All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

The ChokePoint dataset is designed for experiments in person identification/verification under real-world surveillance conditions using existing technologies. An array of three cameras was placed above several portals (natural choke points in terms of pedestrian traffic) to capture subjects walking through each portal in a natural way. While a person is walking through a portal, a sequence of face images (ie. a face set) can be captured. Faces in such sets will have variations in terms of illumination conditions, pose, sharpness, as well as misalignment due to automatic face localisation/detection. Due to the three camera configuration, one of the cameras is likely to capture a face set where a subset of the faces is near-frontal.

The dataset consists of 25 subjects (19 male and 6 female) in portal 1 and 29 subjects (23 male and 6 female) in portal 2. The recording of portal 1 and portal 2 are one month apart. The dataset has frame rate of 30 fps and the image resolution is 800X600 pixels. In total, the dataset consists of 48 video sequences and 64,204 face images. In all sequences, only one subject is presented in the image at a time. The first 100 frames of each sequence are for background modelling where no foreground objects were presented.

Each sequence was named according to the recording conditions (eg. P2E_S1_C3) where P, S, and C stand for portal, sequence and camera, respectively. E and L indicate subjects either entering or leaving the portal. The numbers indicate the respective portal, sequence and camera label. For example, P2L_S1_C3 indicates that the recording was done in Portal 2, with people leaving the portal, and captured by camera 3 in the first recorded sequence.

To pose a more challenging real-world surveillance problems, two seqeunces (P2E_S5 and P2L_S5) were recorded with crowded scenario. In additional to the aforementioned variations, the sequences were presented with continuous occlusion. This phenomenon presents challenges in identidy tracking and face verification.

This dataset can be applied, but not limited, to the following research areas:

person re-identification

image set matching

face quality measurement

face clustering

3D face reconstruction

pedestrian/face tracking

background estimation and subtraction

Please cite the following paper if you use the ChokePoint dataset in your work (papers, articles, reports, books, software, etc):

Y. Wong, S. Chen, S. Mau, C. Sanderson, B.C. Lovell Patch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition IEEE Biometrics Workshop, Computer Vision and Pattern Recognition (CVPR) Workshops, pages 81-88, 2011. http://doi.org/10.1109/CVPRW.2011.5981881

What’s Included

The English Closed-Ended Question Answering Dataset is a meticulously curated collection of 5000 comprehensive Question-Answer pairs. It serves as a valuable resource for training Large Language Models (LLMs) and question-answering models in the English language, advancing the field of artificial intelligence.

Each question is accompanied by an answer, providing valuable information and insights to enhance the language model training process. Both the questions and answers were manually curated by native English people, and references were taken from diverse sources like books, news articles, websites, web forums, and other reliable references.

This question-answer prompt completion dataset contains different types of prompts, including instruction type, continuation type, and in-context learning (zero-shot, few-shot) type. The dataset also contains questions and answers with different types of rich text, including tables, code, JSON, etc., with proper markdown.

The English versions is grammatically accurate without any spelling or grammatical errors. No toxic or harmful content is used while building this dataset.

Block Groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people, and are used to present sample data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number. For example, blocks 3001, 3002, 3003 . . . 3999 in census tract 1210.02 belong to BG 3 in that census tract. Block groups generally contain between 600 and 3,000 people. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program. The Census Bureau delineated BGs only where a local or tribal government declined to participate and a regional organization or State Data Center was not available to participate.A BG usually covers a contiguous area. Each census tract contains at least one BG and BGs are uniquely numbered within census tract. Within the standard census geographic hierarchy, BGs never cross county or census tract boundaries but may cross the boundaries of areas any other geographic entity. Tribal census tracts and tribal BGs are separate and unique geographic areas defined within federally recognized American Indian reservations and can cross state and county boundaries. The tribal census tracts and tribal block groups may be completely different from the census tracts and block groups defined by state and county.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_substategeo.gdb.zip Layer: Block_GroupMetadata: https://meta.geo.census.gov/data/existing/decennial/GEO/GPMB/TIGERline/Current_19115/series_tl_2023_bg.shp.iso.xml

This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Kenya. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 600 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Census Block Groups for Macon-Bibb County.

Block Groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people and are used to present data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number. For example, blocks 3001, 3002, 3003, . . ., 3999 in census tract 1210.02 belong to BG 3 in that census tract. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program. The Census Bureau delineated BGs only where a local or tribal government declined to participate, and a regional organization or State Data Center was not available to participate.

A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within the census tract. Within the standard census geographic hierarchy, BGs never cross state, county, or census tract boundaries but may cross the boundaries of any other geographic entity. Tribal census tracts and tribal BGs are separate and unique geographic areas defined within federally recognized American Indian reservations and can cross state and county boundaries (see "Tribal Census Tract" and "Tribal Block Group"). The tribal census tracts and tribal block groups may be completely different from the census tracts and block groups defined by state and county.

Block Group Codes—BGs have a valid code range of 0 through 9. BGs beginning with a zero only contain water area and are generally in coastal and Great Lakes water and territorial seas, but also in larger inland water bodies. For the 2010 Census, a block group 0 for the water portion can be delineated in any census tract and not just those census tracts also defined to only include water area. This is a change from Census 2000, when block groups coded 0 only existed in census tracts with a code of 0. To differentiate between county-based block groups and tribal block groups, the codes for tribal block groups use an alphabetic character (see "Tribal Block Group").

For more information about Census Block Groups or the US Census Bureau visit https://www.census.gov.

The Mississippi River is North America’s largest river, flowing over 2,300 miles through America’s heartland to the Gulf of Mexico. The watershed not only provides drinking water, food, industry, and recreation for millions of people, it also hosts a globally significant migratory flyway and home for over 325 bird species. Leading the world in agricultural production, a healthy agricultural sector in the Mississippi River Basin is essential for maintaining the nation’s and the world’s food and fiber supply. USDA Conservation Effects Assessment Project (CEAP) cropland models show that conservation on cropland throughout the entire Mississippi River Basin has reduced nitrogen and sediment loading to the Gulf of Mexico by 28 percent and 45 percent, respectively, over what would be lost without conservation systems in place. With the CCA designation, USDA will build on existing strong partnerships in the basin to accelerate conservation in the 13-state area to continue to reduce nutrient and sediment loading to local and regional water bodies and to improve efficiency in using water supplies, particularly in the southern states. The CCA boundary was identified to harness the partnerships and momentum already established by NRCS’s Mississippi River Basin Healthy Watersheds Initiative (MRBI). With more than 600 partners engaged throughout the initiative area, MRBI has treated over 800,000 acres of agricultural land with systems of practices intended to avoid, control, and trap nutrient and sediment run-off and improve irrigation efficiency. This dataset includes a printer-friendly CCA map and shapefiles for GIS. Resources in this dataset:Resource Title: Mississippi River Basin. File Name: Web Page, url: https://www.nrcs.usda.gov/programs-initiatives/rcpp-regional-conservation-partnership-program/critical-conservation-areas Information about the project and links to a printer-friendly CCA map (PDF, 1.2MB) and shapefiles for GIS (ZIP, 218KB).

The number of Facebook users in Africa was forecast to continuously increase between 2024 and 2028 by in total 141.6 million users (+56.79 percent). After the ninth consecutive increasing year, the Facebook user base is estimated to reach 390.94 million users and therefore a new peak in 2028. Notably, the number of Facebook users of was continuously increasing over the past years.User figures, shown here regarding the platform facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Facebook users in countries like Europe and Asia.

A dataset listing Florida counties by population for 2024.

Last Update: 02/2021This datasets was was downloaded from the 2020 Census Redistricting Data (P.L. 94-171) page. All 2020 census boundaries are current to January 1, 2020. The Census Bureau will release the first set of corresponding demographic data in September 2021 (the 2020 Census Redistricting P.L. 94-171 Summary Files). Following that release, AGRC will append the demographic data to the existing 2020 geographies served on this page.Block groups are divisions of census tracts that generally contain between 600 and 3,000 people. A block group consists of a cluster of census blocks within the same census tract.Visit the SGID 2020 Census data pagefor more information.

The population share with mobile internet access in Africa was forecast to continuously increase between 2024 and 2029 by in total 21.7 percentage points. After the eighteenth consecutive increasing year, the mobile internet penetration is estimated to reach 46.22 percent and therefore a new peak in 2029. The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the population share with mobile internet access in countries like Caribbean and Europe.

The online banking penetration rate in Africa was forecast to continuously increase between 2024 and 2029 by in total 5.2 percentage points. After the fifteenth consecutive increasing year, the online banking penetration is estimated to reach 13.25 percent and therefore a new peak in 2029. Notably, the online banking penetration rate of was continuously increasing over the past years.Shown is the estimated percentage of the total population in a given region or country, which makes use of online banking.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the online banking penetration rate in countries like North America and Europe.

This statistic shows a ranking of the estimated number of households with internet access at home in 2020 in Africa, differentiated by country.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).