Data catalogue
Every indicator with type, unit, level and source.
All indicators of the Online Radar and the additional datasets of our reports – sorted by the level at which they exist. Topics and levels are named exactly as in the source catalogue.
- 189
- indicators in the Online Radar
- 94
- of which at all levels down to municipality
- 401
- districts and district-free cities compared
- 57
- additional entries in the reference district Merzig-Wadern
Merzig-Wadern is our reference district, the one we have worked with from the start. Its data holdings are the largest; we are extending the other districts step by step. All sources we use, with publisher and licence, are listed in the source catalogue.
At all levels
94 entries
Indicators we hold for every federal state, every district and municipalities across Germany – where the definition matches, also for the 27 EU member states.
| Indicator | Topics | Type | Unit | Levels | Coverage |
|---|---|---|---|---|---|
| Old-age dependency ratio 2040 (projection) | Population | number | number | Federal stateDistrictMunicipality | 399 / 401 districts |
| Share aged 65 and over | Population | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Foreign residents | Population | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Population change to 2040 (projection) | Population | Change | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Population change since 2011 | Population | Change | % | Federal stateDistrictMunicipality | 398 / 401 districts |
| Education-related migration (ages 18–24) per 1,000 | Population | Rate | – | Federal stateDistrictMunicipality | 399 / 401 districts |
| Average age | Population | Duration | years | Federal stateDistrictMunicipality | 401 / 401 districts |
| Average age 2040 (projection) | Population | Duration | years | Federal stateDistrictMunicipality | 399 / 401 districts |
| Family migration per 1,000 (ages 30–49 and children) | Population | Rate | – | Federal stateDistrictMunicipality | 399 / 401 districts |
| Deaths per 1,000 inhabitants | Population | Rate | – | Federal stateDistrictMunicipality | 400 / 401 districts |
| Natural change per 1,000 inhabitants | Population | Rate | – | CountryFederal stateDistrictMunicipality | 399 / 401 districts |
| Net migration per 1,000 inhabitants | Population | Rate · time series | – | CountryFederal stateDistrictMunicipality | 399 / 401 districts |
| Old-age poverty (basic income support in old age) | Economy/Work | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Unemployed young people (15–24) as share of population | Economy/Work | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Job centrality (jobs per employed resident) | Economy/Work | Rate | – | Federal stateDistrictMunicipality | 399 / 401 districts |
| Local jobs, change over 5 years | Economy/Work | Change | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Employees in industry and construction | Economy/Work | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Employment rate (employees with social insurance) | Economy/Work | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Income tax (municipal share) per inhabitant | Economy/Work | Amount | € | Federal stateDistrictMunicipality | 399 / 401 districts |
| In-commuters (share of employees at place of work) | Economy/Work | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Business start-ups per 1,000 inhabitants | Economy/Work | Rate | – | Federal stateDistrictMunicipality | 399 / 401 districts |
| Basic income support (SGB II) | Economy/Work | Share · time series | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Child poverty | Economy/Work | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Socio-economic deprivation (GISD, 0 = low, 1 = high) | Economy/Work | number | number | Federal stateDistrictMunicipality | 400 / 401 districts |
| Youth welfare spending per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Cash balance per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Local business tax (net) per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 399 / 401 districts |
| Property tax B (built-up land) per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 399 / 401 districts |
| Municipal multiplier, property tax B | Government/Finance | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Investment loans per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Short-term cash loans per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Capital investment per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Core budget debt per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Social benefits per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Government investment grants per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Tax revenue per inhabitant | Government/Finance | Amount · time series | € | Federal stateDistrictMunicipality | 399 / 401 districts |
| Tax capacity per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 400 / 401 districts |
| Levy paid to municipal associations per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Available funding per inhabitant | Government/Finance | Amount | € | Federal stateDistrictMunicipality | 395 / 401 districts |
| Turnout, 2025 federal election | Government/Finance | Share | % | Federal stateDistrictMunicipality | 398 / 401 districts |
| Floor area per dwelling (Census 2022) | Housing | Measurement | m² | Federal stateDistrictMunicipality | 401 / 401 districts |
| Net rent excluding heating (Census 2022) | Housing | Amount | €/m² | Federal stateDistrictMunicipality | 401 / 401 districts |
| Persons per household (Census 2022) | Housing | Rate | – | Federal stateDistrictMunicipality | 401 / 401 districts |
| Living space per person | Housing | Measurement · time series | m² | Federal stateDistrictMunicipality | 399 / 401 districts |
| Residential buildings built 2010–2022 | Housing | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Residential buildings built before 1949 (Census 2022) | Housing | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Residential buildings with 1 or 2 dwellings | Housing | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Dwellings in one- and two-family houses | Housing | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Children aged 3–5 in day care | Education | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Residents with a primary school nearby | Education | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Highly qualified residents | Education | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Children under 3 in childcare | Education | Share · time series | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Childcare staff with a university degree | Education | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Distance to the nearest primary school (population-weighted) | Education | Measurement | m | Federal stateDistrictMunicipality | 400 / 401 districts |
| GPs per 10,000 inhabitants | Health | Rate | – | Federal stateDistrictMunicipality | 400 / 401 districts |
| Hospital beds per 1,000 inhabitants | Health | Rate | – | Federal stateDistrictMunicipality | 400 / 401 districts |
| Doctors per 10,000 inhabitants | Health | Rate | – | Federal stateDistrictMunicipality | 400 / 401 districts |
| Share of heat demand in the densest 10 % of inhabited hectares (indicates cores suitable for heat networks) | Climate/Energy | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| of which at least 60 °C (directly usable for heat networks) per inhabitant | Climate/Energy | Measurement | kWh/yr | Federal stateDistrictMunicipality | 401 / 401 districts |
| Buildings with district heating (Census 2022) | Climate/Energy | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Buildings with gas heating (Census 2022) | Climate/Energy | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Buildings with heat pump, solar or geothermal heating (Census 2022) | Climate/Energy | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Buildings with oil heating (Census 2022) | Climate/Energy | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Reported industrial waste heat per inhabitant (German waste-heat platform) | Climate/Energy | Measurement | kWh/yr | Federal stateDistrictMunicipality | 401 / 401 districts |
| Heavy rain days (≥ 20 mm) per year, average 2016–2025 | Climate/Energy | number | days | Federal stateDistrictMunicipality | 401 / 401 districts |
| Heavy rain days: change 2016–2025 compared with 1961–1990 | Climate/Energy | number | days | Federal stateDistrictMunicipality | 401 / 401 districts |
| Heat demand of residential buildings per inhabitant (estimated from floor area and building age) | Climate/Energy | Measurement | MWh | Federal stateDistrictMunicipality | 401 / 401 districts |
| Heat island: how much warmer it is by day where people live than in the surroundings (average 2015–2024) | Climate/Energy | Measurement | °C | Federal stateDistrictMunicipality | 401 / 401 districts |
| Additional tropical nights due to built-up areas (heat island), per year 2015–2024, where people live | Climate/Energy | number | nights | Federal stateDistrictMunicipality | 401 / 401 districts |
| Spruce (share of forest area 2022) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| New land take | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Grassland (share of agricultural area 2024) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Agricultural area (share of total area) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Broadleaved trees (share of forest area 2022) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Mowings per year on grassland (average 2024) | Nature/Environment | Rate | – | Federal stateDistrictMunicipality | 401 / 401 districts |
| Maize (share of agricultural area 2024) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Maize: change 2017–2024 | Nature/Environment | Change | percentage points | Federal stateDistrictMunicipality | 401 / 401 districts |
| Local recreation areas per inhabitant | Nature/Environment | Measurement | m² | Federal stateDistrictMunicipality | 399 / 401 districts |
| Settlement and transport area | Nature/Environment | Share · time series | % | Federal stateDistrictMunicipality | 399 / 401 districts |
| Drinking water use per inhabitant per day | Nature/Environment | Measurement | l | Federal stateDistrictMunicipality | 399 / 401 districts |
| Forest loss 09/2017–10/2025 (share of forest area) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Vineyards, orchards and hedgerows (share of agricultural area) | Nature/Environment | Share | % | Federal stateDistrictMunicipality | 401 / 401 districts |
| Drive time to the nearest IC/ICE station | Mobility | Travel time | min | Federal stateDistrictMunicipality | 400 / 401 districts |
| Drive time to the nearest international airport | Mobility | Travel time | min | Federal stateDistrictMunicipality | 400 / 401 districts |
| Drive time to the nearest middle- or higher-order centre | Mobility | Travel time | min | Federal stateDistrictMunicipality | 400 / 401 districts |
| Drive time to the nearest higher-order centre | Mobility | Travel time | min | Federal stateDistrictMunicipality | 400 / 401 districts |
| Drive time to the nearest motorway | Mobility | Travel time | min | Federal stateDistrictMunicipality | 400 / 401 districts |
| Area with 4G (LTE) | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Area with 5G | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Business sites with at least 1,000 Mbit/s | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Households with fibre to the home or building (FTTH/B) | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Households with at least 1,000 Mbit/s | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Households with at least 100 Mbit/s | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
| Households with at least 50 Mbit/s | Digital | Share | % | Federal stateDistrictMunicipality | 400 / 401 districts |
For all districts
33 entries
Indicators for all 401 districts and district-free cities, mostly also for the federal states. The Coverage column shows how many districts have a value.
| Indicator | Topics | Type | Unit | Levels | Coverage |
|---|---|---|---|---|---|
| Share aged 80 and over | Population | Share | % | Federal stateDistrict | 399 / 401 districts |
| Unemployed (relative to employees) | Economy/Work | Share | % | Federal stateDistrict | 399 / 401 districts |
| Long-term unemployment rate | Economy/Work | Share | % | Federal stateDistrict | 399 / 401 districts |
| GDP per inhabitant | Economy/Work | Amount | € | Federal stateDistrict | 399 / 401 districts |
| New residential buildings with renewable heating | Housing | Share | % | Federal stateDistrict | 399 / 401 districts |
| Homeless people | Housing | Share | % | Federal stateDistrict | 394 / 401 districts |
| Children aged 5–10 in after-school care | Education | Share | % | Federal stateDistrict | 395 / 401 districts |
| Upper-secondary graduates (Abitur) | Education | Share | % | Federal stateDistrict | 397 / 401 districts |
| Participation in further training (employment promotion) | Education | Share | % | Federal stateDistrict | 399 / 401 districts |
| Success rate in vocational qualifications | Education | Share | % | Federal stateDistrict | 323 / 401 districts |
| School leavers with university entrance qualification | Education | Share | % | Federal stateDistrict | 397 / 401 districts |
| School leavers without qualifications | Education | Share | % | Federal stateDistrict | 399 / 401 districts |
| Pupils at Gymnasium (academic secondary schools) | Education | Share | % | Federal stateDistrict | 397 / 401 districts |
| Beds in preventive and rehabilitation clinics per 1,000 inhabitants | Health | Rate | – | Federal stateDistrict | 401 / 401 districts |
| Hospital beds in private ownership | Health | Share | % | Federal stateDistrict | 397 / 401 districts |
| Hospital beds per 1,000 inhabitants (sites within the area) | Health | Rate | – | Federal stateDistrict | 401 / 401 districts |
| Hospitals with emergency care (G-BA levels 1–3) per 100,000 inhabitants | Health | Rate | – | Federal stateDistrict | 401 / 401 districts |
| Care home staff (FTE per 1,000 people in need of care) | Health | Rate | – | Federal stateDistrict | 399 / 401 districts |
| People in need of care looked after at home | Health | Share | % | Federal stateDistrict | 399 / 401 districts |
| People in need of care as share of population | Health | Share | % | Federal stateDistrict | 399 / 401 districts |
| People in need of care per 1,000 older people | Health | Rate | – | Federal stateDistrict | 399 / 401 districts |
| Places in care homes per 1,000 older people | Health | Rate · time series | – | Federal stateDistrict | 399 / 401 districts |
| Overweight at the school entry examination | Health | Share | % | District | 181 / 401 districts |
| Offences per 1,000 inhabitants | Safety | Rate · time series | – | Federal stateDistrict | 399 / 401 districts |
| Road casualties per 10,000 | Safety | Rate | – | Federal stateDistrict | 399 / 401 districts |
| Charging points per 1,000 electric cars | Climate/Energy | Rate | – | Federal stateDistrict | 399 / 401 districts |
| Electric cars | Climate/Energy | Share | % | Federal stateDistrict | 399 / 401 districts |
| Electricity from renewable sources | Climate/Energy | Share · time series | % | Federal stateDistrict | 399 / 401 districts |
| Heat in wastewater treatment plant effluent per inhabitant (theoretical) | Climate/Energy | Measurement | kWh | Federal stateDistrict | 382 / 401 districts |
| Wastewater treatment (share with biological stage) | Nature/Environment | Share | % | Federal stateDistrict | 383 / 401 districts |
| Exposure to air pollutants (index) | Nature/Environment | number | number | District | 399 / 401 districts |
| Cars per 1,000 inhabitants | Mobility | Rate · time series | – | CountryFederal stateDistrict | 399 / 401 districts |
| Broadband from 50 Mbit/s (Wegweiser Kommune) | Digital | Share | % | Federal stateDistrict | 399 / 401 districts |
Additionally for countries
38 entries
Indicators available with this definition only for the 27 EU member states – mostly from Eurostat.
| Indicator | Topics | Type | Unit | Levels | Coverage |
|---|---|---|---|---|---|
| Population change since 2014 | Population | Change | % | Country | 27 / 27 countries |
| Unemployment rate | Economy/Work | Share | % | Country | 27 / 27 countries |
| At-risk-of-poverty rate | Economy/Work | Share · time series | % | Country | 27 / 27 countries |
| Income inequality (top to bottom fifth, S80/S20) | Economy/Work | number | number | Country | 27 / 27 countries |
| Employment rate 20–64 | Economy/Work | Share | % | Country | 27 / 27 countries |
| Young people neither in employment nor in education or training (15–29) | Economy/Work | Share | % | Country | 27 / 27 countries |
| GDP per inhabitant in purchasing power standards | Economy/Work | Amount | PPS | Country | 27 / 27 countries |
| Government deficit/surplus in % of GDP | Government/Finance | Share | % | Country | 27 / 27 countries |
| Government debt in % of GDP | Government/Finance | Share | % of GDP | Country | 27 / 27 countries |
| Severe housing deprivation | Housing | Share | % | Country | 27 / 27 countries |
| Overcrowding rate | Housing | Share | % | Country | 27 / 27 countries |
| Housing cost overburden | Housing | Share | % | Country | 27 / 27 countries |
| Adults in learning (last 4 weeks) | Education | Share | % | Country | 27 / 27 countries |
| Research and development in % of GDP | Education | Change | % | Country | 27 / 27 countries |
| Early leavers from education and training | Education | Share | % | Country | 27 / 27 countries |
| Tertiary educational attainment, ages 25–34 | Education | Share | % | Country | 27 / 27 countries |
| Early childhood education from age 3 | Education | Share · time series | % | Country | 27 / 27 countries |
| Hospital beds per 100,000 inhabitants | Health | Rate | – | Country | 27 / 27 countries |
| Life expectancy at birth | Health | Duration | years | Country | 27 / 27 countries |
| Unmet need for medical care | Health | Share | % | Country | 27 / 27 countries |
| Doctors per 100,000 inhabitants | Health | Rate | per 100,000 | Country | 26 / 27 countries |
| Crime, violence or vandalism in the local area (survey) | Safety | Share | % | Country | 27 / 27 countries |
| Intentional homicides per 100,000 | Safety | Rate · time series | per 100,000 | Country | 27 / 27 countries |
| Road deaths per 100,000 | Safety | Rate | per 100,000 | Country | 27 / 27 countries |
| Energy import dependency | Climate/Energy | Share | % | Country | 27 / 27 countries |
| Renewables share of final energy consumption | Climate/Energy | Share · time series | % | Country | 27 / 27 countries |
| Energy productivity | Climate/Energy | Amount | €/kgoe | Country | 27 / 27 countries |
| Greenhouse gas emissions per inhabitant | Climate/Energy | Measurement | t | Country | 27 / 27 countries |
| Protected land area | Nature/Environment | Share | % | Country | 27 / 27 countries |
| Recycling rate of municipal waste | Nature/Environment | Share | % | Country | 27 / 27 countries |
| Premature deaths from fine particulate matter per 100,000 | Nature/Environment | Rate | – | Country | 27 / 27 countries |
| Area under organic farming | Nature/Environment | Share | % | Country | 27 / 27 countries |
| Buses and trains in passenger transport | Mobility | Share | % | Country | 25 / 27 countries |
| Rail share of freight transport | Mobility | Share | % | Country | 25 / 27 countries |
| At least basic digital skills | Digital | Share | % | Country | 27 / 27 countries |
| Internet use (last 12 months) | Digital | Share | % | Country | 27 / 27 countries |
| Use of e-government services (12 months) | Digital | Share | % | Country | 27 / 27 countries |
| Very fast fixed broadband connections | Digital | Share · time series | % | Country | 27 / 27 countries |
Additionally for federal states
7 entries
Indicators that official statistics publish only down to the level of the federal states.
| Indicator | Topics | Type | Unit | Levels | Coverage |
|---|---|---|---|---|---|
| Diabetes-related amputations per 100,000 | Health | Rate | – | Federal state | 16 / 16 federal states |
| Disease burden from diabetes (DALYs per 100,000) | Health | Rate | – | Federal state | 16 / 16 federal states |
| Physically inactive adults | Health | Share | % | Federal state | 16 / 16 federal states |
| Adult smokers | Health | Share | % | Federal state | 16 / 16 federal states |
| Waste per inhabitant | Nature/Environment | Measurement | t | Federal state | 16 / 16 federal states |
| Contaminated sites needing remediation per 100 km² | Nature/Environment | Rate | – | Federal state | 16 / 16 federal states |
| Contaminated sites with completed remediation (share) | Nature/Environment | Share | % | Federal state | 16 / 16 federal states |
Additionally for municipalities and city districts
11 entries
Indicators for municipalities only; comparison values for municipalities across Germany. For Hamburg’s city districts, the features of the twin search are available.
| Indicator | Topics | Type | Unit | Levels | Coverage |
|---|---|---|---|---|---|
| Births per 1,000 inhabitants | Population | Rate | – | Municipality | 875 municipalities |
| Out-commuters (share of employees at place of residence) | Economy/Work | Share | % | Municipality | 891 municipalities |
| Employment rate of women | Economy/Work | Share | % | Municipality | 876 municipalities |
| Marginally employed at place of residence | Economy/Work | Share | % | Municipality | 876 municipalities |
| Long-term unemployed (share of the unemployed) | Economy/Work | Share | % | Municipality | 891 municipalities |
| General revenue per inhabitant | Government/Finance | Amount | € | Municipality | 876 municipalities |
| Trade tax multiplier | Government/Finance | Share | % | Municipality | 876 municipalities |
| Investment balance per inhabitant | Government/Finance | Amount | € | Municipality | 876 municipalities |
| Staff expenditure per inhabitant | Government/Finance | Amount | € | Municipality | 876 municipalities |
| General grants per inhabitant | Government/Finance | Amount | € | Municipality | 876 municipalities |
| Paediatricians per 10,000 under-15s | Health | Rate | – | Municipality | 891 municipalities |
Reference district Merzig-Wadern
57 entries
Merzig-Wadern is our reference district, the one we have worked with from the start. Its data holdings are the largest; we are extending the other districts step by step.
| Indicator | Topics | Type | Unit | Levels | Coverage |
|---|---|---|---|---|---|
| Population on 1 January by 5-year age group, sex and NUTS 3 region | Population | Time series · annual | persons | CountryDistrict | |
| Population on 1 January by broad age group, sex and NUTS 3 region | Population | Time series · annual | – | CountryAdministrative regionDistrict | |
| Regional values Moselle (département) and Grand Est (region) | Population | Time series · annual | – | Administrative regionDistrict | |
| Page views of the Wikipedia articles on the region | Population | Time series · daily | – | District | |
| Administrative areas 1:250,000 – districts and municipalities | Population | Reference date | – | CountryFederal stateDistrictMunicipality | |
| Wikidata – language versions (sitelinks) of the articles on the region | Population | Reference date | – | District | |
| Wikipedia articles as a source for the regional portrait (introduction) | Population | Reference date | – | DistrictMunicipality | |
| Compensation of employees by NUTS 2 region | Economy/Work | Time series · annual | € million | CountryAdministrative region | |
| Unemployed and unemployment rate (all civilian labour force) per district – current month, previous month, same month last year | Economy/Work | Time series · monthly | – | District | |
| Unemployment rates by district – annual average, moving annual average and monthly values, by legal basis and group of persons | Economy/Work | Time series · monthly | – | CountryFederal stateDistrict | |
| Local labour market – employees at place of residence and work, unemployed per municipality | Economy/Work | Time series · annual | – | Municipality | |
| Employment (persons) by NUTS 3 region and economic activity (NACE Rev. 2) | Economy/Work | Time series · annual | thousand persons | CountryAdministrative regionDistrict | |
| Establishments and employees by size class – Germany, federal states and districts | Economy/Work | Reference date | – | CountryFederal stateDistrict | |
| Gross domestic product at market prices by NUTS 3 region | Economy/Work | Time series · annual | – | CountryDistrict | |
| Gross value added at basic prices by NUTS 3 region and economic activity (NACE Rev. 2) | Economy/Work | Time series · annual | € million | CountryDistrict | |
| Average length of stay of guests | Economy/Work | number | nights | Federal stateDistrictMunicipality | 16 municipalities |
| Average population (reference for regional accounts), NUTS 3 | Economy/Work | Time series · annual | – | District | |
| Wages in regional comparison – base data of the maps (1 km and 5 km grid) | Economy/Work | Reference date | € gross per month | Grid | |
| Employed persons by commuting status (place of work at home/abroad) and NUTS 2 region | Economy/Work | Time series · annual | – | Administrative region | |
| EU Regional Competitiveness Index 2.0, 2022 edition – pillars and overall index | Economy/Work | Reference date | index EU-27 = 100, rank | Administrative region | |
| Hours worked by employed persons by NUTS 2 region | Economy/Work | Time series · annual | thousand hours | Administrative region | |
| GLEIF LEI records with legal address by postcode | Economy/Work | Time series · daily | – | MunicipalityMonitoring site | |
| Guest beds per 1,000 inhabitants (tourism) | Economy/Work | Rate | – | Federal stateDistrictMunicipality | 16 municipalities |
| Overnight stays per inhabitant (tourism) | Economy/Work | Rate | – | Federal stateDistrictMunicipality | 16 municipalities |
| Overnight stays: change since 2019 (pre-COVID) | Economy/Work | Change | % | Federal stateDistrictMunicipality | 11 municipalities |
| Household income by NUTS 2 region | Economy/Work | Time series · annual | € per inhabitant | Administrative region | |
| Employees insured in Luxembourg by municipality of residence in neighbouring countries | Economy/Work | Time series · quarterly | – | Federal stateMunicipality | |
| OffeneRegister – companies from register announcements (as of February 2019) | Economy/Work | Reference date | – | Municipality | |
| Commuter flows of employees subject to social insurance by district (residence × workplace) | Economy/Work | Reference date | – | District | |
| Regional report on employees (quarterly figures) per district | Economy/Work | Reference date | – | District | |
| Business demography by NACE Rev. 2 and NUTS 3 region | Economy/Work | Time series · annual | – | CountryDistrict | |
| Federal elections – results by district and municipality | Government/Finance | Reference date | – | DistrictMunicipality | |
| European election 2024 – results by district and municipality | Government/Finance | Reference date | – | DistrictMunicipality | |
| Local tax multipliers per municipality: property tax A and B, trade tax | Government/Finance | Time series · annual | % | Municipality | |
| Integrated debt of municipalities and municipal associations 2024 – core budget and public sector per inhabitant | Government/Finance | Reference date | € per inhabitant | DistrictMunicipality | |
| Business development, location costs and online services of the district and municipalities of Merzig-Wadern (pilot) | Government/Finance | Reference date | – | DistrictMunicipality | |
| Census 2022 – dwellings by tenure, floor area, year of construction and heating type per district and municipality | Housing | Reference date | – | DistrictMunicipality | |
| Population by educational attainment, sex, age and NUTS 2 region (%) | Education | Time series · annual | – | CountryAdministrative region | |
| Health expenditure of the federal states – key figures | Health | Time series · annual | – | Federal state | |
| Uptake of routine vaccinations per district (flu 60+, HPV, measles) | Health | Time series · annual | – | Federal stateDistrict | |
| GEOFON event catalogue – earthquakes within 2° of the district | Safety | Time series · real time | magnitude, depth km | Monitoring site | |
| Rhineland-Palatinate state earthquake service – located earthquakes since 2000 (epicentre, ML, depth) | Safety | Time series · real time | – | Monitoring site | |
| Police crime statistics 2025 – cases, frequency rate and clearance rate by offence code per district | Safety | Time series · annual | – | District | |
| Accident atlas – road accidents with personal injury, georeferenced | Safety | Time series · annual | – | DistrictMonitoring site | |
| USGS ComCat – earthquakes of magnitude 2 and above within 2° of the district | Safety | Time series · real time | – | Monitoring site | |
| DWD climate grid 1 km – annual climate indicator days and mean temperature, district average | Climate/Energy | Time series · annual | – | DistrictGrid | |
| Warming 2016–2025 compared with 1961–1990 | Climate/Energy | Measurement | °C | DistrictMunicipality | 29 municipalities |
| Hot days (≥ 30 °C), average 2016–2025 | Climate/Energy | number | days | DistrictMunicipality | 29 municipalities |
| Noise exposure along major federal railway lines per municipality – people affected by noise band, dwellings, schools, hospitals | Nature/Environment | Reference date | – | Municipality | |
| Water levels of the Saar gauges Rehlingen, Fremersdorf, Mettlach, Serrig | Nature/Environment | Time series · every 15 minutes | cm above gauge zero | Monitoring site | |
| ADSB.lol – daily tracks of all received aircraft, aggregated into overflights per area | Mobility | Time series · hourly | – | DistrictGrid | |
| Stock of motor vehicles and trailers by registration district – vehicle classes, female keepers, commercial keepers, body types, fuels | Mobility | Reference date | – | District | |
| deutsche-bahn-data – scheduled and actual times at all DB stops | Mobility | Time series · daily | – | Monitoring site | |
| Vehicle stock by registration district and municipality | Mobility | Time series · annual | – | DistrictMunicipality | |
| Federal toll data – mileage per tolled motorway section | Mobility | Time series · monthly | – | Monitoring site | |
| Train traffic on the rail network – Germany, network sections 2020 | Mobility | Time series · annual | trains per year, converted to trains per day | Monitoring site | |
| Broadband and mobile coverage per district (households, business parks, area) | Digital | Reference date | – | District |
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In the Online Radar you see every indicator for your area – with rank and comparison.