Crop production (apro_cp)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Poland Statistics


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

Poland Statistics
1.2. Contact organisation unit

Department of Agriculture and Environment
1.5. Contact mail address

00-925 Warsaw, Al. Niepodległości 208, Poland


2. Statistical presentation Top
2.1. Data description

Annual crop statistics provide statistics on main areas, vegetables and permanent crops, as well as production levels and yields. Statistics are collected from many different sources: surveys, administrative sources, experts and other data providers. The dataset includes early estimates (before harvest) and final data. Data are mainly collected at national and regional level (NUTS1/2).
2.2. Classification system

Hierarchical crop classification system
2.3. Coverage - sector

Cultivation of non-perennial plants, perennial plants and plant propagation (NACE A01.1-01.3)
2.4. Statistical concepts and definitions

See: Manual of annual crop statistics
2.5. Statistical unit

Utilised agricultural area cultivated by the holding.
2.6. Statistical population

All farms growing crops.
2.7. Reference area

The entire territory of the country.
2.8. Coverage - Time

Year of harvest.
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?  YES      
If yes, which new data sources have been introduced since the previous quality report?

 

Satellite data

IACS
Type of source? Other Administrative data
To which Table (Reg 543/2009) do they contribute? Table1 Table1
Have some data sources been dropped since the previous quality report? YES      
Which data sources have been dropped since the previous quality report?

Survey
Type of source? Survey
Why have they been dropped?
Additional comments


Data sources: Please indicate the data sources which were used for the reference year on which is reported

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

Estimation of area

  
Final area under cultivation Survey
Administrative data
Expert estimate
Other

 

Agricultural and Food Quality Inspection - Main Inspectorate (GIJHARS)

National Support Centre for Agriculture (KOWR)

Agency for Restructuring and Modernisation of Agriculture (ARMA-IACS)

Estimation of yields of potatoes (R-r-z) Plant Breeding and Acclimatization Institute (IHAR) - National Research Institute 

Estimation of area on individual species of crops

Satellite data
Production Expert estimate

Estimation of production
Yield Expert estimate
Other

Estimation of yields

The Earth observation data
Non-existing and non-significant crops Expert estimate

Estimation of  NSC
Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas Expert estimate

Estimation of area
Final harvested area Administrative data
Expert estimate

GIJHARS

Estimation of area on individual species of crops

 
Production Expert estimate

Estimation of production
Non-existing and non-significant crops Expert estimate

Estimation of  NSC
Table 3: Permanent crops      
Early estimates for production area Expert estimate

Estimation of  NSC
Final production area Administrative data
Expert estimate

GiJHARS

Estimation of area on individual species of crops
Production Expert estimate

Estimation of production
Non-existing and non-significant crops Administrative data
Expert estimate

Estimation of  NSC
Table 4: Agricultural land use      
Main area Administrative data

 

GIJHARS

KOWR

Agency for Restructuring and Modernisation of Agriculture 

 
Non-existing and non-significant crops Administrative data
Expert estimate

Estimation of  NSC
Total number of different data sources

3

  
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

 x

Other type

 

If other type, please explain

 

Additional information

 
   


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




 
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

Administrative Data:

ARMA( Agency of Restructuring and Modernisation of Agriculture)

cultivated area

Assessment of potato yields (R-r-z)

Institute of Plant Breeding and Acclimatization (IHAR) – National Research Institute 

 

Administrative Data:

GIJHARS (Agricultural and Food Quality Inspection - Main Inspectorate)

Administrative Data:

KOWR (National Support Centre for Agriculture)

Expert Estimation

Satellite data
Planning (month-month/year)

not applicable

03.2021-02.2022
 
not applicable

not applicable

03.2021-02.2022

03.2022

 
Preparation (month-month/year) Restricted from publication

02-03.2022

not applicable

not applicable

02-05.2022

03.2022

 
Data collection (month-month/year)

06.2022

04-09.2022

not applicable

not applicable

03-11.2022

04.2022

 
Quality control (month-month/year)

06.2022

not applicable

04-06.2022

not applicable

06-11.2022

not applicable
Data analysis (month-month/year)

06.2022

11.2022

04-06.2022

04.2022

04-12.2022

04.2022
Dissemination (month-month/year)

07.2022

12.2022

04-09.2022

07.2022

04.2022

05.2022
If there were delays, what were the reasons?

not relevant

data on organic farming were delayed

not relevant

not relevant

not applicable






 
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? YES

Poland uses the concept “sown area” (and only in case of huge damages or disasters it could be recalculated). Usually Poland doesn't survey the area after the harvest and the yields are calculated on the basis of the sown area and not the harvested area.
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).

The total cultivated area( satellite data, administrative data)
Is the data collection based on holdings? NO
If yes, how the holdings were identified? Other
If not, on which unit the data collection is based on?

Mostly on parishes (i.e. the smallest administrative units)
When was last update of the holding register? (month/year)

March/2022
Was a threshold applied? NO
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 %)
Dried pulses and protein crops (in %)
Root crops (in %)
Oilseeds (in %)
Other industrial crops (included all industrial crops besides oilseeds)  (in %)
Plants harvested green from arable land (in %)
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 %)


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

 

 

 
Which survey method was used?
If 'other', please specify
Please provide a link to the questionnaire

 
Data entry method, if paper questionnaires?


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

Register of organic farms

Register of farms cultivating hops (area and production)

Register of farms cultivating sugar beet (area and production)

ARMR (Agency for Restructuring and Modernization of Agriculture)
Description

individual data

aggregated data

aggregated data

Aggregated data
Data owner (organisation)

GIJHARS (Agricultural and Food Quality Inspection - Main Inspectorate)

GIJHARS (Agricultural and Food Quality Inspection - Main Inspectorate)

KOWR( National Support Centre for Agriculture)

IACS DATA
Update frequency Once per year or more often Once per year or more often Once per year or more often Once per year or more often
Reference date (month/year)

31.12.2022

31.12.2022

31.12.2022

06.2022
Legal basis
Reporting unit

Farm

NUTS2

NUTS2

Farm
Identification variable (e.g. address, unique code, etc.)
Percentage of mismatches (%)

0%

0%

0%

0%
How were the mismatches handled?
Degree of coverage (holdings, e.g. 80%)

100%

100%

100%

100%
Degree of completeness (variables, e.g. 60%)

100%

100%

100%

100%
If not complete, which other sources were used ?
Were the data used for sample frame? Sample frame
Validation
Directly for estimates		 Directly for estimates Directly for estimates Validation
Directly for estimates
Data used for other purposes, which?
Which variables were taken from administrative sources?

The area of land use and individual crops

The area and production of hops

The area and production of sugar beet

Cultivated area
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation? NO NO NO NO
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?

other data were not available

data were similar

data were similar

The data was similar
What were the possible limitations, drawbacks of using the data from administrative source(s)?

not applicable

not relevant

not relevant

not applicable


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

Autumn assessment on crops condition

Spring assessment on crops condition

First expert estimation - provisional

Second expert estimation - provisional

Third expert estimation - final

Estimation of NSC
Data owner (organisation)

Statistics Poland

Statistics Poland

Statistics Poland

Statistics Poland

Statistics Poland

Statistics Poland
Update frequency (e.g. 1 year or 6 months) Yearly Yearly Yearly Yearly Yearly Yearly
Reference date (Month/Year  e.g. 1/22 - 8/22)

11/2022

05/2022

06/2022-07/2022

08/2022-09/2022

10/2022-11/2022

11/2022- 12/2022
Legal basis

Law issued on 29 June 1995 
on official statistics

and

Regulation of the Council of Ministers of 21 July 2018. on the program of official statistics for 2022

Law issued on 29 June 1995 
on official statistics

and

Regulation of the Council of Ministers of 21 July 2018. on the program of official statistics for 2022

Law issued on 29 June 1995 
on official statistics

Regulation of the Council of Ministers of 21 July 2018. on the program of official statistics for 2022

Law issued on 29 June 1995 
on official statistics

and

Regulation of the Council of Ministers of 21 July 2018. on the program of official statistics for 2022

Law issued on 29 June 1995 
on official statistics

and

Regulation of the Council of Ministers of 21 July 2018. on the program of official statistics for 2022

Law issued on 29 June 1995 
on official statistics

and

Regulation of the Council of Ministers of 21 July 2018. on the program of official statistics for 2022
Use purpose of the estimates?

for Statistics Poland and users needs 

for Statistics Poland and users needs 

for Statistics Poland and users needs 

for Statistics Poland and users needs 

for Statistics Poland and users needs 

for Eurostat needs
What kind of expertise the experts have?

scientific and practical expertise in the field

scientific and practical expertise in the field

practical expertise in the field

practical expertise in the field

practical expertise in the field

scientific and practical expertise in the field
What kind of estimation methods were used?

NUTS2 experts' estimates

NUTS3 experts' estimates

 

NUTS3 experts' estimates

Satellite data

Administrative data

NUTS3 experts' estimates

Satellite data

Administrative data

NUTS3 experts' estimates

satelita estimates

 

using of many different sources of information (for NUTS0)
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation? NO NO YES YES YES
If yes, please describe the differences

e.g. rape and turnip rape together

e.g. rape and turnip rape together

e.g. rape and turnip rape together
What measures were taken to eliminate the differences?

the differences were not significant and they were described in the handbook (in chapter "Country notes")

the differences were not significant and they were described in the handbook (in chapter "Country notes")
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?

other data were not available

other data were not available

Data on yields  originated from experts' estimates were compared with administrative and satellite data. Data on yields from experts' estimates were more representative.  

Data on yields  originated from experts' estimates were compared with administrative and satellite data. Data on yields from experts' estimates were more representative.  
What were the possible limitations, drawbacks of using the data from expert estimate(s)?

Such kind of estimates is appropriate.

Such kind of estimates is appropriate.

The data on area were not accepted from expert estimates because experts had no possibility to assess precisely such kind of data.

The data on area were not accepted from expert estimates because experts had no possibility to assess precisely such kind of data.

The data on area were not accepted from expert estimates because experts had no possibility to assess precisely such kind of data.
Additional comments


 
3.4. Data validation

Which kind of data validation measures are in place? Automatic
What do they target? Completeness
Outliers
Aggregate calculations
Is the data cross-validated against an other dataset? YES
If yes, which kind of dataset? Previous results
Farm Structure Survey
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 the previous quality report?
Is there a quality management process in place for crop statistics? NO        
If, yes, what are the components?        
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? Increase of resources
Systematic validation improvements		        
If, other, please specify        
Additional comments        






 
4.2. Quality management - assessment

See the report on quality at European level.


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?
If not, which additional data are collected?

Assessments on crops condition (autumn and spring)
Additional comments






 
5.2. Relevance - User Satisfaction

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

We try to satisfy users’ needs as they come






 
5.3. Completeness

See the report on quality at European level.
5.3.1. Data completeness - rate

See the report on quality at European level.


6. Accuracy and reliability Top
6.1. Accuracy - overall

See the quality report at European level.
6.2. Sampling error

Sampling method and sampling error

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

 

 

 

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

 

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

 

 

 
Size of sample

 

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

 

 

 

 

 
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

Survey of potatoes yields

(R-r-z)

 

 
Cereals for the production of grain (in %)

Not applicable

 
Dried pulses and protein crops (in %)

Not applicable

 
Root crops (in %)

Potatoes 1,2

 
Oilseeds (in %)

Not applicable

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

Not applicable

 
Plants harvested green from arable land (in %)

Not applicable

 
Total vegetables, melons and strawberries (in %)

Not applicable
Cultivated mushrooms (in %)

Not applicable

 
Total permanent crops (in %)

Not applicable
Fruit trees (in %)

Not applicable
Berries (in %)

Not applicable
Nut trees (in %)

Not applicable
Citrus fruit trees (in %)

No relevant
Vineyards (in %)

No relevant
Olive trees (in %)

No relevant
Additional comments            




 
6.3. Non-sampling error
6.3.1. Coverage error

Over-coverage - rate

 


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

 
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




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

 
Preparatory (field) testing of the questionnaire?
Number of units participating in the tests? 
Explanatory notes/handbook for surveyors/respondents? 
On-line FAQ or Hot-line support for surveyors/respondents?
Were pre-filled questionnaires used?
Percentage of pre-filled questions out of total number of questions
Were some actions taken for reducing the measurement error or to correct the statistics?
If yes, describe the actions and their impact






 
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
Unit level non-response rate (in %)

 

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

 

 

 
               - Max% / item
               - Overall%
Was the non-response been treated ?
Which actions were taken to reduce the impact of non-response?
Which items had a high item-level non-response rate? 
Which methods were used for handling missing data?
(several answers allowed)
In case of imputation which was the basis?
In case of imputation, which was the imputation rate (%)?
Estimated degree of bias caused by non-response?
Which tools were used for correcting the data?
Which organisation did the corrections?
Additional comments




 
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


Time lag - final result


  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?

4

4

4

4

4

4

4

4

4

4
How many of them are forecasts (releases before the harvest)?

2

2

2

2

2

2

2

1

2

1
When was the first  forecasting published for the crop year on which is reported? (day/month/year) 31/07/2022 31/07/2022 31/07/2022 31/07/2022 31/07/2022 31/07/2022 31/07/2022 31/07/2022 31/07/2022 31/07/2022
When were the final results published for the crop year on which is reported? (day/month/year) 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023
Additional comments

No

No

No

No

No

No

No

No

No

No

No

No

No

No




 
7.2. Punctuality

See the Quality Report at European level
7.2.1. Punctuality - delivery and publication

See the Quality Report at European level


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 in the previous 5 years? 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

With which other data sources the crop statistics data have been compared?  None
If others, which?

 
If no comparisons have been made, why not?

Some data and data sources are not comparable or not available  


Differences between ACS and other data sources (%)

Results of comparisons IFS 2020 Vineyard survey 2020 IACS Other source(s)  In case of other sources, which?
Cereals    

Annual crop statistics (ha)
Dried pulses and protein crops    

Annual crop statistics (ha)
Root crops    

Annual crop statistics (ha)
Oilseeds    

Annual crop statistics (ha)
Other industrial crops (than oilseeds)    

Annual crop statistics (ha)
Plants harvested green    

Annual crop statistics (ha)
Total vegetables, melons and strawberries    

Annual crop statistics (ha)
Vegetables and melons    

Annual crop statistics (ha)
Strawberries    

Annual crop statistics (ha)
Cultivated mushrooms

0%

  

Annual crop statistics (ha)
Total permanent crops

0%

  

Annual crop statistics (ha)
Fruit trees

Not applicable.

Annual crop statistics (ha)
Berries  

Annual crop statistics (ha)
Nut trees  

Annual crop statistics (ha)
Citrus fruit trees

Not applicable.
Vineyards
Olive trees

Not applicable.
If there were considerable differences, which factors explain them?

In FFS  fruit trees and bushes from plantations were surveyed separately

 

Between orchard survey and ACS there were some differences in methodology and terms, in orchard survey the population was dedicated to holdings with special fruit production (e.g. apple, peach and apricot production in orchard)  

  





 
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

 

Główny Urząd Statystyczny / Obszary tematyczne / Rolnictwo. Leśnictwo / Uprawy rolne i ogrodnicze / Wstępna ocena przezimowania upraw w 2022 roku

Główny Urząd Statystyczny / Obszary tematyczne / Rolnictwo. Leśnictwo / Uprawy rolne i ogrodnicze / Wiosenna ocena stanu upraw rolnych i ogrodniczych w 2022 roku

Główny Urząd Statystyczny / Obszary tematyczne / Rolnictwo. Leśnictwo / Uprawy rolne i ogrodnicze / Wstępna ocena przezimowania upraw w 2022 roku

Główny Urząd Statystyczny / Obszary tematyczne / Rolnictwo. Leśnictwo / Uprawy rolne i ogrodnicze / Wynikowy szacunek głównych ziemiopłodów rolnych i ogrodniczych w 2022 roku

Główny Urząd Statystyczny / Obszary tematyczne / Rolnictwo. Leśnictwo / Uprawy rolne i ogrodnicze / Wstępna ocena przezimowania upraw w 2022 roku

 
Publications in English Electronic

 

Główny Urząd Statystyczny / Obszary tematyczne / Rolnictwo. Leśnictwo / Uprawy rolne i ogrodnicze / Wynikowy szacunek głównych ziemiopłodów rolnych i ogrodniczych w 2022 roku

 






 
9.3. Dissemination format - online database

Data tables - consultations


  Availability Links
On-line database accessible to users YES

https://bdl.stat.gov.pl
Website None
National language





 
9.4. Dissemination format - microdata access

Availability Links






 
9.5. Dissemination format - other
9.6. Documentation on methodology

  Availability Links
Methodological report None
National language
Quality Report None
Metadata None
National language
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 quality report? Further automation
Increased use of administrative data
Staff further training
Other
If other, which?

use of satellite data
Burden reduction measures since the previous reference year  Less frequent surveys
Less respondents
More user-friendly questionnaires
Easier data transmission
Multiple use of the collected data
Other
If other, which?

Data collection of electronic form






 


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


12. Comment Top

GIJHARS and KOWR (National Support Centre for Agriculture) are maintained by the ministry.

Polish IACS is a register kept by ARMA (Agency for Restructuring and Modernization of Agriculture – ARMA), also kept by the ministry.

 


Related metadata Top


Annexes Top