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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., By default, all variables within a given register are selected. If you wish to limit the selection at the variable level, click the ˅ next to Add and then select , Limit variables, ., 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 rate and renting of disk space, Hourly rate for private institutions, DKK 2,299 excl. VAT, Hourly rate for public institutions*, DKK 1,674 excl. VAT (after deduction of the special contribution from the Danish e-infrastructure Cooperation via the coordinating organ for register research, KOR)., Renting of disk space, DKK 16 excl. VAT per 5 Gigabyte (GB) disk space per quarter, *For public authorised institutions, a special contribution is given towards the hourly rate from the Danish e-infrastructure Cooperation via KOR.,  , Table 2: 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

Documentation of statistics: Hospitalization

Contact info, Personal Finances and Welfare, Social Statistics , Line Neerup Handlos , +45 26 64 03 00 , lha@dst.dk , Get documentation of statistics as pdf, Hospitalization 2024 , Previous versions, Hospitalization 2023, Hospitalization 2022, Hospitalization 2021, Hospitalization 2019, Hospitalization 2018, Hospitalisation 2017, Hospitalization 2016, Hospitalization 2015, Hospitalization 2014, Hospitalization 2013, The purpose of the Hospital Utilisation Statistics is to shed light on the connection between hospitals stays and social and demographic conditions. The statistics have been compiled since 1990, but are comparable in their current form only from 2017 onwards., Statistical presentation, The statistics are an annual inventory of stays at public and private somatic and psychiatric hospital wards within one calendar year. The statistics show how hospital stays vary with demographic and social factors, such as residence, sex, age, educational level, labour market affiliation and relatives. The statistics are published in News from Statistics Denmark and in the StatBank., Read more about statistical presentation, Statistical processing, The statistics are based on data retrieved from the National Patient Registry, which is shared with Statistics Denmark by the Danish Health Data Authority. Background data from Statistics Denmark are linked to the registry, and summaries and counts are produced — for example, the number of hospital stays and patients in public and private somatic and psychiatric hospital departments during the calendar year., Read more about statistical processing, Relevance, Public and private stakeholders, as well as the general population, can use the statistics to extract data on the population’s hospital utilisation for various analyses, research, public debate, etc. The statistics make it possible to produce figures for specific diagnosis groups and to link information on hospital utilisation with sociodemographic factors such as place of residence, education, labour market attachment, and origin. This is made possible by linking data from the National Patient Register with population register data from Statistics Denmark., Read more about relevance, Accuracy and reliability, The National Patient Register is validated by the Danish Health Data Agency and the accuracy of the register data must be considered to be high because the registration has a long tradition and a high priority for administrative purposes. Accordingly, the overall accuracy of the Hospital Utilisation Statistics is high. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published within approximately nine months after the end of the reference period., Read more about timeliness and punctuality, Comparability, The statistics have been developed since 1990, but are only comparable in their current form from 2017 onwards., Eurostat and the OECD make comparable statistics in this field. There are a number of organizational and institutional conditions that we must keep in mind when comparing countries. , Read more about comparability, Accessibility and clarity, The statistics are released in the newsletter Nyt from Statistics Denmark (in Danish only) and the Statbank, Statbank tables on hospitalisation utilisation (https://www.Statbank.dk/20050). Statistical Yearbook and Statistical Ten-Year Review contain selected sections about hospitalisation rates. For further information, go to the , subject page, ., Read more about accessibility and clarity

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

Documentation of statistics

Labour Force Survey (LFS)

How high is the employment rate in Denmark? How many work part time? And how many are working from home?

https://www.dst.dk/en/Statistik/emner/arbejde-og-indkomst/befolkningens-arbejdsmarkedsstatus/arbejdskraftundersoegelsen-aku

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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

Data in general

Denmark’s Data Portal has gathered a vast series of historical register data in a databank of basic data. Here you can find information on the various types of data made available and on the documentation of data., Databank of basic data, Read about the data displayed in Denmark’s Data Portals databank of basic data., Data from data providers to the databank of basic data, See how external data providers get their data displayed in Denmark’s Data Portals databank of basic data., Registers and reference types, See the overview of registers and variables, and read about the different reference types., Documentation of data, Read about how data is documented in Denmark’s Data Portal., Data from other sources, See what data you can access from other statistical authorities.

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

Surveys

Contact Information, Senior Advisor, Bo Lønberg Bilde, , mobile +45 91 37 64 26, Head of Division, Marie Fuglsang, , mobile +45 20 35 39 25, Statistics Denmark conducts surveys for both private and public customers. We carry out nationwide surveys with a random sample of the Danish population and businesses. We can also use our extensive registers as a basis to form a sample. This means that we can carry out interviews among almost any sample in Denmark, such as: , Parents of children in kindergarten , Nurses who completed their training 3-5 years ago , Car owners in the metropolitan area , Export Companies in the capital area , Companies of a certain size in Jutland   , There are many more options than the ones mentioned above. Contact us to learn more about the possibilities., The surveys are carried out either via a web form, using telephone interviews or a postal questionnaire or a combination of these three methods., Delivery, Results from the survey can be delivered as anonymised data on an individual and company level and/or coupled with register data in tables. If you want to analyze data from Statistics Denmark registers coupled with data from the study on an individual or company level this can be done through our Division of Research. Read more about the possibilities here , www.dst.dk/research, ., Price, The price depends on the content and scope of the survey. When the design of a particular survey is settled, we will send you a final price quote. It is also possible to get supplementary questions included on the monthly omnibus survey – an inexpensive way to conduct small studies with high quality.

https://www.dst.dk/en/TilSalg/interview

Statistics on income and living conditions (SILC)

What share of the population is economically vulnerable? How is overall life satisfaction? The survey on Living Conditions is conducted annually in all EU countries.

https://www.dst.dk/en/Statistik/emner/sociale-forhold/levevilkaar/levevilkaarsundersoegelsen-silc

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Documentation of statistics: Survey on Living Conditions (SILC)

Contact info, Labour Market, Social Statistics , Martin Faris Sawaed Nielsen , +45 23 69 90 67 , MFS@dst.dk , Get documentation of statistics as pdf, Survey on Living Conditions (SILC) 2025 , Previous versions, Survey on Living Conditions (SILC) 2024, Survey on Living Conditions (SILC) 2023, Survey on Living Conditions (SILC) 2022, Survey on Living Conditions 2021, Survey on Living Conditions 2020, Survey on Living Conditions 2019, Welfare Indicators 2018, Welfare Indicators 2017, Welfare Indicators 2016, Welfare Indicators 2015, Welfare Indicators 2014, Welfare Indicators 2013, In Denmark EU-SILC (Statistics on income and living conditions) is a combination of survey and register data. The purpose of EU-SILC is to provide a statistics on income, living conditions and risk of social exclusion. Statistics Denmark only disseminate a small part of EU-SILC. Dissemination is by Eurostat primarily., The survey is conducted in all EU member states once a year following the same guidelines. In Denmark the survey has been conducted since 2004., Statistical presentation, SILC consists of data on the composition of the households and their living conditions including questions on how easy it is for the household to make ends meet and the financial burden of the housing costs. Further information is collected on health and position on the labour market etc. These interview questions are then supplemented by a lot of register based information, mainly on incomes, demographics, housing and education. , Read more about statistical presentation, Statistical processing, The subjective data from the interviews are combined with the register based data using the Central personal Register. To adjust for non-response bias, weights are computed and assigned to respondents. This ensures that the survey population match the Danish population on demographics and income levels. , Read more about statistical processing, Relevance, SILC is primarily used by Eurostat and the European Commission. Users of the statistics published in Denmark are mainly the press., Read more about relevance, Accuracy and reliability, Data are based on a survey; hence there is some statistical uncertainty; especially on subgroups. In addition to sampling errors there might be a slight risk of bias. A calibration of the survey is carried out in order to limit any bias and make sure that the sample reflects the population on factors such as demographics and incomes. For the published variables the effect and risk of bias is assumed to be negligible due to the strong correlation with incomes., Read more about accuracy and reliability, Timeliness and punctuality, The data are usually published in December or January following the interview period. There is a risk of delays, due to the many different data sources used to compile SILC - which may not be available in due time., Read more about timeliness and punctuality, Comparability, The published indicators are assumed comparable over time and between countries participating in the EU-SILC., Read more about comparability, Accessibility and clarity, Some main figures are published in Nyt fra Danmarks Statistik and in the statbank. Eurostat publish many figures in the , Eurostat database, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/survey-on-living-conditions--silc-

Documentation of statistics