Landings of fishery products (fish_ld)

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

Compiling agency: FISHERIES AGENCY


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

FISHERIES AGENCY
1.2. Contact organisation unit

IT & Data
1.5. Contact mail address

Nyropsgade 30
1780 København V

Denmark


2. Statistical presentation Top
2.1. Data description

Main characteristics

2.1.1 Describe shortly the main characteristics of the statistics  

The Landings Regulation (Reg (EC) 1921/2006) requires Member States and EEA EFTA States to submit statistical data on an annual basis and within six months of the end of the reference calendar year. They are required to provide data on total quantities and unit values of the fishery products landed in their territory by EU and EEA EFTA vessels.


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?  No
If Yes, please answer all the following questions.   
2.1.4 Name of the national legislation 
2.1.5 Link to the national legislation 
2.1.6 Responsible organisation for the national legislation 
2.1.7 Year of entry into force of the national legislation 
2.1.8 Please indicate which variables required under EU regulation are not covered by national legislation, if any.
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? 


Additional comments on data description
2.2. Classification system

Data are broken down by:
1) the species of aquatic organisms identified using the 3-alpha codes as defined by the FAO (ASFIS List of Species for Fishery Statistics Purposes);
2) the flag state of the fishing vessels carrying out landings (as per the codes set out in Annex II to the Landings Regulation);
3) the ‘presentation’ of the products i.e. processed state of the fisheries product or part thereof e.g. fresh fillets, frozen headed and gutted, smoked, etc. (See Annex III of the Regulation);
4) the intended use of the products i.e. how landed fish are intended to be used e.g. for human consumption, industrial uses, bait etc. (See Annex IV to the Regulation).
2.3. Coverage - sector

Fishery products landed on Danish territory by EU and EEA EFTA vessels
2.4. Statistical concepts and definitions

Total quantities and corresponding value of all fishery products landed in the reporting country are to be reported, regardless of the nationality of the vessel making the landings. Landings by vessels of the reporting country in foreign ports are excluded. Details on products presentation and intended use are required, as well as vessel nationality.
'Community fishing vessels' means fishing vessels flying the flag of an EU Member State and registered in the Community.
'EFTA fishing vessels' means fishing vessels flying the flag of, or registered in, an EEA EFTA country.
'Unit value' means the value at first sale of the fishery products landed (in national currency) divided by the quantity landed (in tonnes), or for fishery products not immediately sold, the average price per tonne in national currency, estimated using an appropriate method.
Landed quantities are expressed in Tonnes Product Weight.
Unit values are reported as unit price in national currency per tonne.
2.5. Statistical unit

The basic statistical units are the individual fishing vessels
2.6. Statistical population

All registered vessels landing fishery products on Danish territory.
2.7. Reference area
2.7.1 Geographical area covered

The entire territory of Denmark. This does not include Greenland and Faroe Islands.
2.7.2 Which special Member State territories are included?

None
2.8. Coverage - Time

1986-present
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"

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 Marine fishing areas covered
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 Marine fishing areas covered
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

Sales note Register
3.1.32 Name of Organisation responsible

Fisheries Agency
3.1.33 Contact information (email and phone)

mail@fisk-st.dk
3.1.34 Main administrative scope

To fulfil 1380/2013 and administer the quota utilisation.
3.1.35 Geospatial Coverage National
Regional
3.1.36 Type of administrative documents collected Paper Logbooks
Electronic logbooks
Sales notes
Landings declarations
3.1.37 If Other, please specify
3.1.38 Are these documents in accordance with the rules set in the current EU Regulations (EC) 1224/2009 and (EU) 404/2011 for each of your fleet segments? Yes
3.1.39 If partially, which rules are not applied?
3.1.40 Are landing data for vessels under 10 metres long collected? Yes
3.1.41 Is the Electronic Reporting System (ERS) used for vessels above 12 meters as foreseen in Regulations (EC) 1224/2009 and (EU) 404/2011? Yes
3.1.42 Is the Vessel Monitoring System (VMS) used for vessels above 12 meters as foreseen in Regulations (EC) 1224/2009 and (EU) 404/2011? Yes
3.1.43 Marine fishing areas covered Atlantic, Northwest
Atlantic, Northeast
Atlantic, Eastern Central
3.1.44 Update frequency Continuous
3.1.45 Legal basis

The Common Fisheries Policy, 1380/2013
3.1.46 Are you able to access directly to the micro data? Yes
3.1.47 Are you able to check the plausibility of the data, namely by contacting directly the units? Yes
3.1.48 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
3.1.49 Please list the main differences between the administrative source and the statistical definitions and concepts

Sampling techniques are generally not used in the collection of data for the official fishery statistics. Sampling is not necessary because all commercial catch and landings of fish, crustaceans and molluscs are recorded. A sale by non-commercial (recreational) Danish fishermen is forbidden. Sample techniques are only used to estimate bycatches in the industrial fishery before April 1st 2020. All fishing areas are covered.
3.1.50 Is a different threshold used in the administrative source and statistical data? No
3.1.51 If Yes, please specify
3.1.52 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 
3.1.53 Name/Title
3.1.54 Primary purpose
3.1.55 Legal basis
3.1.56 Update frequency
3.1.57 Expert data supplier
3.1.58 If Other, please specify
3.1.59 How would you assess the quality of those data?
3.1.60 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 
3.1.61 Name/Title
3.1.62 Name of Organisation
3.1.63 Primary purpose
3.1.64 Data type
3.1.65 If Other, please specify
3.1.66 How would you assess the quality of those data?
3.1.67 Additional comments

 
3.2. Frequency of data collection

Annual

Log-books and sales notes are processed daily. Every night a computerized system ensures correlation between logbooks and sales notes on the basis of a complex algorithm. Furthermore overnight new statistical data sets are compiled for management and control purposes. For use in the information system for statistics, new data sets with preliminary figures are released about two weeks after the end of each month. Thus, preliminary figures for a year are released by the end of January the following year. It is difficult to estimate when final figures are available since corrections to information can be necessary due to more recent and correct information about data. It is the objective to obtain as updated figures as possible in the databases. However, after the month of June there are few corrections with regard to figures for the previous year. For statistical purposes, a version of selected data from the previous year is ‘frozen’ each year around May 1st. This is done in agreement with Statistics Denmark.
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

Sales note register
3.3.16 Extraction date

24-06-2020
3.3.17 How easy is it to get access to the data? Direct constant access
3.3.18 Data transfer method

Every night the sales note register is updated automatically by a computerized system.
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
Other
3.4.3 If Other, please specify

Unit value, Unit price-range, Geografical areas
3.5. Data compilation
3.5.1 Describe the data compilation process

Data is compiled in accordance with Reg. 1921/2006 using SAS (a statistical analysis system)
3.5.2 Which conversion factors were used from tonnes product weight (TPW) to tonnes live weight (TLW)? EU conversion factors
3.5.3 Additional comments
3.6. Adjustment

The first-hand buyer is obliged to register the area in which the fish is caught on the sales note, although the buyer does not have direct access to this type of information. This can cause problems with data quality. Until data on fishing area from the sales notes is reliable, a computerized algorithm correlates sales notes with logbooks and “stamp” the fishing area from the logbook to the sales note.


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?

Every day logbooks and sales notes are attempted correlated and matched by the computer system, according to vessel registration number, date of landing, port, etc. A number of internal reports provide information on potential data errors in both logbooks and sales notes. These are subsequently checked by our data quality staff, and if errors are encountered, they are corrected manually in the database. Occasionally The Danish Agrifish Agency launches campaigns targeted at specific data quality issues. Further the rules of Control Regulation 1224/2009 article 109 onwards is implemented in a VALID system that checks for inconsistencies according to the national plan sent to DGMARE.
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?
4.1.6 If Other, please specify
4.1.7 Additional comments
4.2. Quality management - assessment

Development since the last quality report

4.2.1 Overall quality Stable
4.2.2 Relevance Stable
4.2.3 Accuracy and reliability Stable
4.2.4 Timeliness and punctuality Stable
4.2.5 Comparability Stable
4.2.6 Coherence Stable
4.2.7 Additional comments


5. Relevance Top
5.1. Relevance - User Needs
5.1.1 If certain user needs are not met, please specify which and why
5.1.2 Please specify any plans to satisfy needs more completely in the future
5.1.3 Additional comments
5.2. Relevance - User Satisfaction
5.2.1 Has a user satisfaction survey been conducted? No
If Yes, please answer all the following questions 
5.2.2 Year of the user satisfaction survey
5.2.3 How satisfied were the users?
5.2.4 Additional comments
5.3. Completeness
5.3.1 Data completeness - rate

99%
5.3.2 If not complete, which characteristics are missing?

The calculation of average prices is based on the total registered quantities and the corresponding values. Estimation is generally not necessary because all lots of commercialised fish etc. are registered. The value of the Danish landings in foreign ports is registered in Danish Krone (DKK) using the exchange rate on the day of marketing.

Average prices are only used, when the price of the landing is zero. In general there are three instances in which we register zero prices: 1) Transit landings, because it can be difficult to receive the actual price from foreign buyers 2) When a landing is withdrawn from the market 3) In cases, where the landing has no reel value, e.g. by-catches in fishery for reduction purposes landed as industrial fishery or catches of starfish harmful to production of mussels

In the first two cases, a price is estimated from other landings on the basis of: 1) Species, 2) Area of the catch 3) Conservation 4) Presentation, 5) Intended use, 6) Month and year of the landing

Data on recreational fishery is not collected.
5.3.3 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? Non-response error
Processing error
Other
6.1.3 If Other, please specify

Late or lacking sales notes on landings in foreign ports or prices from foreign byers.
6.1.4 Additional comments

Every day logbooks, landing declarations and sales notes are attempted correlated and matched by the computer system, according to vessel registration number, date of landing, port, etc. Lacking or late sales notes or sales notes dated before the logbook (i.e. if landed around midnight) can occur and can lead to processing errors. A number of internal reports provide information on potential data errors in both logbooks and sales notes. Our data quality staff subsequently check these, and if errors are encountered, they are corrected manually in the database. However, it cannot be excluded that a few pass unnoticed.
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 the worksheet CV of the annexed Excel file
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

Not applicable.
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

Not applicable.
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

Sales note register
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?

Control and validation of data occurs in the process of entering data into the IT-system. A number of cross validation systems highlights potential errors in data. These are subsequently checked by our data quality staff, and if errors are encountered, they are corrected manually in the database. 

Every day logbooks and sales notes are attempted correlated and matched by the computer system, according to vessel registration number, date of landing, port, etc. A number of internal reports provide information on potential data errors in both logbooks and sales notes. These are subsequently checked by our data quality staff, and if errors are encountered, they are corrected manually in the database. Occasionally The Danish Agrifish Agency launches campaigns targeted at specific data quality issues. Further the rules of Control Regulation 1224/2009 article 109 onwards is implemented in a VALID system that checks for inconsistencies according to the national plan sent to DGMARE.
6.3.1.30 Does the administrative source include units that do not exist in practice? No
6.3.1.31 Over-coverage - rate

None
6.3.1.32 Impact on the data quality None
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey? Yes
6.3.1.34 If Not, which units are not included?

Illegal trade does occur, but at a very low scale and our control officers takes a strong line against it.

 
6.3.1.35 How large do you estimate the proportion of those units? (%)

Very low
6.3.1.36 Impact on the data quality None
Misclassification 
6.3.1.37 Impact on the data quality Low
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 applicable.
6.4. Seasonal adjustment

Not applicable.
6.5. Data revision - policy

Logbooks and sales notes are processed daily. Every night a computerized system ensures correlation between logbooks and sales notes on the basis of a complex algorithm. Furthermore overnight new statistical data sets are compiled for management and control purposes. For use in the information system for statistics, new data sets with preliminary figures are released about two weeks after the end of each month. Thus, preliminary figures for a year are released by the end of January the following year. It is difficult to estimate when final figures are available since corrections to information can be necessary due to more recent and correct information about data. It is the objective to obtain as updated figures as possible in the databases. However, after the month of June there are few corrections with regard to figures for the previous year. For statistical purposes, a version of selected data from the previous year is ‘frozen’ each in the beginning of May. This is done in agreement with Statistics Denmark. 
6.6. Data revision - practice
6.6.1 Data revision - average size

Not available.
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?

01-01-2023
7.1.2 When were  the final results for the reference period published?

01-04-2023
7.1.3 Reasons for possible long production times?

Compiled data is shown on our homepage for administrative purposes. These are updated on a nightly basis current year and the following year. Data for statistical purposes are 'frosen' around April 1st the following year. Frosen data on the year before are uptaded at the same time.
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
7.2.4. Punctuality - delivery and publication

0


8. Coherence and comparability Top
8.1. Comparability - geographical

To be assessed by Eurostat
8.1.1. Asymmetry for mirror flow statistics - coefficient

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

1986-2019
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? None
8.3.2 If Other, please specify
8.3.3 Describe briefly the results of comparisons
8.3.4 If no comparisons have been made, explain why

Validations are made on micro data.
8.3.5 Additional comments
8.4. Coherence - sub annual and annual statistics

Not applicable.
8.5. Coherence - National Accounts

Not applicable.
8.6. Coherence - internal


9. Accessibility and clarity Top
9.1. Dissemination format - News release
9.1.1 Do you publish a news release? No
9.1.2 If Yes, please provide a link
9.2. Dissemination format - Publications
9.2.1 Do you produce a paper publication? No
9.2.2 If Yes, is there an English version?
9.2.3 Do you produce an electronic publication? Yes
9.2.4 If Yes, is there an English version? Yes
9.2.5 Please provide a link

https://fiskeristyrelsen.dk/english/fishery-statistics/
9.3. Dissemination format - online database
9.3.1 Data tables - consultations

http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
9.3.2 Is an on-line database accessible to users? Yes
9.3.3 Please provide a link

https://fiskeristatistik.fiskeristyrelsen.dk/SASVisualAnalytics/?reportUri=%2Freports%2Freports%2F3207ff0a-4f3c-4adb-a9ca-e8f45f15e3ae&sso_guest=true&sas-welcome=false

To be accessed in Google Crome 
9.4. Dissemination format - microdata access
9.4.1 Are micro-data accessible to users? No
9.4.2 Please provide a link

none
9.5. Dissemination format - other
9.6. Documentation on methodology
9.6.1 Are national reference metadata files available? Yes
9.6.2 Please provide a link

https://fiskeristyrelsen.dk/fiskeristatistik/kvotestatistik-og-kvoteudnyttelse/kode-og-begrebsforklaring-til-kvotestatistikken/
9.6.3 Are methodological papers available? Yes
9.6.4 Please provide a link

https://fiskeristyrelsen.dk/fiskeristatistik/dynamiske-tabeller/vejledning-til-dynamisk-fartoejstabel/
9.6.5 Is a handbook available? No
9.6.6 Please provide a link

None
9.7. Quality management - documentation
9.7.1 Metadata completeness - rate

Not availlable
9.7.2 Metadata - consultations

None
9.7.3 Is a quality report available? Yes
9.7.4 Please provide a link

https://www.dst.dk/da/Statistik/dokumentation/statistikdokumentation/landinger-af-fisk


10. Cost and Burden Top
10.1 Efficiency gains if compared to the previous quality report None
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report None
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

Same as in (EC) 223/2009
11.2. Confidentiality - data treatment
11.2.1 Describe the procedures for ensuring confidentiality during dissemination

Checks are made to ensure confidentiallity on figures contributed by less than three vessels.
11.2.2 Additional comments


12. Comment Top


Related metadata Top


Annexes Top