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Statistics based on roads and addresses

Reach your target audience with statistics on roads and addresses, This product allows you to rank roads or streets in a particular geographical area according to where you are most likely to hit a specific audience., Get assistance selecting roads, The product is designed for those who want to reach a specific target group, for example in connection with marketing or other promotional activities. For example, if your company manufactures child bike seats, then this product will help you to only distribute advertising matter on the roads where there is a high proportion of families with at least one child under four years., Multiple options, You can rank the roads or streets in many different ways, for example after the following variables:, household income, educational level, age or sex, List of variables, Documentation - standard variables for statistics on roads and addresses, Combine information, You can also combine the different variables in order to reach exactly the target audience of your interest. Again, if you sell child bike seats at the high end of the market, you can combine the number of families with at least one child under four with a level of household income., Statistics based on roads and streets step by step, Roads are ranked based on statistics, All households are first divided into smaller groups according to the type of road where they are located and, if relevant, according to the type of house. Subsequently, households are grouped into clusters or groups of at least 400 households, which then form the basis for statistics, e.g. household income in intervals. The clusters of households can be formed in three different ways in increasing detail and thus also in precision., The level of detail is also reflected in the price. You can read more about how we create household clusters here:, How do we create clusters, Household clusters with type of housing, Household clusters without type of housing, Prices, Prices per variable vary between approx. DKK 10,000 for the simplest ranking for one municipality to approx. DKK 70,000 for the most detailed variant for the entire country. See the detailed price list here:, Pricelist_RoadsAddresses_2026 - English,  , Ordering, Please click on the button below and fill out the form. , ORDER, Please note that by ordering you accept Statistics Denmark's General Terms and Conditions of Agreements., Contact information, DST Consulting, tel: +45 3917 3600, Allan Hansen, tel: +45 3917 3168, Related products, Statistics on the Danish national grid, Staistics based on distances or neighbourhoods,  

https://www.dst.dk/en/TilSalg/produkter/geodata/vejsegmentering

Joint Data Responsibility

At Denmark Statistics (DST), we offer users under the Researcher Scheme the option to enter into ‘Joint Data Responsibility’, which enables collaboration on a single project between two authorised institutions, where responsibility for the data is shared equally., The project is created under one authorised institution, and users affiliated with the second authorised institution, who are to participate in the project, are linked via a user and association agreement. Both institutions must confirm via email to the contact person in Denmark's Data Portal that they wish to establish a project under joint data responsibility between [authorisation number – name of institution 1] and [authorisation number – name of institution 2] for project [project number]., In addition, it must be clearly stated in the project description that the project has been confirmed and approved for joint data responsibility between the two institutions., Sanction Framework for Projects under Joint Data Responsibility, In the event of a breach of DST’s rules for working with microdata, institutions with projects under joint data responsibility are subject to the applicable sanction system specified for projects under the Researcher Scheme on DST’s website: , Sanction Rules., Sanctions Affect Both User and Project Simultaneously, If a breach of DST’s rules for working with microdata occurs in projects under joint data responsibility, it may result in sanctions against the user who has transfered the data. For example, DST may decide that the user is sanctioned with a quarantine period during which the individual user does not have access to the DDV App. This sanction will also affect the relevant project from which the data was extracted, meaning that all access to the project will be closed for the same quarantine period that applies to the user who transfered the data., Thus, the sanction policy does not differ from the applicable sanction rules for projects and users without joint data responsibility., Institution-Level Sanctions Affect Both Institutions, The sanction framework for institutions likewise follows DST’s applicable sanction rules. Accordingly, both institutions must report when a breach occurs, and repeated or serious breaches may result in measures such as temporary or permanent closure., In line with the applicable sanction framework, the sanctioning process will take into account the history of the two institutions. This means that the same offense may affect institutions differently if one institution has a long history of breaches while the other has not previously violated the rules., Institutions must account for errors in data transfer as per normal practice and must indicate that the project is subject to joint data responsibility, so that Denmark's Data Portal transfer team can take this into account when processing any potential breaches.

https://www.dst.dk/en/TilSalg/data-til-forskning/anmodning-om-data/faelles-dataansvar

The research machine

Users of the microdata schemes can choose to do their work on Statistics Denmark’s research machine – a server that can accommodate several separate projects. , Here you can find guides for set-up, login and use of Statistics Denmark’s research machine:, Connection to Researcher servers at DST - Windows users, Connection to Researcher servers at DST - Mac users, Connection to Research Servers at DST - Linux Users, How to change your password, How to reset your password, Connection to research servers at Statistics Denmark from abroad,  , Use of disk space by the projects, In the below overviews of disk space (in Danish), you can see how much space your research project has taken up on the research servers in recent years., Diskforbrug 2025, 1-2. kvartal, Diskforbrug 2024, Diskforbrug 2023, Diskforbrug 2022, Diskforbrug 2021, Diskforbrug 2020, Diskforbrug 2019, Diskforbrug 2018, Diskforbrug 2017, Diskforbrug 2016, Diskforbrug 2015, Diskforbrug 2014, Diskforbrug 2013, Diskforbrug 2012, Diskforbrug 2011, Diskforbrug 2010, AI Tool for Code Assistance, On the research machine and hosted servers, An AI-based code assistance tool has been developed. The purpose of the tool is to help users of Denmark’s Data Portal with various programming tasks. The tool allows you to prompt a model that helps you write and understand a wide range of programming languages, including SAS, SPSS, Python, Stata, and R, which are the five languages supported on the research machine., How to get access, Log in to the research machine:, The AI code assistance tool is located on the research machine. To gain access start by logging in to the research machine via remote.dst.dk., Open the AI-tool:, Click on the icon named “AI code-help”, which is on the desktop., Log in to the AI tool:, After opening the AI-tool, a page will appear asking for login information. Here you must use your project-IDENT (without @dstfse.local) and your Windows password., Once you have done this, you will have access to the AI tool’s main page, and you can begin prompting. Please note that even though the tool runs locally on the research machine, , you must not enter data of any kind., The tool is intended solely for code assistance., For security reasons, your dialogues with the tool will not be saved after the tool is closed. If there are code examples you wish to keep for a longer period, you should therefore save them in the work data folder., The model underlying the tool is the publicly available qwen2.5-coder, produced by the company Ollama. If you want more information about the model’s functionality, we refer you to Ollama’s website.

https://www.dst.dk/en/TilSalg/data-til-forskning/analyseplatform/forskermaskinen

REGN80: Accounts statistics (DB07)

region, industry, items and time
2019-2023 (-)

https://www.statbank.dk/REGN80

Tables in StatBank

VANDRG1: Abstraction of water (Physical water accounts)

industry, water type and time
2010-2024 (1,000 m3)

https://www.statbank.dk/VANDRG1

Tables in StatBank

ATR112: Working Time Accounts (seasonal adjustment) (quarter)

industry (DB07 10- and 19-grouping), type, socioeconomic status and time
2008Q1-2025Q4 (-)

https://www.statbank.dk/ATR112

Tables in StatBank

Linking of external data

Statistics Denmark, Service Desk

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

Producer and import price index for commodities

Hvad er udviklingen i producenternes salgspriser og importørernes købspriser? Hvad er prisudviklingen for udvalgte varegrupper såsom; jern og stål, træ eller plast?

https://www.dst.dk/en/Statistik/emner/oekonomi/prisindeks/producent-og-importprisindeks-for-varer

Subject page

SPOP2K: Indices of Service Production

industry, seasonal adjustment and time
2021Q1-2025Q4 (Index)

https://www.statbank.dk/SPOP2K

Tables in StatBank

MRS1: Environmental taxes

industry, environmental category and time
1995-2024 (m DKK)

https://www.statbank.dk/MRS1

Tables in StatBank