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    Documentation of statistics: Imprisonments

    Contact info, Personal Finances and Welfare, Social Statistics , Iben Birgitte Pedersen , +45 23 60 37 11 , IPE@dst.dk , Get documentation of statistics as pdf, Imprisonments 2024 , Previous versions, Imprisonments 2023, Imprisonments 2022, Imprisonments 2021, Imprisonments 2020, Imprisonments 2019, Imprisonments 2018, Imprisonments 2017, Imprisonments 2016, Imprisonments 2015, The purpose of the statistics is to analyze the number of arrests for violation of the penal code and the special laws (among these the Danish Road Traffic Act). The statistics on imprisonments was published for the first time for the year 2015., Statistical presentation, The statistics shed light on the number of arrests for violation of the penal code, the road traffic act and other special legislation. In the published statistics the arrests are classified into type of offence, outcome and education. Demographically the statistics are divided into age and sex., Read more about statistical presentation, Statistical processing, Data on imprisonments, which Statistics Denmark receive from the Central Criminal Register, are linked to data from Statistics Denmark's Population Register and Statistics Denmark's Educational Register. Data are already validated. However, central variables go through a probability check in form of a comparison with data from the previous year., Read more about statistical processing, Relevance, The statistics are used broadly by the authorities, enterprises, organisations, researchers, the press, in the public debate etc. Views and suggestions from key users are taken into consideration in the preparation of the statistics., Read more about relevance, Accuracy and reliability, The data used in the statistics are drawn from the Central Criminal Register. The data are typically drawn about 1 February following the relevant calendar year. A number of imprisonments started/ended during the calendar year have not been registered before the data are drawn. This implies that the total number of imprisonments presumably is under-estimated., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately 5 months after the end of the reference year. The statistics are published without delay in relation to the scheduled time., Read more about timeliness and punctuality, Comparability, Since 2015, the statistics has been prepared on the same date source. In general the statistics is therefore comparable during time. As a consequence of law amendments or wishes for more information on specific kind of offences the division of type of offences has been altered during the years. , Read more about comparability, Accessibility and clarity, In StatBank the statistics are published in the tables , STRAF70, , , STRAF71, , , STRAF72, , , STRAF73, , og , STRAF74, ., Furthermore the statistics are published in the publication , "Kriminalitet", (Criminality)., See more at the , Subject page, ., Taylor made statistics can be produced on the basis of data from different registers, moreover through Statistics Denmark's Division of Research Service it is possible for researchers to be granted access to anonymised data., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/imprisonments

    Documentation of statistics

    Documentation of statistics: Accounts Statistics for Aquaculture

    Contact info, Food Industries, Business Statistics , Michael Brogaard , +45 51 62 70 89 , MIB@dst.dk , Get documentation of statistics as pdf, Accounts Statistics for Aquaculture 2023 , Previous versions, Accounts Statistics for Aquaculture 2022, Accounts Statistics for Aquaculture 2021, Accounts Statistics for Aquaculture 2020, Accounts Statistics for Aquaculture 2019, Accounts Statistics for Aquaculture 2018, Accounts Statistics for Aquaculture 2017, Accounts Statistics for Aquaculture 2016, Accounts Statistics for Aquaculture 2015, Accounts Statistics for Aquaculture 2014, Accounts Statistics for Aquaculture 2013, Accounts Statistics for Aquaculture 2012, The purpose of Account statistics for aquaculture is to show the economy in the Danish aquaculture sector. The statistics is used to monitor the economic development and to compare economic key figures from different farm types. The statistics was first made in 2004 and is comparable in its current form since 2017., Statistical presentation, The Account statistics for aquaculture is an annual estimation of the production value and costs, results, assets and liabilities and investments of the aquaculture sector in Denmark., Read more about statistical presentation, Statistical processing, Data for this statistics are collected yearly from the aquaculture companies' chartered accountants using an electronic accounting form. The collected accounts (the sample) are thoroughly tested, and possible errors corrected in cooperation with the reporting accountant. When all accounts are approved for statistical use, the sample of approved accounts are used together with register data for the entire population to simulate individual accounts for all units not in the sample., Read more about statistical processing, Relevance, The statistics is used by the fish farmers and their organization, Danish Aquaculture, as well as authorities and legislators. The statistics is used in economic models and as a basis for yearly economic statistical reports for aquaculture to EU (DG Mare)., Read more about relevance, Accuracy and reliability, The statistic is based on a sample, hence the results are uncertain. The aim is to include the biggest companies in the sample, and that 75 per cent of gross revenue is covered by the sample. There are no planned revisions of the statistics., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is normally made public before one year after the conclusion of the reference year., Read more about timeliness and punctuality, Comparability, The statistics is comparable from 2004 to present. All EU member states submit statistics to the , Directorate-General for Maritime Affairs and Fisheries, . Hence, it's possible to make comparisons within the EU. The Danish Fisheries Agency publish a Structure and production statistics for the profession., Read more about comparability, Accessibility and clarity, The statistics is published yearly in a Danish press release and in the StatBank under , Aquaculture, . For more information please see the , subject page, for these statistics., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/accounts-statistics-for-aquaculture

    Documentation of statistics

    Documentation of statistics: Purchases and sales by enterprises

    Contact info, Short Term Statistics , Lina Pedersen , +45 51 68 72 80 , LIP@dst.dk , Get documentation of statistics as pdf, Purchases and sales by enterprises 2024 , Previous versions, Purchases and sales by enterprises 2020, Purchases and sales by enterprises 2019, The purpose of the statistics Purchases and sales by enterprises is to monitor business cycles in Denmark, based on sales of enterprises. The statistics is based on information on value added tax (VAT) reported by the enterprises to the Danish Tax Authorities. , The statistics is compiled and disseminated monthly and provides a short-term status of Danish business economy. The statistics have been published with variation in calculation methods and frequencies, since value added tax (VAT) was introduces in Denmark in 1967. In its current form, the statistics is comparable from 2011 onwards., Statistical presentation, Purchases and sales by enterprises is a monthly statement of purchases and sales of goods and services. The Statement is calculated in millions (Danish kroner). The statement is calculated at industry level defined in the Danish Industrial Classification of All Economic Activities 2007 (DB07). In addition, the statistics are divided into domestic purchases and sales. , Read more about statistical presentation, Statistical processing, Data originates from the Danish Tax Agency’s VAT registers plus information from the Central Business Register (CVR). Missing reports are replaced with imputed values, which are values estimated for each missing report. Imputed values are provisional and removed when the enterprise has reported VAT to the Tax Agency or the enterprise's business status in the CVR register is updated as inactive. The report follows the enterprise's main industry. , Read more about statistical processing, Relevance, Users of the statistics are ministries, researchers, students and organizations. Used for e.g. analysis of business trends and market research. In Statistics Denmark, the statistic provides supporting information to e.g. the National Accounts and statistics on foreign trade. Data contribute to the Danish compliance with requirements in the European business statistics regulation regarding turnover on industries on service and trade. In order to comply with requirements, monthly turnover must be distributed to Kind of Activity Units (KAU). A model is used to split legal units into KAU. , Read more about relevance, Accuracy and reliability, The statistics is based on VAT, reported by enterprises to the Tax Agency. The precision is strengthened by the fact that all companies subject to VAT are included. It is weakened by too little information sales not subject to VAT, e.g. train tickets and recycled clothes. The reliability increases as the enterprises report and revise values. It's possible to revise up to three years after submission. Values are considered final after three years. The sales are used as an estimate for turnover. Please notes that turnover includes more than sales, e.g. revenue from investments., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximate 40 days after the end of the reference period. The statistics contain a statement of sales that are subject to VAT. A statement of an enterprise's sales subject to VAT can be used as an estimate of the enterprise's turnover, which is why the statistics are used for short-term statistics on turnover. The publication date is announced at least 6 months in advance, and it is rare that a publication of the statistics is delayed. , Read more about timeliness and punctuality, Comparability, From 2010, the statistics are based on register data, the information on VAT that enterprise report to the Tax Agency. From the year 2010, data is comparable year to year, as it includes all enterprises that report VAT. The variable "salg i alt" can be used as estimate for the enterprises' net turnover and can be compared with the net turnover in other statistics, e.g. General Enterprise Statistics. When comparing, take into account the differences, for example which types of sales or revenue are included, whether excise duties are included, and whether smaller companies are included. , Read more about comparability, Accessibility and clarity, The statistics are published on the webpage , StatBank Denmark, under the topic Purchases and sales by Enterprises. Until December 2023, the statistics was published monthly in a Danish newsletter called NYT. , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/purchases-and-sales-by-enterprises

    Documentation of statistics

    About microdata schemes

    Denmark's Data Portal makes data available to authorised institutions for specific research, fact-finding and analytical tasks. Access to data can be granted under various data schemes depending on the institution or the project to which you seek access., The researcher scheme , Researchers and other analysts from authorised institutions can create a project with access to Statistics Denmark’s register data. , Read more about authorisation of institutions, The project database scheme , The project database scheme is intended for institutions that are continuously creating projects with significant overlap in data content. Under this scheme, it is not allowed to carry out research directly on the project database, and the scheme must not be used for projects or tasks that are not directly related to the purpose of the project database. Furthermore, the institution must have one or more employees at who can serve as project database managers, of whom at least one can functions as an administrator. The duties of the project database manager include population generation, data extraction etc. as well as ongoing communication with Statistics Denmark., If you want to apply for a project database to be set up, you must contact the Project database group at , FSEProjektdatabase@dst.dk, ., More on the project database scheme, An authorised institution can have a maximum of one project database. The project database is a collection of pseudonymised microdata. It is used over time for multiple projects (called subprojects) under the relevant project database scheme., For the project database, data is selected from Statistics Denmark’s databank of basic data and, if relevant, data from other sources (such as the institution’s own data). The data content in project databases is subject to the data minimisation principle, and for that reason, data in a project database must be applied in several subprojects., In the project database scheme, the project database is called the main project. Other projects in the project database scheme are subprojects of the project database. The authorised institution that owns the project database therefore owns both the main project and the subprojects in the scheme., The target group of the project database scheme is institutions that:, are authorised for microdata schemes at Statistics Denmark., have at least five active projects with significantly overlapping data., continuously extend their project portfolio with new subprojects with significant overlap in the underlying data., Terms of a project database scheme, Project databases are subject to the following terms:, The institution is required to appoint one to three experienced project database managers who will be the assigned liaison officers with Statistics Denmark. Only project database managers get access to the actual project database., The project database and subprojects are subject to the data minimisation principle., The user must pay for all costs associated with the creation, operation and maintenance of the relevant project database. Subprojects are considered regular projects and are handled and invoiced separately., You can keep a project database going for as long as it is used for active subprojects. The project database can only be preserved as long as it is used for subprojects to an extend that is consistent with the data made available in the project database. The project database can thus be limited or discontinued if Statistics Denmark estimates that this is no longer the case., The authority scheme, The authority scheme makes microdata available to Danish institutions that carry out tasks for the authorities, i.e. departments, agencies and directorates, regions and municipalities. The scheme meets the demand for ad hoc analyses with tight deadlines. , Read more about the Authority scheme,  (in Danish), Data confidentiality and access rules, Access to data is given in agreement with the principles of the General Data Protection Regulation, especially article 5(1)(c): , “Personal data shall be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed (‘data minimisation’).” , This also applies to section 10 of the Danish Data Protection Act: , “Data as mentioned in Article 9(1) and Article 10 of the General Data Protection Regulation may be processed where the processing takes place for the sole purpose of carrying out statistical or scientific studies of significant importance to society and where such processing is necessary in order to carry out these studies.” , Read more on Statistics Denmark’s Data confidentiality policy and Information security policy 

    https://www.dst.dk/en/TilSalg/data-til-forskning/mikrodataordninger/om-mikrodataordninger

    Documentation of statistics: International Trade in Goods by Enterprise Characteristics

    Contact info, External Economy , Søren Burman , +45 30 51 45 62 , SBU@dst.dk , Get documentation of statistics as pdf, International Trade in Goods by Enterprise Characteristics 2022 , Previous versions, International Trade in Goods by Enterprise Characteristics 2021, International Trade in Goods by Enterprise Characteristics 2019, International Trade in Goods by Enterprise Characteristics 2018, International Trade in Goods by Enterprise Characteristics 2017, The purpose of Trade in Goods by Enterprise Characteristics (TEC) is to describe enterprises engaging in foreign trade, how large they are, which economic sector they belong to, how many countries they trade with etc. These statistics have been compiled since 2010 are comparable until 2018 for legal units. From 2019 and onwards the statistics have been compiled on the basis of the enterprise unit., Statistical presentation, Trade in Goods by Enterprise Characteristics is an annual measurement of enterprises involved in foreign trade and their characteristics, stated in number of enterprises and value. The statistics are grouped by economic activity, enterprise size, partner countries, ownership, type of trade and concentration of trade until 2022. From 2023 the statistics will be a measurement of enterprises involved in foreign trade and their characteristics, stated in value and they will be grouped by economic activity, items, enterprise size and ownership. The statistics can be found in our statbank under the subject External Economy. , Read more about statistical presentation, Statistical processing, These statistics are compiled by combining data for International Trade in Goods (ITGS) with Business register data. Data is validated by comparing data with the sources used for compiling the statistics and by comparing the different tables compiled in this statistic., Read more about statistical processing, Relevance, These statistics are relevant for analysts and enterprises, for analyses of e.g. globalization and enterprises which contribute to external trade in Denmark., Read more about relevance, Accuracy and reliability, The accuracy for International Trade in Goods by Enterprise Characteristics is closely related to the accuracy of International Trade in Goods Statistics which is high on an aggregated level. The revisions follow the revision structure of International Trade in Goods Statistics., There may be changes in enterprise characteristics (e.g. size, industry and ownership) during a given year, which can give rise to a change the trade flows, but the statistics reflect the characteristics at the end of the year., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published 10 months after the reference period. They are published without any delays., Read more about timeliness and punctuality, Comparability, These statistics have been disseminated since 2014 and contains values from 2010 and onwards. It is in its present form comparable from 2010 and onwards. These statistics are compiled according to common European guidelines and are therefore comparable with statistics from other EU countries published by Eurostat. The comparability can be influenced by the difference between the general- and special trade system., Read more about comparability, Accessibility and clarity, These statistics are published annual in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, these statistics can be found under the , International Trade in Goods, . The statistics can also be found in various publications and analysis’ and it is possible to gain access to microdata through our program for authorized research institutions., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/international-trade-in-goods-by-enterprise-characteristics

    Documentation of statistics

    How to create a data order

    A data order is a request used to specify which , registers, , , periods, , , populations, , and , external data, you wish to use in the project.,  , Via Projects and Data, Open , Projects and Data, Select , Reorder, Choose the project to which the data order relates, Via the Project Proposal, Go to the Data packages section in the project proposal, Follow the link Create a new order in the text at the top of the page, A new data order is created automatically, Once the data order has been created, a new section called , Order, appears in the navigation menu. Here, you can choose whether to order , register data, , , external data, , or , population creation, ., Please note that for a new project, a data order can be created once a project proposal has been set up, but it can only be submitted after the project proposal has been submitted., How to Order Register Data, Under Register Data, select the registers that should be included in or updated for the project. You can only choose registers from data packages that have either been requested or approved in the project proposal., If the project proposal has already been approved and you wish to use registers from data packages that are not yet approved, you must create a resubmission. Registers from new data packages will only be processed once the resubmission has been approved., Before selecting registers, you may specify the , Preferred order period, at the top of the page if the data should only be delivered for a limited time period., Under , Choose populations, , choose which populations the registers should be extracted for. Under , Distribution of registers on populations, , specify which registers should be extracted for which populations., If a full register extract is required, this must be indicated in the project proposal under the population description. The full register will then automatically appear as a population in the data order. If the project has previously been approved for a full population but this option does not appear, you should contact the project owner at Statistics Denmark., If a population is uploaded to the project, it must be ordered as a population creation, as this is a prerequisite for it to be selected., How to Order External Data, If the project uses data that is not register data, this should be added as , External Data, ., External data is added by:, Creating an order (see above), Selecting the plus sign next to , Processing of external data, Entering a title, data source type (dropdown menu), and a brief description, Uploading relevant attachments and variable lists. Read more about the requirements for , linking of external data, External data is currently linked to populations in the same way as register data, and the distribution is specified per population., How to Create a Population, If there is a need to create populations or if external populations are used, these must be created under , Population creation, . Once the population has been created, it can be selected in the data order., To create a new population:, Click , Description, under , Population creation, in the navigation menu, Select , Add Population, Provide a descriptive title, Briefly and precisely describe who the population includes and how it is defined, Upload any relevant attachments, You must also indicate whether the population is uploaded or should be created by Denmark’s Data Portal. If the population is created from a project database, this should be marked with a checkmark., If an existing population needs to be updated, select , New Version, . An overview of the project’s populations will be displayed. Select one, and the system will automatically create a new version that can be further edited., Summary, Once the data order has been completed, a full summary is displayed. It is recommended to review this carefully to ensure that all necessary data has been included. The data order can then be submitted., Note:, For new projects, the data order can only be submitted once the project proposal has been submitted. For already approved projects, a data order can always be submitted within the framework of the most recently approved project proposal., Questions and answers about data orders, Data orders, Is a data order always required to have data transferred to a project? , Yes. A data order must always be created and submitted, and it also serves as documentation of which data are included in the project., Can a data order contain multiple elements, such as register data, external data, and a population? , Yes. When completing the data order, you may submit your entire order at once. However, an expansion requires that the project proposal is updated. If you want to order register data from a new package and already approved external data, you may create two separate orders. The order for external data can be submitted immediately, while the order for register data requires a resubmission of the project proposal before it can be submitted., Can I cancel an order that has been created? , Yes. You can cancel an order before it is sent to Statistics Denmark by going to ‘Projects and data’ and clicking the three dots next to the order. Here you can select ‘Terminate order’., Does the data order replace the previous email correspondence with Statistics Denmark? , It does not fully replace previous email correspondence. Price quotes will still be sent by email, and clarifications and guidance will also continue to take place by email or phone., Data packages, Can data be ordered from data packages that are not approved? , Only if the project proposal is still open. When selecting a register from a non-applied-for data package, the package will be added to the project proposal. If the project proposal is already approved, registers can only be ordered from approved data packages. In this case, a resubmission of the project proposal is required to argue for the necessary data packages., Do data orders for register data need approval from Statistics Denmark when the data package is already approved?, No. A data order does not require additional approval, but a staff member at Denmark’s Data Portal must process and price the data order according to the project’s pricing model., Does it cost anything to add new registers within an approved data package?, It depends on the project’s pricing model. Projects on the new pricing model have all register orders within an approved package covered by the package payment and receive them without additional charges. Projects on the old pricing model pay for register deliveries as usual. All projects will transition to the new pricing model with their first data order after 31st of December 2026., Variables, If only a few variables from a register were previously delivered, can the entire register now be transferred?, As a general rule, all variables in a selected register are delivered. Unless you wish to limit the variables, no further action is needed., If a register is missing a variable in an existing project, what should be done? , If a variable is missing, you may order the register again and receive all variables., Populations, Do all projects need to specify a population?, Yes. All projects must specify at least one population in order to order data. For projects with multiple populations, you must indicate which population the data should be extracted for. For projects with only one population (e.g., full register extract), that population will be preselected. If new population delimitations are needed for register data, the population creation must be ordered. It can then be selected as the basis for delimiting register data., Must a population always be specified in a data order?, Yes. A data order must include an approved population (e.g., full register extract)., Project databases, How is register data handled if it was previously ordered directly from Statistics Denmark but now exists in the project database?, Each data order is independent of previous orders. The data order indicates whether data will be delivered from the project database or from Statistics Denmark. There are no restrictions based on where data was previously delivered from., Can future years still be pre-ordered?, Yes. When selecting register data, you can open each dataset via the shopping cart and complete ‘Pre-order’. At present, you must always create a data order when retrieving data from the project database., Why order population creation via the project database?, If the project requires a delimited population, the project database may choose to create it. If register data is needed that the project database does not have, Denmark’s Data Portal can extract register data for the population created by the project database., Can the data manager still create populations manually?, Yes. The data manager can still create populations independently.

    https://www.dst.dk/en/TilSalg/data-til-forskning/anmodning-om-data/oprettelse-af-databestilling

    Registers and reference types

    Statistics Denmark has gathered a vast series of historical register data in our databank of basic data, which users can access via the platform DDP App. Denmark’s Data Portal manages the databank of basic data and handles access to the platform, support, etc. Most registers in the databank are updated at least once a year in connection with release of the register-based statistics (, see Scheduled releases, ). , The data safari and the List of registers and variables (below) both show the registers in DDP App, and here you can see variables for the individual registers. The documentation of variables is available in Statistics Denmark’s , documentation system, ., Go to Data safari , Go to List of registers and variables (in Danish),  , Overview of rerun registers (in Danish), Genkørte registre 2025-3. kvt (pdf), Genkørte registre 2025-2. kvt (pdf), Genkørte registre 2025-1. kvt (pdf), Genkørte registre 2024-4. kvt (pdf), Genkørte registre 2024-3. kvt (pdf), Genkørte registre 2024-2. kvt (pdf), Genkørte registre 2024 - 1. kvt (pdf), Genkørte registre 2023 - 4. kvt (pdf), Genkørte registre 2023 - 3. kvt (pdf), Genkørte registre 2023 - 2. kvt (pdf) , Genkørte registre 2023 - 1. kvt (pdf), Genkørte registre 2022 (pdf),  , Reference types, Registers in the basic data overview are compiled by means of different reference types. Next to each register in the basic data overview, you can see which reference type a register has: ’Status’, ’Statusperiode’ (status period), ’Forløb’ (longitudinal) or ’Hændelse’ (incident)., Status, The reference type shows the status for a given date. For example, LONN (structure of earnings), which shows what a citizen earns as of the register date (e.g. 31 December 2021). Or BEF, which shows the population as of the quarter date (including status of residence, age, family, etc.)., Data definition: Clear status as of a given date. The population delimitation and all data content is focused on the date., Status period, This reference type shows the period status, where the population is delimited as of a given date, but the variables contain summed up data for a specific period. For example, IND, which contains the labour income for a year (the period appears from ’Opdateringsfrekvens’ (update frequency) in the basic data overview). Other examples of status period registers: PERSBEST (board members and managers), MFR (medical birth register), HANDICB (financial support for disability cars), DMRB (motor vehicles). It is not always easy to see what is being summed up., Data definition: The population delimitation is made as of a given date, but the content of the variables is accumulated over a given period. The period cannot be deduced from dates in microdata, but from the indicated period (shown under ‘Opdateringsfrekvens’ (update frequency)) – meaning that content in for example amounts, volumes, quantities etc. is aggregated over the indicated period (e.g. a quarter, a year)., Longitudinal, Here, data covers a longitudinal study. There will always be just one version of the register available. For example, UDD, which contains Highest educational attainment. Or BEFADR, which is an address key register (where e.g. 1.4m addresses changed key on 1 January 2007 in connection with the local government reform). When a longitudinal register is updated, the individual dataset is updated. This is why there is always only one dataset for a longitudinal register., Data definition: The definition of longitudinal data is that data contains a start date and an end date., Incident, Here, data covers an incident. For example, UDFK, which contains primary and lower secondary school marks (does not include a date but a school year), or OPHGIN (basis of right of residence for immigrants). When a longitudinal register is updated, the individual dataset is updated with new incidents. This is why there is always only one dataset., Data definition: The definition of incidents is first and foremost that data contains a date - only one date - for the occurrence of the incident, and will usually also have one incident type attached., Documentation for the use of registers and data packages, Statistics Denmark has prepared a memo describing the coherence between several of the most used registers in Statistics Denmark’s microdata scheme and their connection with the published statistics., The social statistics registers in Statistics Denmark consist of comprehensive data collections, which have been built and extended since the early 1980s. Data is of high quality and comprises the whole population. This gives the users of data unique possibilities of analysis, allowing them to analyse both status at a given point in time and the development over time., The memo is primarily intended for researchers, analysts and other users of microdata who want to obtain deeper insight into the quality of the coherence between the different registers. , Read more on Documentation for the use of registers (in Danish), Datapackages (pdf - in Danish), Especially on the Data Warehouse for Business Statistics, In January 2024, Statistics Denmark launched the new Data Warehouse for Business Statistics – a significant extension and improvement of the existing business registers. , The new warehouse ensures wider and better access to anonymised data on enterprises and facilitates extraction of unique data by linking data across more statistical registers. The data warehouse also facilitates linking of business statistics and social statistics at micro level, the so-called ‘Linked Employer-Employee Data’ (LEED). , Read more in , this brochure (pdf), or see , the presentationen of The Data Warehouse for Business Statistics on 30 November 2023 (pdf), .

    https://www.dst.dk/en/TilSalg/data-til-forskning/generelt-om-data/registre-og-referencetyper

    Prices and price agreements

    The price of a Denmark's Data Portal's assignment is based on the time it takes to solve the part elements of the assignment. We have two types of price agreements: , fixed-price agreements and framework agreements, . You can also commission a combined fixed-price and framework agreement. Furthermore, you will be paying rent for disk space for active projects on Statistics Denmark’s servers. If you have your own-hosted server set up at Statistics Denmark, you must pay for the set-up and for routine maintenance., Table 1: Hourly rates and renting of disk space, Rates 2026,  , Public institutions*, Private institutions, Pricemodel for existing projects, Hourly rates, DKK 1.674 excl. VAT, DKK 2.077 excl. VAT, Pricemodel for new projects, Data packages per unit, DKK 4.400 excl. VAT, DKK 5.500 excl. VAT,  , Project access per unit, DKK 700 excl. VAT, DKK 900 excl. VAT,  , Hourly rates, DKK 1.100 excl. VAT, DKK 1.400 excl. VAT, Renting of disk space, DKK 10,8 excl. VAT per 5 Gigabyte (GB) disk space per quarter, Note that for project databases, the price for data packages is 17.600 kr. excl. VAT (public institutions)/ 22.000 kr. excl. VAT (private institutions), thus 4 times the price of projects under the researcher scheme or subprojects. , *For public authorised institutions, a special contribution is given towards the hourly rate from the Danish e-infrastructure Cooperation via KOR., Denmark's Data Portal offers paid-for services to users of Statistics Denmark’s microdata schemes. Initially, we offer consultancy in connection with questions for clarification of an assignment. For this, we invoice the actual time used at the hourly rate in force at any time. This also applies should you decide to not proceed with the assignment. If we subsequently enter into a specific fixed-price agreement for the assignment, the service and consultancy will be included in this (within reason)., Fixed-price agreements and framework agreements, Both fixed-price agreements and framework agreements are based on the time it takes to process and deliver an assignment. The time is charged by the hourly rate in force at any time. Denmark's Data Portal uses standardised prices based on the average estimated time consumption for a given service assignment., Fixed-price contract, The price is determined based on an estimated time consumption for a given service. With a fixed-price agreement, you thus pay the same price for comparable services., Further on the structure of fixed-price agreements, The price of a fixed-price agreement is based on one or more of the following assignment elements. The below table shows the various elements of the assignment, which are charged on the basis of fixed-price agreements and associated time consumption., Assignment element, Time consumption, Project proposal (processing and approval hereof), 2, Extraction of one data set from register, 1.05, Extraction of two data sets from register*, 1.09, No additional time charge in case of data extraction from register <= 15 variables,  0, Additional time charge in case of data extraction from register > 15 variables,  0.5, *The price increases with 0,047 hours pr. dataset, Further, the assignment price consists of a fixed extra charge for additional services and consultancy of 20 per cent of the price of the assignment part elements, which are not necessarily in direct contact with you. Such part elements are, for example, participation in meetings etc., internal documentation, documentation requirements, invoicing etc., Data extraction from registers include time consumption for e.g. programming, pseudonymisation and control of data extractions from , Denmark's Data Portal's databank of basic data, . The fixed price agreement may also include time consumption for processing and pseudonymisation of a population submitted to Denmark's Data Portal from other sources than the Denmark's Data Portal's databank of basic data., Framework agreements, The price is variable and the service is charged according to the actual time consumption on the specific service. We invoice every hour of work commenced. If we have used less than one hour on an individual assignment, we invoice for the first hour of work commenced., Further on the structure of framework agreements, The following assignments, Denmark's Data Portal carries out based on a framework agreement:, Population creation as well as case control populations. The service covers counselling regarding the extraction description as well as the subsequent population creation. , Data from statistical division or Survey in Statistics Denmark. This is charged via a framework agreement based on the actual time consumption. The service includes, for example, data extraction from register in the statistical division, pseudonymisation and direct communication and consultancy, back office activities and internal communication., Data submitted from sources outside Statistics Denmark. This is charged via a framework agreement based on the actual time consumption. The service includes control and pseudonymisation of the submitted data. See estimated time consumption and prices for delivery of submitted data under , Linking other data, .,  , Part elements of an assignment, The total price of a given assignment depends on the time it takes to solve the assignment and the part elements involved. For that reason, the price may vary from one assignment to the next. For example, the price depends on how many registers that are required to create a population, or from how many registers the project requires extraction of data., See the part elements of the assignment, Project proposal, : Processing and approval. The project proposal is charged via a fixed-price agreement, which is based on a fixed time value corresponding to two hours., Population, : Population creation is charged via a framework agreement, which is based on the time it takes Denmark's Data Portal to create the population., Standardised data from Statistics Denmark’s databank of basic data, : This is charged via a fixed-price agreement, which is based on fixed time values per number of registers and variables., Additional services and consultancy, : Direct communication and consultancy, back office activities and internal communication. This is charged via a fixed-price agreement that is based on fixed time values depending on the scope of the assignment., Additional data from Statistics Denmark, : Data extraction from register, direct communication and consultancy, back office activities and internal communication. This is charged via a framework agreement that is based on actual time consumption., Data from other data providers, : Processing of data submitted from you or other data providers. The data processing is charged via a framework agreement that is based on actual time consumption., Special data from Statistics Denmark, : Data compiled especially for the users (not in connection with statistics). The compilation is charged via a fixed-price or framework agreement that is based on actual time consumption for compilation divided by expected sales.,  , Examples of price calculations, Example of price calculation for a new research project, The following price calculation includes processing of the project proposal as well as data extraction on demographics (BEF), educational attainment (UDDA), income (FAIK and IND) as well as employment information (DREAM). The price calculation is based on a project with full register extraction where the user creates the population. , Since Denmark's Data Portal rounds up to the nearest whole number due to the standardised price calculation method, the price is calculated according to the following table., Assignment element, Time consumption, Price, Project proposal, 2, Data extraction from register, 6, Data extraction from register > 15 variables, 0,  , Subtotal, 8 ,  , Additional services and consultancy (extra charge 20 per cent)*, 1 ,  , Total hours used, 9,  , Public user,  , 9 hours * 1,674.00 DKK = 15,066.00 DKK, Private user,  , 9 hours * 2,299.00 DKK = 20,691.00 DKK, *The additional service fee corresponds to 20% of the hours for processing of the project proposal, data extraction as well as other requirements (programing/data)., Please note that the price calculation does not include population creation. If Denmark's Data Portal should create the population, this will be carried out based on a framework agreement., Example of price calculation for a new research project enriched with data from the Danish Health Data Authority, This price calculation includes processing of the project proposal, population creation (based on a framework agreement) as well as data extraction on demographics (BEF, BEFADR, VNDS, DOD) and registrations in the National Patient Register (LPR_ADM, LPR_BES, LPR_DIAG, LPR_SKSUBE). The population consists in persons with a consumption of some specific types of medicinal products found via variables in the Danish National Prescription Registry (LMDB2005-2015). These persons must not be registered as emigrated in the register ‘Historiske vandringer’ (VNDS), meaning that they must be marked INDUD_KODE=U. Furthermore, they must not be registered in ‘Døde i Danmark’ (DOD). Moreover, the population from Statistics Denmark is transferred to the Danish Health Data Authority for enrichment with data from the Danish Pathology Register. The processing and pseudonymisation of data from the Danish Health Data Authority are not included in the price., Assignment element, Time consumption, Price, Project proposal, 2, Data extraction from register, 14, Data extraction from register > 15 variables, 0,  , Subtotal, 16 ,  , Additional services and consultancy (extra charge 20 per cent)*, 4 ,  , Total hours used, 20,  , Public user,  , 20 hours * 1,674.00 DKK = 33,480.00 DKK, Private user,  , 20 hours * 2,299.00 DKK = 45,980.00 DKK, Framework agreement for the population creation, Assignment element , Estimated time consumption**, Price, Population creation, 5, Public user,  , 5 hours * 1,674.00 kr. = 8,370.00 DKK, Private user,  , 5 hours * 2.299,00 kr. = 11,495.00 DKK, *The additional service fee corresponds to 20% of the hours for processing of the project proposal, data extraction as well as other requirements (programing/data)., **After the population is created, the time actually sepnt by Denmark's Data Portal is billed at the hourly rate applicable at any given time.,  , Determination of the hourly rate, The hourly rate is determined once a year based on four part elements. The final hourly rate consists in a number of part elements including a development contribution of 3 per cent., Surcharge, : Income forecast for the current year and accumulated surplus/deficit from previous years, Overhead Statistics Denmark and externally funded activities, : Joint expenses, for example for staff, rent, electricity etc. and common administration of externally funded activities, such as maintenance of data bank of basic data, development of externally funded activities etc., Overhead Denmark's Data Portal, : For example, authorisation of new institutions, control of transferred files, sanctioning and general development of the microdata schemes and Statistics Denmark’s Data Portal etc.,  , Other services, Renting of disk space, Projects take up space on Statistics Denmark’s servers. For that reason, we have introduced renting of disk space, so that you as a user are made aware of how much storage capacity your project takes up on Statistics Denmark’s servers. You will only pay for disk space for active projects using a storage capacity over 5 Gigabyte (GB) on the servers. An active project is defined by a minimum of one user logging on to the project within a quarter., Disk space renting is charged on a quarterly basis, and you are invoiced for all projects for which your institution is data controller. For an individual active project using a storage capacity of more than 5 GB, the institution will be charged quarterly in units of 5 GB. Disk space renting will be charged, regardless of the reason for logging onto the project and how often during a quarter., Hosted server, Statistics Denmark also offers to host your own servers, which will be located at Statistics Denmark. , Read more about requirements and prices for hosted servers ,  , FAQ on prices, We have gathered some of our frequently asked questions on prices below., FAQ on prices, Why does the price vary from one assignment to the next?, An assignment is composed of several part elements. The assignment is priced based on the part elements of the assignment. This is why the price may vary, for example depending on the number of registers used for population creation, populations from other data providers or the number of registers from which the project needs data extraction. The part elements of the assignment are described in the section “Part elements of an assignment”., The hourly rate has changed over the years – why?, You can see the changes in the hourly rates of Denmark's Data Portal below., All institutions, 2013, 1,248 DKK, 2012, 1,187 DKK, 2011, 1,167 DKK, 2010 2nd half, 1,197 DKK, 2010 1st half, 1,229 DKK, 2009, 1,229 DKK , 2008, 1,229 DKK, Prices after 2014, Private institutions, Other public institutions, 2024, 2,130 DKK, 1,538 DKK, 2023, 2,130 DKK , 1,568 DKK,  , 2022, 2,130 DKK, 1,568 DKK,  , 2021,  2,168 DKK, 1,735 DKK,  , 2020, 2,202 DKK, 1,745 DKK ,  , 2019,  2,202 DKK, 1,607 DKK,  , 2018, 2nd half,  1,749 DKK, 1,050 DKK,  , 2018, 1st half,  1,749 DKK, 1,050 DKK,  , 2017,  1,650 DKK, 1,050 DKK,  , 2016,  1,650 DKK, 1,050 DKK,  , 2015,  1,750 DKK, 1,050 DKK,  , 2014,  1,650 DKK, 1,050 DKK, There are various reasons for the price changes., Each year, we adjust the hourly rate for surcharge, which accumulates the surplus/deficit of previous years. Moreover, we include an income forecast for the current year, which can cause variations from one year to the next., Public institutions are not allowed to generate a profit. For that reason, Statistics Denmark regularly adjusts the hourly rates so that they reflect the actual costs and make the accounts balance., In 2014, a distinction was made between private and public institutions, when Denmark's Data Portal for the first time received a special contribution from the coordinating organ for register research, KOR, among others, supporting the hourly rate for public users. This accounts for the difference in price depending on whether a private or a public institution owns the project., Why must I pay for other variables to be added to my project?, Changes in an already existing project must be described in the project proposal and/or the variables documentation. Furthermore, they must be documented and the approval must be renewed in Denmark's Data Portal. The only exception that does not require renewed approval is an update of an already approved population or variable., The approval requires a number of processes, which can be anything from dialogue between you and Denmark's Data Portal to a review of the project and its variables documentation for renewed approval of the project. The process can vary considerably depending on the project, and the time consumption up until the approval is in the range of 1-4 hours whether for new projects, updates or extensions. The price of processing a project proposal is therefore set at two hours. If the time consumption exceeds four hours, a supplementary agreement is made in the form of a framework agreement to cover the actual processing time., We encourage you to make a professional assessment of when and how often you apply for approval of project changes,, so that we can reduce the number of ongoing and minor changes., For how long is a quotation valid?, A quotation is valid for 30 days starting from the date of the quotation. After that, we recalculate the quotation at the current hourly rate., How we charge for a project database? , The charge is based on an annual contract with a fixed-price agreement that includes update of agreed register data in the project database as well as a possible framework agreement for additional services, such as deliveries from the project database to sub-projects and consultancy according to the needs of the project database., The establishment of a project database follows the same pricing guidelines as a new project. Since the project database has a longer time perspective than a project, an annual contract on updating is entered. Thus, the pricing is based on an expected average time consumption for the service., The settlement period appears from the below table. The fixed-price agreement for updating of the project database is settled together with the Q2 settlement of ‘Additional services’. ‘Additional services’ are settled quarterly., Invoiced in the calendar year yyyy, Invoiced in the calendar year, The annual contract covers, Mid-January, Mid-April, Mid-July, Mid-October, Mid-January, Data extraction, Fixed-price agreement for data, Additional services, Consumption Q4 from the previous year, Consumption Q1, Consumption Q2, Consumption Q3, Consumption Q4, Why do prices of comparable services vary?, The price of services is based on past experience and averages. Comparable services may imply small differences in the various part elements that affect the price, for example, the price of processing external data (submitted from other data providers) compared to processing of standardised data extractions from registers in Statistics Denmark’s databank of basic data. If project changes appear later in the process, the price may change based on the changes. Furthermore, the hourly rate is calculated annually, which can also affect the assignment price., What is the background for Statistics Denmark’s prices?, Statistics Denmark is the central producer of statistics in Denmark, and the costs of carrying this obligation as an authority are covered by the Danish Finance Act., The data that we collect and store can be used for scientific and statistical surveys under Statistics Denmark’s researcher scheme. Only authorised research and analysis environments are granted access to data, and we charge for making data available for the surveys., In principle, the price must cover the costs associated with performing the assignments from the initial dialogue to the final dialogue no later than 30 days after the assignment has been delivered., The price must further contribute towards the costs associated with:, Consultancy on the use of data in the individual project., Administration of the scheme, for example authorisation, Data access rights, Standardisation of register data, Development of our user services, Securing continued high data security and data confidentiality, Overhead costs, Statistics Denmark’s pricing is subject to the rules on externally funded activities in the public sector and is checked by the National Audit Office of Denmark. Income and expenditure must balance, and the income from services must not be used to fund the obligations of the authority. The financial balance is continuously monitored across a ten-year average.

    https://www.dst.dk/en/TilSalg/data-til-forskning/mikrodataordninger/priser-og-prisaftaler

    Databank of basic data

    Here you can read a general description of the databank of basic data in Denmark’s Data Portal (DDP)., Basic data (also called ‘DDP basic data’ or ‘data in the databank of basic data in Denmark’s Data Portal’) refers to the microdata that DDP offers to external users for research and statistical purposes. Statistics Denmark (DST) has collected a wide range of register data with historical information in a bank of basic data within the DDP App. The various registers come from both external sources and internal statistical offices. Thematically, the data cover a broad spectrum, and the statistical unit may be individuals, addresses, enterprises, library loans, motor vehicles, and more. All basic data must comply with a set of standards for formats and naming etc., The data undergo extensive processing before being placed in the bank of basic data. There are several reasons for this:, Standardization saves users time-consuming preparation: by ensuring uniform data, external users can avoid a significant amount of manual data processing., Key variables must be standardized to enable data linkage: combining data across years and registers requires a common standard for key variables., Key variables must be standardized to enable pseudonymization: data can only be pseudonymized correctly if variables follow fixed standards and naming., Purpose of the databank of basic data, The purpose of the databank of basic data is to collect microdata for research and analysis in a way that makes it easy and straightforward to make microdata available to researchers., Content and use of the databank of basic data, DDP aims to ensure that all DST data from the official statistical program are available as basic data. This primarily includes microdata related to individuals, enterprises, or addresses., DST also holds data that are not part of the official statistical program but which DDP has received or collected for various reasons. This type of data is also made available as basic data to support reuse, rather than requiring the statistical offices to design customized extracts for the users., To qualify as basic data, a number of conditions must be met. For certain data, special considerations regarding data confidentiality, funding arrangements or data quality may influence how the data can be used. DST enters into agreements with other authorities (and data owners) for regular deliveries of register data that can be made available to researchers. These data are also placed in the databank of basic data. Read more under , Data from other data providers for the databank of basic data, ., Before data may be used on the research server, variables that can directly identify individuals undergo pseudonymization. This means that all variables containing identification information such as CPR numbers, CVR numbers, addresses, and property numbers, are recoded in a pseudonymization process before being transferred to the user’s project. Each register includes a marking of which variables must be pseudonymized. When new variables are added to a register, DDP assesses, together with the data owner and based on the data confidentiality policy, whether the variables must be pseudonymized before the data can be released for research and analysis., Applying the procedures and guidelines described, ensures that data stored in the databank of basic data and presented within DST follow a standardized format. This makes it easy for researchers to access the data and navigate the available datasets. Read more about where to find documentation for basic data on the page , Documentation of data, .

    https://www.dst.dk/en/TilSalg/data-til-forskning/generelt-om-data/grunddatabanken