Aquaculture production by species (fish_aq)

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

Compiling agency: State enterprise Agricultural Data Center (ADC)


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)
 



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1. Contact Top
1.1. Contact organisation

State enterprise Agricultural Data Center (ADC)
1.2. Contact organisation unit

Market Information and Economic Analysis division
1.5. Contact mail address


2. Statistical presentation Top
2.1. Data description

Main characteristics

2.1.1 Describe shortly the main characteristics of the statistics 

Aquaculture production statistics as defined in Regulation (EC) 762/2008 contain four different datasets:
AQ2A - Aquaculture production volume at first sale for human consumption (excluding hatcheries and nurseries) by species, FAO Major Area, cultivation method and aquatic environment.
AQ2B - Production of fish eggs (roe) for human consumption at first sale by species, by FAO Major Area, cultivation method and aquatic environment.
AQ3 - Input to capture-based aquaculture, i.e. wild seed, by species.
AQ4 - Production of juveniles and fertilised eggs at first sale for further on-growing or release to the wild by species.
The production volume is measured in tonnes live weight (TLW) and economic value as unit price in national currency per tonne (NAC_T/TLW), with the exception of juveniles and fertilised eggs which are measured in numbers.
In addition, a fifth dataset (AQ5) provides information on the size (in hectares, 1000 cubic metres or metres) of aquaculture production facilities segmented by species group, FAO Major Area, cultivation method and aquatic environment.


Reference period

2.1.2 Reference period of the data collection 

2022


National legislation

2.1.3 Is there a national legislation covering these statistics? Yes
If Yes, please answer all the following questions.
2.1.4 Name of the national legislation

Order of Lithuanian Minister of Agriculture 2010 08 04  No. 3D-707 "Concerning approval of rules for fishery statistical data collection"
2.1.5 Link to the national legislation

https://www.e-tar.lt/portal/lt/legalAct/TAR.4671ED89B13B/asr
2.1.6 Responsible organisation for the national legislation

Legislation approved by the Order of Lithuanian Minister of Agriculture, implemented by ADC
2.1.7 Year of entry into force of the national legislation

2010
2.1.8 Please indicate which variables required under EU regulation are not covered by national legislation, if any.

All variables required under EU regulation are covered by national legislation.
2.1.9 Please indicate which national definitions differ from those in the EU regulation, if any.
2.1.10 Is there a legal obligation for respondents to reply? Yes


Additional comments to data description
2.2. Classification system

The following variables are recorded with regard to aquaculture production:
a) 'Species' means the species of aquatic organisms identified using the international 3-alpha code as defined by the FAO (ASFIS List of Species for Fishery Statistics Purposes). Individual species are grouped in aggregates according to their taxonomy and living habits. These aggregates are specified in the International Standard Statistical Classification of Aquatic Animals and Plants (ISSCAAP) and indicated in the ASFIS list.
b) 'FAO major areas' means the geographical areas as defined by the FAO (CWP Handbook of fishery statistical standards). The FAO major areas covered are: 27 'Northeast Atlantic', 37 'Mediterranean and Black Sea', 34 'Atlantic Eastern Central', 5 'European inland waters', 1 'African inland waters'.
c) 'Cultivation method' includes ponds, cages, tanks and raceways, enclosures and pens, recirculation systems, others and not specified. For molluscs also on-bottom and off-bottom systems.
d) 'Aquatic environment' distinguishes the water types fresh water and salt (sea and brackish) water.
The methods and water types are defined in Annex I of Regulation (EC) No 762/2008.

Classification of Economic Activities (EVRK 2 red).
2.3. Coverage - sector

Aquaculture production sector in Lithuania
2.4. Statistical concepts and definitions
According to Regulation (EC) 762/2008, aquaculture production means the output from aquaculture at first sale. If aquaculture farm carry out processing of their own production and release to the market processed product, information on production value takes into account processed fish.
The production volume is expressed in tonnes live weight [TLW] of the product. This weight includes all shells and bones. Data for the economic value of the production are reported as unit price in national currency per tonne [NAC_T]. The production of hatcheries and nurseries is reported in numbers and expressed in millions. Data on the structure of the aquaculture sector are expressed in thousand cubic metres, hectares or, optionally, 'metres rope length' according to the method.
2.5. Statistical unit

Enterprises, farmers and licensed individuals carrying out aquaculture activities
2.6. Statistical population

Business entities carrying out aquaculture activities under EVRK code 03.22 and aquaculture farmers, registered in the Register of Farmers' Register of the Republic of Lithuania and included in the list of State Veterinary Control Register of  Lithuanian Food and Veterinary Service and having a veterinary approval number.

  • State institutions of the Republic of Lithuania, which in their internal regulation specify aquaculture activities as commercial.
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?

not applicable
2.8. Coverage - Time

Annual statistics on the structure and production of aquaculture since 2010.
2.9. Base period

Not applicable


3. Statistical processing Top
3.1. Source data

Overall summary

3.1.1 Total number of different data sources used

1
The breakdown is as follows:
3.1.2 Total number of sources of the type "Census"

1
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"

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

Semiannual/Annual survey of Aquaculture production, sale, structure and employment
3.1.8 Name of Organisation responsible

State enterprise Agricultural Data Center
3.1.9 Main scope

To collect data for statistics on aquaculture
3.1.10 List used to build the frame

Commercial aquaculture units, included in register of Lithuanian State Food and Veterinary Service for aquaculture activities
3.1.11 Any possible threshold values
3.1.12 Population size

Depending on reference year. In 2022 was 66 active commercial aquaculture units which reported aquaculture production at first sale
3.1.13 Surveyed entity Enterprise
3.1.14 If Enterprise, please specify Any enterprise active in the aquaculture sector
3.1.15 Additional comments

Excluding National authorities carrying fish restocking activities and research institutes which possess aquaculture units for research purposes.


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 
3.1.16 Name/Title
3.1.17 Name of Organisation responsible
3.1.18 Main scope
3.1.19 List used to build the frame
3.1.20 Any possible threshold values
3.1.21 Population size
3.1.22 Surveyed entity
3.1.23 If Enterprise, please specify
3.1.24 Sample size
3.1.25 Sampling basis
3.1.26 If Other, please specify
3.1.27 Type of sample design
3.1.28 If Other, please specify
3.1.29 If Stratified, number of strata
3.1.30 If Stratified, stratification criteria
3.1.31 If Other, please specify
3.1.32 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 
3.1.33 Name/Title
3.1.34 Name of Organisation responsible
3.1.35 Contact information (email and phone)
3.1.36 Main administrative scope
3.1.37 Geospatial Coverage
3.1.38 Update frequency
3.1.39 Legal basis
3.1.40 Are you able to access directly to the micro data?
3.1.41 Are you able to check the plausibility of the data, namely by contacting directly the units?
3.1.42 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?
3.1.43 Please list the main differences between the administrative source and the statistical definitions and concepts
3.1.44 Is a different threshold used in the administrative source and statistical data?
3.1.45 If Yes, please specify
3.1.46 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 
3.1.47 Name/Title
3.1.48 Primary purpose
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 Data type
3.1.59 If Other, please specify
3.1.60 How would you assess the quality of those data?
3.1.61 Additional comments

 
3.2. Frequency of data collection

Annual
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

Semiannual/Annual survey of Aquaculture production, sale, structure and employment
3.3.2 Methods of data collection Electronic questionnaire
Other
3.3.3 If Other, please specify

Interactive data input system (direct input of data to database)
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)

Questionnaire on aquaculture production, sales, employment and economic activity (Ž-4) (in national language) 
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
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
Consistency
Other
3.4.3 If Other, please specify

In order to increase the accuracy of the published statistics, all submitted data is checked. In case of significant deviations, data providers are contacted for clarification concerning non-compliance. If non-conformities are detected, they are recorded in the non-compliance journal (Annex 6 of Rules of fisheries data collection in Lithuania). After clarification, statistical data are corrected. In order to reduce the number of discrepancies, non-compliances registered in the journal are analyzed, their causes and preventive measures as well as actions for reducing the non-compliance are considered.

Pursuant to the Description of Data Provider Verification Procedure, approved by Order No. 1V-353 of 9 June2023 of the Director General of ADC, the compliance of data with the requirements of legal acts and the completeness and accuracy of submission are verified in data providers companies and farms by crosschecking the data provided with accountancy documentation (internal document).
3.5. Data compilation
3.5.1 Describe the data compilation process

The compilation of statistics after data collection and verification is performed by aggregating the data as needed. Explanations of the calculation of the applied methods and indicators are provided in the Methodology for the survey of production, sales, employment and economic activity indicators in aquaculture, marine fisheries and fish processing industries (only in Lithuanian).

Disaggregation of production data to juveniles and for consumption, is based on the weight per fish unit (depending on species with particular minimum pan size) and crosschecked with fish age. 
3.5.2 Additional comments
3.6. Adjustment

Impact of seasonality on survey of the structure and production of Lithuanian aquaculture sector is not assessed.


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?

The quality of statistical information and its preparation is ensured in accordance with the provisions of the European Statistics Code of Practice. For quality assurance framework ADC has adopted:
•    2017 March 15 Order No. 1V-54 of the Director General of the AIRBC “On the provision, verification, processing, preparation of statistical information to the European Commission, Eurostat and National Authorities for the statistical information on the Lithuanian agricultural and food products market system and the approval of the publication procedure (internal document);
•    2023 March 6 Order No. 1V-367 of Director General of ADC “On the approval of quality policy of State enterprise Agricultural Data Center” (internal document).
In its activities, ADC follows the principles of the integrated management system, which includes elements of quality and information security management in accordance with the Lithuanian standard LST ISO / IEC 9001: 2015 and the Lithuanian standard LST ISO / IEC 27001: 2013.
4.1.3 Has a peer review been carried out? Yes
4.1.4 If Yes, which were the main conclusions?

SE AIRBC (currently ADC) carried out European Statistical System Peer Reviews “Light Self-assessment questionnaire on the implementation of the European Statistics Code of Practice” (Final version as approved by the ESSC on 14 November 2013) for all types of statistics including fisheries. There were not a separate assessment for aquaculture statistics. With regard to Self-assessment analysis audit from Eurostat was carried out and audited processes were in line with standard, no remarks were provided.
4.1.5 What quality improvements are foreseen? Other
4.1.6 If Other, please specify

SE AIRBC (currently ADC) composed a list of measures complying with each ESCP principles and prepare annual reports for implementation of each measure. (The document is in Lithuanian language and if needed, could be attached to the ESS MH)
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 Improvement
4.2.3 Accuracy and reliability Improvement
4.2.4 Timeliness and punctuality Improvement
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

All end-user needs were met
5.1.2 Please specify any plans to satisfy needs more completely in the future

Additional needs from end-users (concerning implementation of Operational Programme) are included updating aquaculture data reporting form
5.1.3 Additional comments

The main end-users of statistical information are European Commission, Lithuanian Agricultural Ministry and other national authorities, municipal institutions, business and science representatives, the media and other users whose needs are met without prejudice to the principle of confidentiality.
5.2. Relevance - User Satisfaction
5.2.1 Has a user satisfaction survey been conducted? Yes
If Yes, please answer all the following questions
5.2.2 Year of the user satisfaction survey

Continuous
5.2.3 How satisfied were the users?
5.2.4 Additional comments

Quality assessment questionnaire for the data user service is available online.
5.3. Completeness
5.3.1 AQ2A - Data completeness - rate

100%
5.3.2 AQ2B - Data completeness - rate

100%
5.3.3 AQ3 - Data completeness - rate

100%
5.3.4 AQ4 - Data completeness - rate

100%
5.3.5 AQ5 - Data completeness - rate

100%
5.3.6 If not complete, which characteristics are missing?
5.3.7 Additional comments


6. Accuracy and reliability Top
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? Other
6.1.3 If Other, please specify

Survey on the Lithuanian aquaculture sector is census.

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 If coefficients of variation are calculated, please describe the calculation methods and formulas
6.2.5 Sampling error - indicators
6.2.6 Additional comments

Sampling is not applied for the compilation of statistics of the structure and production of Lithuanian aquaculture sector.
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

Semiannual/Annual survey of Aquaculture production and sale (Statistical form Ž-4 (3D-707))
Over-coverage 
6.3.1.2 Over-coverage - rate

Not available.
Under-coverage 
6.3.1.3 Does the sample frame include all units falling within the scope of this survey? Yes
6.3.1.4 If Not, which units are not included?
6.3.1.5 How large do you estimate the proportion of those units? (%)

All units are covered
6.3.1.6 Impact on the data quality None
Misclassification 
6.3.1.7 Impact on the data quality None
Common units 
6.3.1.8 Common units - proportion

Not available.
6.3.1.9 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  
6.3.1.10 Name/Title
Over-coverage 
6.3.1.11 Over-coverage - rate

Not available.
Under-coverage 
6.3.1.12 Does the sample frame include all units falling within the scope of this survey?
6.3.1.13 If Not, which units are not included?
6.3.1.14 How large do you estimate the proportion of those units? (%)
6.3.1.15 Impact on the data quality
Misclassification 
6.3.1.16 Impact on the data quality
Common units 
6.3.1.17 Common units - proportion

Not available.
6.3.1.18 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 
6.3.1.19 Name/Title
Over-coverage 
6.3.1.20 Over-coverage - rate

Not available.
Under-coverage 
6.3.1.21 Does the administrative source include all units falling within the scope of this survey?
6.3.1.22 If Not, which units are not included?
6.3.1.23 How large do you estimate the proportion of those units? (%)
6.3.1.24 Impact on the data quality
Misclassification 
6.3.1.25 Impact on the data quality
6.3.1.26 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

Semiannual/Annual survey of Aquaculture production and sale (Statistical form Ž-4 (3D-707))
6.3.2.2 Is the questionnaire based on usual concepts for respondents? Yes
6.3.2.3 Number of censuses already performed with the current questionnaire?

12
6.3.2.4 Explanatory notes/handbook for surveyors/respondents?  Yes
6.3.2.5 On-line FAQ or Hot-line support for surveyors/respondents? No
6.3.2.6 Other actions taken for reducing the measurement error?

Prepared and publicly available methodology, consultation by email or phone call is used
6.3.2.7 Additional comments

Errors not related to the sample do not have a significant effect on results, but inconsistencies may occur when respondents report data in inappropriate units of measurement or make errors in reporting data. In these cases, deviations are determined applying methods used to find out the outliers, as well as by comparing data for the reporting period with time series. Identified discrepancies are corrected.


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 
6.3.2.8 Name/Title
6.3.2.9 Is the questionnaire based on usual concepts for respondents?
6.3.2.10 Number of surveys already performed with the current questionnaire?
6.3.2.11 Explanatory notes/handbook for surveyors/respondents? 
6.3.2.12 On-line FAQ or Hot-line support for surveyors/respondents?
6.3.2.13 Other actions taken for reducing the measurement error?
6.3.2.14 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
6.3.3.2 Unit non-response - rate

 In 2021 responses were achieved from all aquaculture producers which declare aquaculture production.
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 Reminders
Legal actions
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate

Depending on the nature of statistical survey, it is considered that there are no indicators that have voluntary or mandatory options of reporting. Therefore, in the case of empty values of indicator and in the absence of possibility to check whether the value of indicator shall be reported (compared to administrative or previous year's data) it is not considered as item non-response.
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

Error due to non-response is insignificant.


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
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

Semiannual/Annual survey of Aquaculture production, sale, structure and employment (Statistical form Ž-4 (3D-707))
6.3.4.2 Imputation - rate

Not applicable
6.3.4.3 Imputation - basis
6.3.4.4 If Other, please specify
6.3.4.5 Additional comments


Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file 
6.3.4.6 Name/Title
6.3.4.7 Imputation - rate
6.3.4.8 Imputation - basis
6.3.4.9 If Other, please specify
6.3.4.10 How do you evaluate the impact of imputation on Coefficients of Variation?
6.3.4.11 Additionnal comments
6.3.5. Model assumption error

Not applicable
6.4. Seasonal adjustment

Not applicable
6.5. Data revision - policy

Final results are published and are not subject to subsequent revision. The exception is when legal acts change (if this affects statistical reports or data) or when errors become apparent after checking statistical reports (indicators) and when business entities correct data.
6.6. Data revision - practice
6.6.1 Data revision - average size

Not applicable
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

The final results are published and are not subsequently revised. Exception - the revision of statistical reports is carried out in the course of the change of legal acts or when significant errors are identified.


7. Timeliness and punctuality Top
7.1. Timeliness
7.1.1 When were the first  results for the reference period published?

Information is published after 4 months after the end of reference year.
7.1.2 When were the final results for the reference period published?

Statistical information is published according to the ADC Calendar of Statistics.
7.1.3 Reasons for possible long production times?
7.2. Punctuality
7.2.1 Were data released 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 release date of data and the target date

0


8. Coherence and comparability Top
8.1. Comparability - geographical

Statistical information is comparable between EU countries.
8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.
8.2. Comparability - over time
8.2.1 Length of comparable time series

from 2010 up to now
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?

Trade statistics
8.3.2 Describe briefly the results of comparisons
8.3.3 Additional comments

Statistical information on the employment in aquaculture is coherent with aquaculture production and structure of sector.
8.4. Coherence - sub annual and annual statistics

Not applicable.
8.5. Coherence - National Accounts

Not applicable.
8.6. Coherence - internal

Full internal data coherence is ensured


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.vic.lt/drp-en/statistics/aquaculture/3-1-1-sales-of-aquaculture-production-in-lithuania/
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.vic.lt/leidiniai/lietuvos-zemes-ukis-faktai-ir-skaiciai-2007-m/
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? Yes
9.3.3 Please provide a link

https://www.vic.lt/drp-en/statistics/aquaculture/3-1-1-sales-of-aquaculture-production-in-lithuania/
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

By end-user request
9.6. Documentation on methodology
9.6.1 Are national reference metadata files available? Yes
9.6.2 Please provide a link

https://osp.stat.gov.lt/documents/10180/5118910/Akvakult%C5%ABros+%C4%AFmoni%C5%B3+strukt%C5%ABra+ir+produkcija+%5BEN%5D+5201.html/964e6b1c-1e36-436e-b3f3-922e1ac65cc9
9.6.3 Are methodological papers available? Yes
9.6.4 Please provide a link

Methodology for the survey of production, sales, employment and economic activity indicators in aquaculture, marine fisheries and fish processing industries (only in Lithuanian).
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 available.
9.7.2 Metadata - consultations

There is a constant coordination with Statistics Lithuania for metadata preparation and consultations
9.7.3 Is a quality report available? No
9.7.4 Please provide a link

For quality assurance framework AIRBC has adopted:

  • 2017 March 15 Order No. 1V-54 of Director General of the AIRBC Regarding the provision, verification, processing, preparation of statistical information to the European Commission, Eurostat and National Authorities for the statistical information on the Lithuanian agricultural and food products market system and the approval of the publication procedure (internal document).
  • 2023 March 6 Order No. 1V-367 of Director General of ADC “On the approval of quality policy of State enterprise Agricultural Data Center” (internal document).


10. Cost and Burden Top
10.1 Efficiency gains over the last 3 years None
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report None
10.4 If Other, please specify

Data concerning aquaculture sector is collected for administrative needs (Ž-4 questionnaire) and parallelly used for the preparation of official statistics. Therefore, it is considered no response burden on respondents.


11. Confidentiality Top
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

Concerning the data collection, processing, analysis and dissemination of statistical information, ADC fully guarantees the confidentiality of data provided by respondents according to the Information Security Policy Guidelines of ADC. The Guidelines of Security Policy were approved by Order No. 1V-367 of 15 June 2023 of the Director General of ADC “On the approval of the information security policy of the State enterprise Agricultural Data Center” (internal document).
11.2. Confidentiality - data treatment
11.2.1 Describe the procedures for ensuring confidentiality during dissemination

Procedures for confidentiality are laid down in the Order No. 1V-367 of 15 June 2023 of the Director General of ADC “On the approval of the information security policy of the State enterprise Agricultural Data Center” (internal document).
11.2.2 Additional comments

Approach for publishing national Aquaculture statistics: Top-down

Procedures for ensuring confidentiality of disseminated data: Aggregation


12. Comment Top


Related metadata Top


Annexes Top