Orchard (orch)

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

Compiling agency: Statistical Office of the Republic of SloveniaLitostrojska cesta 54SI-1000 Ljubljana+ 386 1 234 07 49www.stat.si


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 Top
1.1. Contact organisation

Statistical Office of the Republic of Slovenia
Litostrojska cesta 54
SI-1000 Ljubljana
+ 386 1 234 07 49
www.stat.si
1.2. Contact organisation unit

Statistical Office of the Republic of Slovenia
Environmental Statistics
Agriculture, Forestry, Fishing and Hunting Statistics Department
Litostrojska cesta 54
SI-1000 Ljubljana
+ 386 1 234 07 49
www.stat.si
1.5. Contact mail address

Litostrojska cesta 54
SI-1000 Ljubljana


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
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)


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)? Yes
2.4.2 If Yes, please specify the items and the differences

In principal all fruits are produced for fresh consumption, so all areas are included in the dessert fruit areas. After the harvest the product quality and market conditions determine the usage of fruits.
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.
TOPAZ
GLOSTER
CARJEVIČ
MUTSU
LAFLAMBOYANTE
OPAL
DALINBEL   
BOBOVEC
SUMMERRED
DELCORF DELBARESTIVALE
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?
2.8. Coverage - Time

2007-2017
2.9. Base period


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 of Agricurtural holdings

3.1.32 Name of Organisation responsible

Ministry of Agriculture, Forestry and Food
3.1.33 Contact information (email and phone)
3.1.34 Main administrative scope

Register was established among others needs for The Agency of the Republic of Slovenia for Agricultural Markets and Rural Development (body of the ministry), for the implementation of programs of the agricultural policy reform, alignment to the EU common agricultural policy and payment of SAPARD pre-accession assistance. Since May 2004 has a role of a paying agency for EAGGF funds. Register is also part of Integrated Administration and Control System (IACS).
3.1.35 Target fruit tree types  Dessert apple trees
Olive trees
Dessert pear trees
Apricot trees
Dessert peach and nectarine trees
Orange trees
Small citrus fruit trees
Lemon trees
Table grape vines
Other
3.1.36 Geospatial Coverage National
Regional
3.1.37 Update frequency Continuous
3.1.38 Legal basis

OJ of the Republic of Slovenia No. 04/02 and No. 27/04

OJ of the Republic of Slovenia No. 53/03
3.1.39 Are you able to access directly to the micro data? Yes
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? Very good
3.1.42 Please list the main differences between the administrative source and the statistical definitions and concepts

In register are included producers below production threshold.
3.1.43 Is a different threshold used in the administrative source and statistical data? Yes
3.1.44 If Yes, please specify

In register are included agricultural holdings with minimum 0.2 ha of orchard plantations, or 0.1 ha of stone fruits (walnuts, hazelnuts, almonds, chestnust, pistachio). 
3.1.45 Additional comments

Register of Agricurtural holdings covering:

  • Register of producers and plantations of fruit trees with Rules on register of producers in plantations of fruit trees (OJ of the Republic of Slovenia No. 04/02 and No. 27/04)

  • Register of olive producers with Rules on register of olive producers (OJ of the Republic of Slovenia No. 53/03)

 


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 of Agricurtural holdings (including Register of producers and plantations of fruit trees and Register of olive producers)
3.3.16 Extraction date

01.06.2017
3.3.17 How easy is it to get access to the data? Direct constant access
3.3.18 Data transfer method

Data are extracted from administrative source.
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
Aggregates
Outliers
3.4.3 If Other, please specify
3.5. Data compilation
3.5.1 Describe the data compilation process

Data are extracted from administrative source Register of Agricurtural holdings:

  • Register of producers and plantations of fruit trees with Rules on register of producers in plantations of fruit trees (OJ of the Republic of Slovenia No. 04/02 and No. 27/04)

  • Register of olive producers with Rules on register of olive producers (OJ of the Republic of Slovenia No. 53/03)

 

 

Both registers cover data on:

1- agricultural holder

2- agricultural holding

3- plantations of fruit trees and olives:

            a) land use

            - ID number of agricultural holding

            - ID number of plantation

            - location (plot and cadastral community)

            - numbers of parcels

            - gross and net area

            - method of producing

            - hail protection

            - irrigation

            b) technological characteristics

            - fruit and olive species and varieties

            - number of seedlings

            - rootstock

            - planting year

            - planting distance

            - system of planting

            - training system
3.5.2 Additional comments
3.6. Adjustment

The time series has not been adjusted.


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?

In SURS we use a special program, when editing the data (SOP - Statistical data processing). The processes are efficient, repeatable, and the processes assures traceability (metadata is stored in database).
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? Improve data validation
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


5. Relevance Top
5.1. Relevance - User Needs
5.1.1 If certain user needs are not met, please specify which and why

Data on lower teritorial units.
5.1.2 Please specify any plans to satisfy needs more completely in the future

none
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? 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
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 of Agricurtural holdings (including Register of producers and plantations of fruit trees and Register of olive producers)
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?
6.3.1.30 Does the administrative source include units that do not exist in practice? No
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? No
6.3.1.34 If Not, which units are not included?

Producers of fruit from extensive orchards, which produces fruits for market.
6.3.1.35 How large do you estimate the proportion of those units? (%)

less than 5%
6.3.1.36 Impact on the data quality Low
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 relevant.
6.4. Seasonal adjustment

Data were not seasonal adjusted.
6.5. Data revision - policy

https://www.stat.si/dokument/5299/RevisionOfStatisticalDataMEgeneral.pdf
6.6. Data revision - practice
6.6.1 Data revision - average size

The data has not been revised.
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?
6.6.4 How do you evaluate the impact of the revisions?
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?

May 2018
7.1.2 When were  the final results for the reference period published?

May 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)? Yes
7.2.2 If Yes, were data released on the target date? Yes
7.2.3 If No, reasons for delays?
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
8.2. Comparability - over time
8.2.1 Length of comparable time series

The statistics are comparable from 2007.
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
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  0%    0%  
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  0%   0%   
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

The results were checked and compared with previous surveys and other surveys conducted by SURS. A comparison was made with other sources at macro-data level. The data is comparable and all minor differences can be explained.
8.5. Coherence - National Accounts

The results were not checked and compared with National Accounts.
8.6. Coherence - internal

The results were checked and compared with previous surveys and other surveys conducted by SURS. A comparison was made with other sources at macro-data level. The data is comparable and all minor differences can be explained.


9. Accessibility and clarity Top
9.1. Dissemination format - News release
9.1.1 Do you publish a news release? Yes
9.1.2 If Yes, please provide a link

https://www.stat.si/StatWeb/en/News/Index/7390
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? Yes
9.2.4 If Yes, is there an English version? Yes
9.2.5 Please provide a link

https://www.stat.si/StatWeb/en/News/Index/7390
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? Yes
9.3.3 Please provide a link

http://pxweb.stat.si/pxweb/Database/Environment/15_agriculture_fishing/04_crop_production/04_15P65_orchard_census_2012/04_15P65_orchard_census_2012.asp
9.4. Dissemination format - microdata access
9.4.1 Are micro-data accessible to users? Yes
9.4.2 Please provide a link

https://www.stat.si/StatWeb/en/StaticPages/Index/For-Researchers
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? Yes
9.6.4 Please provide a link

https://www.stat.si/StatWeb/en/Methods/QuestionnairesMethodologicalExplanationsQualityReports
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

100%
9.7.2 Metadata - consultations
9.7.3 Is a quality report available? Yes
9.7.4 Please provide a link

Quality report is available only in Slovene: https://www.stat.si/statweb/Methods/QuestionnairesMethodologicalExplanationsQualityReports


10. Cost and Burden Top
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 Multiple use of the collected data
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

All data, from which individual holding can be recognised, are protected.
11.2. Confidentiality - data treatment
11.2.1 Describe the procedures for ensuring confidentiality during dissemination

p% rule
11.2.2 Additional comments


12. Comment Top


Related metadata Top


Annexes Top
ESQRS_ANNEX_SI