the sense of Reg. (EC) 223/2009?
11.1.3 Describe the data confidentiality policy in place	Official statistics are released in accordance to all confidentiality provisions of the following: National Statistics Law No. 15(I) of 2000 (especially Article 13 on statistical confidentiality). Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendments (especially Chapter 5 on statistical confidentiality). European Statistics Code of Practice (especially Principle 5 on statistical confidentiality). CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.

Annexes:
Statistics Law No. 15(I) of 2000
REGULATION (EC) No 223/2009 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL
European Statistics Code of Practice
Code of Practice for the Collection, Publication and Storage of Statistical Data

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination	ONLY aggregated tables are published. The treatment of confidential data is regulated by CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data. Data tables are send through Edamis and present total values for all Cyprus and do not include row data in order to ensure confidentiality.
11.2.2 Additional comments

12. Comment

Related metadata

Annexes