Online security is as current a topic in Germany as in almost every country in the world. With more and more personal information being stored and accessible online, privacy and data protection laws are becoming increasingly important, with the pressing necessity of establishing more than just general guidelines. As is clear from this statistic, the majority of Germans are more than skeptical about the safety of their personal data on the internet.

Private users

Personal data being secure online is an issue affecting both private citizens and companies alike, across services and industries. The main concerns over using e-government websites, for example, were becoming a so-called transparent citizen with private data stored in one central database, as well as lack of security during data transmissions. Optimistically so, the number of phishing cases targeting online banking users has been dropping in recent years.

Companies

75 percent of companies in Germany were the victims of cyber attacks in 2019. Of these, the most common types were theft of IT and communication devices, as well as sensitive digital documents.

In 2023, the share of German internet users amounted to 94 percent, an increase compared to the previous year at 93 percent. This share has only been growing in recent years. Considering current German population numbers stand at almost 83 million, such a high share of internet users is significant in itself and also for predicting future trends on digitalization and online connectivity in the country. Completely connected Modern life is unthinkable without the internet, without being online or knowing you can go online anytime you want to, especially since the rise of mobile internet and mobile devices. The latter means that internet users are no longer tied to a desktop computer for going online. In terms of age distribution among German internet users, this was mostly even, though users aged 70 years and older tended to make up the smaller share. Up until fairy recently, there were more male internet users in Germany than females ones, but this has changed. Online in the city Internet user share may also depend on whether the user resides in an urban or rural area. Generally, cities have fast and more stable internet connections. However, there is an increasing number of households with fiber-optic cables in Germany, highlighting the ambition for everyone to have good access to the internet. Data volume in stationary broadband internet traffic via landline has been growing in leaps and bounds during the last decade.

Germany Internet Users: Estimated data was reported at 67,242,000.000 Person in 2019. This records an increase from the previous number of 66,484,000.000 Person for 2018. Germany Internet Users: Estimated data is updated yearly, averaging 57,716,500.000 Person from Mar 2006 (Median) to 2019, with 14 observations. The data reached an all-time high of 67,242,000.000 Person in 2019 and a record low of 48,519,000.000 Person in 2006. Germany Internet Users: Estimated data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.TB001: Internet Users.

This statistic shows the data volume development in mobile phone networks in Germany from 2009 to 2023. In 2023, the average monthly data volume per mobile subscription amounted to 7.2 gigabytes.

Germany Internet Users: Internet Banking data was reported at 60.100 % in 2019. This records an increase from the previous number of 58.500 % for 2018. Germany Internet Users: Internet Banking data is updated yearly, averaging 50.500 % from Mar 2006 (Median) to 2019, with 14 observations. The data reached an all-time high of 60.100 % in 2019 and a record low of 42.000 % in 2006. Germany Internet Users: Internet Banking data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.TB001: Internet Users.

Germany Internet Users: Every Day or Almost Every Day data was reported at 89.600 % in 2019. This records an increase from the previous number of 88.900 % for 2018. Germany Internet Users: Every Day or Almost Every Day data is updated yearly, averaging 78.500 % from Mar 2006 (Median) to 2019, with 14 observations. The data reached an all-time high of 89.600 % in 2019 and a record low of 55.700 % in 2006. Germany Internet Users: Every Day or Almost Every Day data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.TB001: Internet Users.

Germany Internet Users: Every Day or Almost Every Day: Male data was reported at 91.100 % in 2019. This records an increase from the previous number of 90.700 % for 2018. Germany Internet Users: Every Day or Almost Every Day: Male data is updated yearly, averaging 81.500 % from Mar 2006 (Median) to 2019, with 14 observations. The data reached an all-time high of 91.100 % in 2019 and a record low of 61.300 % in 2006. Germany Internet Users: Every Day or Almost Every Day: Male data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.TB001: Internet Users.

This statistic shows the data volume development in stationary broadband internet traffic via landline in Germany from 2001 to 2022, with an estimate for 2023. In 2023, the data volume was estimated to have amounted to roughly ***** billion gigabytes.

** percent of German consumers consider their personal data to be secure when paying via an invoice. This statistic shows the results of a survey conducted in 2018 regarding opinions on how safe personal data is when using online payment options.

This statistic shows data on the mobile online advertising revenue in Germany from 2015 to 2027. In 2023, mobile online advertising was predicted to generate a revenue of around 7.5 billion euros. For 2024, PwC projects a revenue of roughly eight billion euros.

The work of Kraus represents a collection of material on population, on population movement and on population structure according to age and sex. The study is subdivided into the individual member states of the German Confederation on the area of the future German Reich, the provinces of Prussia as well as the German Reich in total. The values to the variables inhabitants, marriages, number of births, number of deaths without stillborn ones, number of deaths are to be found in the a-tables. The number of inhabitants according to sex and the age groups of the inhabitants according to sex are to be found in the b-tables. A- and b-tables both contain absolute and relative numbers. Subjects: Tables in the ZA-Online-Database HISTAT: Tables of Population figure and population movement and tables of the distribution by age and sex for the German countries: - Kingdom of Wuerttemberg (Königreich Württemberg) (1815-1875)- Grand Duchy Baden (Großherzogtum Baden) (1815-1875)- Duchy of Braunschweig (Herzogtum Braunschweig) (1816-1875)- Kingdom of Saxony (Königreich Sachsen) (1815-1875)- Grand Duchy of Hesse (Großherzogtum Hessen) (1815-1875)- Kongdom of Bavaria (Königreich Bayern (mit Pfalz)) (Population figure and -movement: 1816-1875; Distribution by age and sex: 1834-1875)- Bavaria to the west of the Rhine: Palatinate (Pfalz) (1818-1875)- Grand Duchy of Mecklenburg-Strelitz, including the principality of Ratzeburg (Großherzogtum Mecklenburg-Strelitz, einschließlich des Fürstentums Ratzeburg) (1815-1875)- Grand Duchy of Mecklenburg-Schwerin (Großherzogtum Mecklenburg-Schwerin) (1815-1875)- Grand Duchy of Oldenburg (Großherzogtum Oldenburg) (1855-1875)- Kingdom of Hannover, since 1966 prussian province (Königreich Hannover, ab 1866 preußische Provinz Hannover) (1815-1875)- The various prussian administrative districts and provinces (1815-1875)- The Free Hanseatic Cities Hamburg, Luebeck and Bremen Tables of Population figure and population movement- The German Empire without Alsace-Lorraine (Deutsches Reich (ohne Elsaß-Lothringen)) (1841-1875)- The German Empire with Alsace-Lorraine (Deutsches Reich (mit Elsaß-Lothringen)) (1840-1875)- Alsace-Lorraine (Elsaß-Lothringen) (1821-1875)

Germany Internet Users: Search for Information on Goods and Services: Male data was reported at 88.900 % in 2019. This records a decrease from the previous number of 91.300 % for 2018. Germany Internet Users: Search for Information on Goods and Services: Male data is updated yearly, averaging 88.950 % from Mar 2006 (Median) to 2019, with 14 observations. The data reached an all-time high of 91.300 % in 2018 and a record low of 85.000 % in 2011. Germany Internet Users: Search for Information on Goods and Services: Male data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.TB001: Internet Users.

Germany Internet Users: Use of Social Networks: Male data was reported at 52.600 % in 2019. This records a decrease from the previous number of 54.600 % for 2018. Germany Internet Users: Use of Social Networks: Male data is updated yearly, averaging 53.300 % from Mar 2011 (Median) to 2019, with 8 observations. The data reached an all-time high of 63.000 % in 2015 and a record low of 49.000 % in 2013. Germany Internet Users: Use of Social Networks: Male data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.TB001: Internet Users.

This dataset features three gridded population dadasets of Germany on a 10m grid. The units are people per grid cell.

Datasets

DE_POP_VOLADJ16: This dataset was produced by disaggregating national census counts to 10m grid cells based on a weighted dasymetric mapping approach. A building density, building height and building type dataset were used as underlying covariates, with an adjusted volume for multi-family residential buildings.

DE_POP_TDBP: This dataset is considered a best product, based on a dasymetric mapping approach that disaggregated municipal census counts to 10m grid cells using the same three underyling covariate layers.

DE_POP_BU: This dataset is based on a bottom-up gridded population estimate. A building density, building height and building type layer were used to compute a living floor area dataset in a 10m grid. Using federal statistics on the average living floor are per capita, this bottom-up estimate was created.

Please refer to the related publication for details.

Temporal extent

The building density layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: http://doi.org/10.1594/PANGAEA.920894)

The building height layer is representative for ca. 2015 (doi: 10.5281/zenodo.4066295)

The building types layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: 10.5281/zenodo.4601219)

The underlying census data is from 2018.

Data format

The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems.

Further information

For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de).
A web-visualization of this dataset is available here.

Publication

Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE. DOI: 10.1371/journal.pone.0249044

Acknowledgements

Census data were provided by the German Federal Statistical Offices.

Funding
This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

Germany Internet Usage: Search Engine Market Share: All Platforms: Sogou data was reported at 0.000 % in 04 Oct 2024. This stayed constant from the previous number of 0.000 % for 03 Oct 2024. Germany Internet Usage: Search Engine Market Share: All Platforms: Sogou data is updated daily, averaging 0.020 % from Sep 2024 (Median) to 04 Oct 2024, with 31 observations. The data reached an all-time high of 0.030 % in 28 Sep 2024 and a record low of 0.000 % in 04 Oct 2024. Germany Internet Usage: Search Engine Market Share: All Platforms: Sogou data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Germany – Table DE.SC.IU: Internet Usage: Search Engine Market Share.

Sources: official statistics; corporation statistics

This statistic shows data on gross internet advertising investments in Germany from 2006 to 2022. In 2022, gross internet advertising investments amounted to roughly *** billion euros.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: No - Individuals: Yes - Group quarters: Yes - Special populations: No

UNIT DESCRIPTIONS: - Dwellings: A dwelling, in terms of a survey unit, is defined as a self-contained set of rooms intended for living purposes which enable persons to keep their own household. - Households: A household consists of all persons who live in the same dwelling and have a common housekeeping budget. Also. persons living and keeping house alone as well as lodgers are counted as households. - Group quarters: Persons in institutions, homes or the like are covered if they live there, are registered at that address with the police or relevant authorities and, fully or partly, make use of communal catering arrangements or of any joint facilities.

Universe

Total population entitled to reside in households

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Federal Statistical Office

SAMPLE UNIT: Person

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 3,094,845

Mode of data collection

Face-to-face [f2f]

Research instrument

2 questionnaires: (f1) population census questionnaire: 90% of the population received a questionnaire comprising 18 questions, the remaining 10% received a questionnaire containing 39 questions; (f2) local unit questionnaire

Response rate

COVERAGE: 100%

The rainfall data inter-comparison dataset is a collection of precipitation statistics calculated from the hourly nationwide German radar climatology (RADKLIM) and radar online adjustment (RADOLAN) composites provided by the German Weather Service (Deutscher Wetterdienst, DWD), which were combined with rainfall statistics derived from rain gauge data for inter-comparison. Moreover, additional information on parameters that can potentially influence radar data quality, such as the height above sea level, information on wind energy plants and the distance to the next radar station, were included in the dataset.

The dataset consists of two point shapefiles which are readable with all common GIS. It constitutes a spatially highly resolved rainfall statistics geodataset for the period 2006 - 2017, which can be used for statistical rainfall analyses or for the derivation of model inputs. Furthermore, this data collection has the potential to benefit all users who intend to use precipitation data for any purpose in Germany and to identify the rainfall dataset that is best suited for their application by a straightforward comparison of three rainfall datasets without any tedious data processing and georeferencing.

Spatial extent: Germany

Spatial Resolution: 1 x 1 km

Time period: 2006 - 2017

Data Format: Two point shapefiles

Compared precipitation datasets: RADKLIM, RADOLAN, rain gauge data

Selection of calculated precipitation statistics:

Annual precipitation sum

Mean annual precipitation sum

Mean seasonal precipitation sums

Number of days exceeding a daily precipitation of 1 mm

Number of days exceeding a daily precipitation of 20 mm

Mean daily precipitation sum of all days exceeding a precipitation sum of 1 mm

Mean daily precipitation sum of all days exceeding a precipitation sum of 20 mm

Number of NoData entries

An Excel file with detailed information on all parameters and on original data sources is also included in the dataset.

Original data source URLs:

RADKLIM (DWD): https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/reproc/2017_002/bin/

RADOLAN (DWD): ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/hourly/radolan/historical/bin/

Rain Gauge Data (DWD): https://opendata.dwd.de/climate_environment/CDC/observations_ germany/climate/1_minute/precipitation/

Location of wind energy plants (UFZ): https://www.ufz.de/record/dmp/archive/5467/de/

SRTM DEM (DLR): https://geoservice.dlr.de/egp/

In 2020, ** percent of companies in Germany stated that their use of cloud services during the corona crisis was restricted by data security requirements. Two percent said they were not able to use cloud services at all. The figures are based on a survey conducted in Germany in September 2020 during the coronavirus (COVID-19) pandemic.