Crop production (apro_cp)

National Reference Metadata in ESS Standard for CROPS Reports Structure (ESQRSCP)

Compiling agency: Statistical Office of the Slovak Republic

Time Dimension: 2016-A0

Data Provider: SK1

Data Flow: CROPROD_ESQRSCP_A


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: EUROPEAN STATISTICAL DATA SUPPORT

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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

Statistical Office of the Slovak Republic

Miletičova 3

824 67 Bratislava

Slovak Republic


2. Statistical presentation Top
2.1. Data description

Annual crop statistics provide statistics on the area under main arable crops, vegetables and permanent crops and production and yield levels.  The statistics are collected from  a wide variety of sources: surveys, administrative sources, experts and other data providers. The data collection covers early estimates (before the harvest) and the final data. Data are collected at regional level, the lowest level is NUTS 4.

2.2. Classification system

The natiaonal classifier - Hierarchical crop classification system

2.3. Coverage - sector

Growing of non-perennial crops, perennial crops and plant propagation (NACE A01.1-01.3)

2.4. Statistical concepts and definitions

See: Annual crop statistics Handbook

2.5. Statistical unit

Utilised agricultural area cultivated by an agricultural holding.

2.6. Statistical population

All agricultural holdings growing crops.

2.7. Reference area

The entire territory of the country.

2.8. Coverage - Time

Crop year.

2.9. Base period

Not applicable.


3. Statistical processing Top
3.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous Quality Report (2014)?  NO      
If yes, which new data sources have been introduced since the previous quality report (2014)?
Type of source?
To which Table (Reg 543/2009) do they contribute?
Have some data sources been dropped since the previous Quality Report (2014)? NO      
Which data sources have been dropped since the previous quality report (2014)?
Type of source?
Why have they been dropped?
Additional comments


Data sources: Please indicate the data sources which were used for the reference year 2016

  Type Name(s) of the sources If other type, which kind of data source?
Table 1: crops from arable land      
Early estimates for areas Census
Survey

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Pol 6-01 - Questionnaire on estimated yields on selected crop as of 20th of June

Pol 8-01 - Questionnaire on estimated yields on selected crop as of 15th of August

Pol 9-01 - Questionnaire on estimated yields on selected crop as of 15th of September

Final area under cultivation Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Production Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Yield Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Non-existing and non-significant crops
Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Final harvested area Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Production Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Non-existing and non-significant crops
Table 3: Permanent crops      
Early estimates for production area Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Final production area Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Production Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Non-existing and non-significant crops
Table 4: Agricultural land use      
Main area Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Non-existing and non-significant crops Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Total number of different data sources

5

   
Additional comments

Data source for the humidity

Put x, if used

Surveyed: farmers report the humidity

 

Surveyed: farmers convert the production/yield into standard humidity     

 

Surveyed: whole sale purchasers report the humidity

 

Surveyed: whole sale purchasers convert the production/yield into standard humidity     

 

Surveyed by experts (e.g. test areas harvested and measured)

 

Estimated by experts

 

Other type

 X

If other type, please explain

 Slovak Technical Standard for humidity of crops wich is equal to Eurostat standards

Additional information

 

   


Which method is used for calculating the yield for main arable crops? Production divided by sown area
production divided by harvested area
If another method, describe it.

For estimates of yield we calculate the yield by using the sown area.

For definitive yield we calculate the yield by using the harvested area.

3.2. Frequency of data collection

  Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Source 7 Source 8 Source 9
Name of data source

Osev 3-01

Pol 6-01

Pol 8-01

Pol 9-01

Pol 18-01

Planning (month-month/year)

February/2016

February/2016

February/2016

February/2016

February/2016

Preparation (month-month/year)

March-July/2016

March-July/2016

March-July/2016

March-July/2016

March-July/2016

Data collection (month-month/year)

May-June/2016

June/2016

August/2016

September/2016

December/2016-February 2017

Quality control (month-month/year)

May-June/2016

June/2016

August/2016

September/2016

January/February 2017

Data analysis (month-month/year)

June/2016

June/2016

August/2016

September/2016

January/February 2017

Dissemination (month-month/year)

July/2016

July/2016

August/2016

September/2016

March/2017

If there were delays, what were the reasons?

No relevant

No relevant

No relevant

No relevant

No relevant

3.3. Data collection

Definitions

  Question In case yes, how do they differ?
Do national definitions differ from the definitions in Article 2 of Regulation (EC) No 543/2009? NO
Are there differences between the national methodology and the methodology described in the Handbook concerning e.g. the item and aggregate calculations? NO
Are special estimation/calculation methods used for main crops from arable land? NO
Are special estimation/calculation methods used for vegetables or strawberries? NO
Are special estimation/calculation methods used for permanent crops for human consumption? NO
Are special estimation/calculation methods used for main land use? NO
Do national crop item definitions differ from the definitions in the Handbook  (D-flagged data)? NO  
In case yes, how do they differ? ( list all items and explanations)
In case data are delivered for one of the items below, describe the crop species included in the item:


Population

Which measures were taken in order to make sure that the requirement stipulated in Art. 3.2 are met?
(Statistics shall be representative of at least 95 % of the areas of each table in the Regulation).

Approved Programme of the State Statistical Surveys for collecting statistical data

Is the data collection based on holdings? YES
If yes, how the holdings were identified? Unique statistical farm identifier
If not, on which unit the data collection is based on?
When was last update of the holding register? (month/year)

Monthly/per year

Was a threshold applied? YES
If yes, size of the excluded area Area excluded on the basis of the threshold in % of the total area for that crop
Cereals for the production of grain (in %)

7,1%

Dried pulses and protein crops (in %)

1,8%

Root crops (in %)

1%

Oilseeds (in %)

3,1%

Other industrial crops (included all industrial crops besides oilseeds)  (in %)

2,8%

Plants harvested green from arable land (in %)

5,7%

Total vegetables, melons and strawberries (in %)

9%

Cultivated mushrooms (in %)
Total permanent crops (in %)

9,8%

Fruit trees (in %)

9,3%

Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)

10,5%

Olive trees (in %)


Survey method (only for census and surveys)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey

Osev 3-01

Pol 6-01

Pol 8-01

Pol 9-01

Pol 18-01

Which survey method was used? On-line electronic questionnaire filled in by respondent
Postal questionnaire filled in by respondent
On-line electronic questionnaire filled in by respondent
Postal questionnaire filled in by respondent
On-line electronic questionnaire filled in by respondent
Postal questionnaire filled in by respondent
On-line electronic questionnaire filled in by respondent
Postal questionnaire filled in by respondent
On-line electronic questionnaire filled in by respondent
Postal questionnaire filled in by respondent
If 'other', please specify
Please provide a link to the questionnaire

Osev 3-01

Poľ 6-01

Poľ 8-01

Poľ 9-01

Poľ 18-01

Data entry method, if paper questionnaires? Manual Manual Manual Manual Manual


Administrative data (This question block is only for administrative data)

  Admin source 1 Admin source 2 Admin source 3 Admin source 4 Admin source 5 Admin source 6
Name of the register
Description
Data owner (organisation)
Update frequency
Reference date (month/year)
Legal basis
Reporting unit
Identification variable (e.g. address, unique code, etc.)
Percentage of mismatches (%)
How were the mismatches handled?
Degree of coverage (holdings, e.g. 80%)
Degree of completeness (variables, e.g. 60%)
If not complete, which other sources were used ?
How were the data used?
Data used for other purposes, which?
Which variables were taken from administrative sources?
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation?
Please describe the differences
What measures were taken to eliminate the differences?
How was the reliability, accuracy and coherence (comparison to other available data) of the data originated from administrative data source (ante- and/or ex-post) checked?
What were the possible limitations, drawbacks of using the data from administrative source(s)?


Expert estimations (This question block is only for expert estimates)

  Expert estimate 1 Expert estimate 2 Expert estimate 3 Expert estimate 4 Expert estimate 5 Expert estimate 6
Name of the estimation
Data owner (organisation)
Update frequency (e.g. 1 year or 6 months)
Reference date (Month/Year  e.g. 1/16 - 8/16)
Legal basis
Use purpose of the estimates?
What kind of expertise the experts have?
What kind of estimation methods were used?
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation?
If yes, please describe the differences
What measures were taken to eliminate the differences?
How were the reliability, accuracy and coherence (comparison to other available data) of the data originated from experts' estimates (ante- and/or ex-post)checked?
What were the possible limitations, drawbacks of using the data from expert estimate(s)?
Additional comments
3.4. Data validation

Which kind of data validation measures are in place? Automatic and Manual
What do they target? Completeness
Outliers
Aggregate calculations
Is the data cross-validated against an other dataset? NO
If yes, which kind of dataset?
If other, please describe
3.5. Data compilation

Not Applicable.

3.6. Adjustment

Not applicable.


4. Quality management Top
4.1. Quality assurance

  Completeness Punctuality Accuracy Reliability Overall quality
How would you describe the overall quality development since 2014? Improvement Stable Stable Stable Improvement
Is there a quality management process in place for crop statistics? YES        
If, yes, what are the components?

communication with reporting units

internal communication within Statistical Office of the SR

controls in IT tools

 

       
Is there a Quality Report available? NO        
If yes, please provide a link(s)        
To which data source(s) is it linked?
       
Has a peer-review been carried out for crop statistics? NO        
If, yes, which were the main conclusions?        
What quality improvement measures are planned for the next 3 years? Other        
If, other, please specify

Use of administrative data

       
Additional comments        
4.2. Quality management - assessment

See the European level Quality Report.


5. Relevance Top
5.1. Relevance - User Needs

Are there known unmet user needs? NO
Describe the unmet needs
Does the Regulation 543/2009 meet the national data needs? YES
Does the ESS agreement meet the national needs? YES
If not, which additional data are collected?
Additional comments
5.2. Relevance - User Satisfaction

Have any user satisfaction surveys been done? NO
If yes, how satisfied the users were?
Additional comments
5.3. Completeness

See the European level Quality Report

5.3.1. Data completeness - rate

See the European level Quality Report


6. Accuracy and reliability Top
6.1. Accuracy - overall

See the European level Quality Report.

6.2. Sampling error

Sampling method and sampling error

  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name

Pol 1-06

Pol 1-08

Pol 1-09

Sampling basis? Area Area Area
If 'other', please specify
Sampling method? Stratified Stratified Stratified
If stratified, number of strata?

8

8

8

If stratified, stratification basis? Location Location Location
If 'other', please specify
Size of total population

5799

5799

5799

Size of sample

753

897

613

Which methods were used to assess the sampling error?  Relative standard error Relative standard error Relative standard error
If other, which?
Which methods were used to derive the extrapolation factor?  Basic weight Basic weight Basic weight
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas

We calculate the standard deviation.

 

Weight:   wi = Ni/ni

Sum:  sum(y)

Average:   y = sum/count

Estimate total: sum*weight

Variance: s2 = sum((y-y)2) / (n-1)

h:         h = (N2/n) * (1-(n/N))

Estimate variance of total:      ROZ = h * s2

Standard error absolute:      SE = sqrt(ROZ)

We calculate the standard deviation.

 

Weight:   wi = Ni/ni

Sum:  sum(y)

Average:   y = sum/count

Estimate total: sum*weight

Variance: s2 = sum((y-y)2) / (n-1)

h:         h = (N2/n) * (1-(n/N))

Estimate variance of total:      ROZ = h * s2

Standard error absolute:      SE = sqrt(ROZ)

 

We calculate the standard deviation.

 

Weight:   wi = Ni/ni

Sum:  sum(y)

Average:   y = sum/count

Estimate total: sum*weight

Variance: s2 = sum((y-y)2) / (n-1)

h:         h = (N2/n) * (1-(n/N))

Estimate variance of total:      ROZ = h * s2

Standard error absolute:      SE = sqrt(ROZ)

 

If the results were compared with other sources, please describe the results
Which were the main sources of errors?


Sampling error - indicators

Not applicable


Coefficient of variation (CV) for the area (on the MS level)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey

Pol 1-06

Pol 1-08

Pol 1-09

Cereals for the production of grain (in %)

1,73

1,94

2,43

Dried pulses and protein crops (in %)
Root crops (in %)

 

0,76

1,26

Oilseeds (in %)

1,7

0,45

2,13

Other industrial crops (included all industrial crops besides oilseeds)  (in %)
Plants harvested green from arable land (in %)

3,76

Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)
Additional comments            
6.3. Non-sampling error
6.3.1. Coverage error

Over-coverage - rate

Not applicable


Common units - proportion

Not applicable


  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source

Pol 1-06

Pol 1-08

Pol 1-09

Pol 18-01

Osev 3-01

Error type
Degree of bias caused by coverage errors
What were the reasons for coverage errors?
Which actions were taken for reducing the error or to correct the statistics?
Additional comments

Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.

Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.

Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.

Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.

Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.




 

6.3.1.1. Over-coverage - rate

Not applicable

6.3.1.2. Common units - proportion

Not applicable

6.3.2. Measurement error

  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source

Pol 1-06

Pol 1-08

Pol 1-09

Pol 1-18

Osev 3-01

Was the questionnaire based on usual concepts for respondents? YES YES YES YES YES
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?

23

23

23

23

23

Preparatory (field) testing of the questionnaire? NO NO NO NO NO
Number of units participating in the tests? 

0

0

0

0

0

Explanatory notes/handbook for surveyors/respondents?  YES YES YES YES YES
On-line FAQ or Hot-line support for surveyors/respondents? NO NO NO NO NO
Were pre-filled questionnaires used? NO NO NO NO NO
Percentage of pre-filled questions out of total number of questions

0

0

0

0

0

Were some actions taken for reducing the measurement error or to correct the statistics? YES YES YES YES YES
If yes, describe the actions and their impact

telephone contact

telephone contact

telephone contact

telephone contact

telephone contact

6.3.3. Non response error

Unit non-response - rate

Not applicable


Item non-response - rate

Not applicable


  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name

Pol 6-01

Pol 8-01

Pol 9-01

Pol 18-01

Osev 3-01

Unit level non-response rate (in %)

0

0

0

1,9

1,6

Item level non-response rate (in %)              
               - Min% / item

0

0

0

0.1

0.1

               - Max% / item

0

0

0

0.1

0.1

               - Overall%

0

0

0

0.1

0.1

Was the non-response been treated ? NO NO NO YES YES
Which actions were taken to reduce the impact of non-response?

not relevant 

not relevant 

not relevant 

Follow-up interviews

Follow-up interviews

Which items had a high item-level non-response rate? 

not relevant

not relevant

not relevant

differently

differently

Which methods were used for handling missing data?
(several answers allowed)
Follow-up interviews Follow-up interviews
In case of imputation which was the basis? Imputation based on other sources Imputation based on other sources
In case of imputation, which was the imputation rate (%)?

0

0

0

<0,1

<0,1

Estimated degree of bias caused by non-response? None None
Which tools were used for correcting the data?

None

None

Which organisation did the corrections?

None

None

Additional comments

In the year of survey all units reply in the census Osev 3-01. We use this opportunity to ask them also for estimation of their production as regards different crops.

In the year of survey all units reply in the census Osev 3-01. We use this opportunity to ask them also for estimation of their production as regards different crops.

In the year of survey all units reply in the census Osev 3-01. We use this opportunity to ask them also for estimation of their production as regards different crops.

6.3.3.1. Unit non-response - rate

Not applicable

6.3.3.2. Item non-response - rate

Not applicable

6.3.4. Processing error

Not applicable.

6.3.4.1. Imputation - rate

Not applicable.

6.3.5. Model assumption error

Not applicable.

6.4. Seasonal adjustment

Not applicable.

6.5. Data revision - policy

Not applicable.

6.6. Data revision - practice

Not applicable.

6.6.1. Data revision - average size

Not applicable.


7. Timeliness and punctuality Top
7.1. Timeliness

Time lag - first result

First result - estimates of yield in the relevant year: 10 - 11 days

 


Time lag - final result

72 days


  Cereals Dried pulses and protein crops Root crops Oilseeds Other industrial crops Plants harvested green Vegetables and melons Strawberries Cultivated mushrooms Fruit trees Berries Nut trees Citrus fruit trees Vineyards Olive trees
How many main data releases there are yearly in the national crop statistics for the following types of crops?

5

3

4

5

2

3

2

2

1

1

1

1

2

How many of them are forecasts (releases before the harvest)?

3

3

1

3

0

1

0

0

0

0

0

0

0

When was  the first  forecasting published for crop year 2016? (day/month/year) 01/07/2016 01/07/2016 26/08/2016 01/07/2016 27/09/2016
When were the final results published for crop year 2016? (day/month/year) 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017 13/03/2017
Additional comments
7.1.1. Time lag - first result

First result - estimates of yield in the relevant year: 10 - 11 days

 

7.1.2. Time lag - final result

72 days

7.2. Punctuality

See the European level Quality Report

7.2.1. Punctuality - delivery and publication

See the European level Quality Report


8. Coherence and comparability Top
8.1. Comparability - geographical

Not applicable.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.

8.2. Comparability - over time

Length of comparable time series

Not applicable


  Crops from arable land
(Table 1)
Vegetables, melons and strawberries (Table 2) Permanent crops
(Table 3)
Agricultural land use
(Table 4)
Have there been major breaks in the time series since 2013? NO NO NO NO
If yes, to which were they related?
If other, which?
Which items were affected?
Year of break (number)
Impact on comparability
Additional comments
8.2.1. Length of comparable time series

Not applicable

8.3. Coherence - cross domain

  Data source
With which other data sources the crop statistics data have been compared?  Farm structure survey 2016
Other
If others, which?

Vineyard survey

If no comparisons have been made, why not?


Results of comparisons FSS 2016 (if available) Vineyard survey 2015 IACS Other source(s)  In case of other sources, which?
Cereals

0,01%

 

 

 

Dried pulses and protein crops

-0,3%

 

 

 

Root crops

-1,03%

 

 

 

Oilseeds

-0,19%

 

 

 

Other industrial crops (than oilseeds)

-0,07%

 

 

 

Plants harvested green

-0,67%

 

 

 

Total vegetables, melons and strawberries

3,07%

 

 

 

Vegetables and melons  
Strawberries  
Cultivated mushrooms  
Total permanent crops  
Fruit trees

 13,25%

 

 

 

Berries  
Nut trees  
Citrus fruit trees  
Vineyards

0,02%

-10,38%

Olive trees  
If there were considerable differences, which factors explain them?

 

 
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

Availability Links
NO
9.2. Dissemination format - Publications

  Availability Links
Publications Electronic
Paper

Publications of the Catalogues

Publications in English None
9.3. Dissemination format - online database

Data tables - consultations

Not applicable


  Availability Links
On-line database accessible to users YES

Slovstat

www.statistics.sk

Website None
National language

www.statistics.sk

9.3.1. Data tables - consultations

Not applicable

9.4. Dissemination format - microdata access

Availability Links
NO
9.5. Dissemination format - other

Free : Archív publikácií

9.6. Documentation on methodology

  Availability Links
Methodological report None
National language

Classifications

Quality Report
Metadata
Additional comments  
9.7. Quality management - documentation

Not applicable.

9.7.1. Metadata completeness - rate

Not applicable.

9.7.2. Metadata - consultations

Not applicable.


10. Cost and Burden Top

Efficiency gains if compared to the previous reference year (2013) Staff further training
If other, which?
Burden reduction measures since the previous reference year  More user-friendly questionnaires
Easier data transmission
Multiple use of the collected data
If other, which?


11. Confidentiality Top
Restricted from publication
11.1. Confidentiality - policy
Restricted from publication
11.2. Confidentiality - data treatment
Restricted from publication


12. Comment Top

Comparison between Annual crop statistics and FSS 2016 is not completed yet.


Related metadata Top


Annexes Top