People data provides complete people information and gives the ability to link individual information to organizations and roles.

[1] The Progress by Population Group analysis is a component of the Healthy People 2020 (HP2020) Final Review. The analysis included subsets of the 1,111 measurable HP2020 objectives that have data available for any of six broad population characteristics: sex, race and ethnicity, educational attainment, family income, disability status, and geographic location. Progress toward meeting HP2020 targets is presented for up to 24 population groups within these characteristics, based on objective data aggregated across HP2020 topic areas. The Progress by Population Group data are also available at the individual objective level in the downloadable data set. [2] The final value was generally based on data available on the HP2020 website as of January 2020. For objectives that are continuing into HP2030, more recent data will be included on the HP2030 website as it becomes available: https://health.gov/healthypeople. [3] For more information on the HP2020 methodology for measuring progress toward target attainment and the elimination of health disparities, see: Healthy People Statistical Notes, no 27; available from: https://www.cdc.gov/nchs/data/statnt/statnt27.pdf. [4] Status for objectives included in the HP2020 Progress by Population Group analysis was determined using the baseline, final, and target value. The progress status categories used in HP2020 were: a. Target met or exceeded—One of the following applies: (i) At baseline, the target was not met or exceeded, and the most recent value was equal to or exceeded the target (the percentage of targeted change achieved was equal to or greater than 100%); (ii) The baseline and most recent values were equal to or exceeded the target (the percentage of targeted change achieved was not assessed). b. Improved—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved 10% or more of the targeted change. c. Little or no detectable change—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was not statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved less than 10% of the targeted change; (iii) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was not statistically significant; (iv) Movement was away from the baseline and target, standard errors were not available, and the objective had moved less than 10% relative to the baseline; (v) No change was observed between the baseline and the final data point. d. Got worse—One of the following applies: (i) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was statistically significant; (ii) Movement was away from the baseline and target, standard errors were not available, and the objective had moved 10% or more relative to the baseline. NOTE: Measurable objectives had baseline data. SOURCE: National Center for Health Statistics, Healthy People 2020 Progress by Population Group database.

The database contains responses from 866 individuals as part of the 'Young People's Relationality' study. The research was conducted using the CAWI method on a research panel, on a representative sample of young Polish women and men aged 16-24, based on the size of the place of residence and the province, from December 1st to December 18th, 2023.

Copy of https://www.kaggle.com/datasets/kisoibo/countries-databasesqlite

Updated the name of the table from 'countries of the world' to 'countries', for ease of writing queries.

Info about the dataset:

Content

Table Total Rows Total Columns countries of the world **0 ** ** 20** Country, Region, Population, Area (sq. mi.), Pop. Density (per sq. mi.), Coastline (coast/area ratio), Net migration, Infant mortality (per 1000 births), GDP ($ per capita), Literacy (%), Phones (per 1000), Arable (%), Crops (%), Other (%), Climate, Birthrate, Deathrate, Agriculture, Industry, Service

Acknowledgements

Acknowledgements Source: All these data sets are made up of data from the US government. Generally they are free to use if you use the data in the US. If you are outside of the US, you may need to contact the US Govt to ask. Data from the World Factbook is public domain. The website says "The World Factbook is in the public domain and may be used freely by anyone at anytime without seeking permission." https://www.cia.gov/library/publications/the-world-factbook/docs/faqs.html

Inspiration

When making visualisations related to countries, sometimes it is interesting to group them by attributes such as region, or weigh their importance by population, GDP or other variables.

[1] Status is determined using the baseline, final, and target value. The statuses used in Healthy People 2020 were: 1 - Target met or exceeded—One of the following applies: (i) At baseline, the target was not met or exceeded, and the most recent value was equal to or exceeded the target. (The percentage of targeted change achieved was equal to or greater than 100%.); (ii) The baseline and most recent values were equal to or exceeded the target. (The percentage of targeted change achieved was not assessed.) 2 - Improved—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved 10% or more of the targeted change. 3 - Little or no detectable change—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was not statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved less than 10% of the targeted change; (iii) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was not statistically significant; (iv) Movement was away from the baseline and target, standard errors were not available, and the objective had moved less than 10% relative to the baseline; (v) No change was observed between the baseline and the final data point. 4 - Got worse—One of the following applies: (i) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was statistically significant; (ii) Movement was away from the baseline and target, standard errors were not available, and the objective had moved 10% or more relative to the baseline. 5 - Baseline only—The objective only had one data point, so progress toward target attainment could not be assessed. Note that if additional data points did not meet the criteria for statistical reliability, data quality, or confidentiality, the objective was categorized as baseline only. 6 - Informational—A target was not set for this objective, so progress toward target attainment could not be assessed. [2] The final value is generally based on data available on the Healthy People 2020 website as of January 2020. For objectives that are continuing into Healthy People 2030, more recent data are available on the Healthy People 2030 website: https://health.gov/healthypeople. [3] For objectives that moved toward their targets, movement toward the target was measured as the percentage of targeted change achieved (unless the target was already met or exceeded at baseline): Percentage of targeted change achieved = (Final value - Baseline value) / (HP2020 target - Baseline value) * 100 [4] For objectives that were not improving, did not meet or exceed their targets, and did not move towards their targets, movement away from the baseline was measured as the magnitude of the percent change from baseline: Magnitude of percent change from baseline = |Final value - Baseline value| / Baseline value * 100 [5] Statistical significance was tested when the objective had a target, at least two data points (of unequal value), and available standard errors of the data. A normal distribution was assumed. All available digits were used to test statistical significance. Statistical significance of the percentage of targeted change achieved or the magnitude of the percentage change from baseline was assessed at the 0.05 level using a normal one-sided test. [6] For more information on the Healthy People 2020 methodology for measuring progress toward target attainment and the elimination of health disparities, see: Healthy People Statistical Notes, no 27; available from: https://www.cdc.gov/nchs/data/sta

As changes in GDPR and the protection of personal data have become important topics in the lives of French people, France was the country they trusted the most in processing their personal data. This survey gives insight on the opinion of French internet users on the storage of their personal data to take place outside of the European Union. Thus, the majority were rather opposed to this option (72 percent).

CITYDATA.ai crowdsources and curates mobile app location data across +1500 cities worldwide to simulate the presence and movement of people. Data Specs:

Horizontal Accuracy

Range: 2-25 m Average: 10 meters

Location Query Granularity:

Minimum area: 25 m Maximum area: No limit

Monthly Active Users (MAU): 1.1 Billion MAUs globally Average signal density per device per month: 41.3 Data capturing frequency: Event based (for significant events like significant change in location or speed based on app configuration) Data transmission frequency: Daily, Weekly Demographics data availability: Generated from goverment census data (available upon request)

Promo People inc. Whois Database, discover comprehensive ownership details, registration dates, and more for Promo People inc. with Whois Data Center.

Legislative Election: Number of DPR Seats data was reported at 575.000 Unit in 2019. This records an increase from the previous number of 560.000 Unit for 2014. Legislative Election: Number of DPR Seats data is updated yearly, averaging 560.000 Unit from Dec 2009 (Median) to 2019, with 3 observations. The data reached an all-time high of 575.000 Unit in 2019 and a record low of 560.000 Unit in 2014. Legislative Election: Number of DPR Seats data remains active status in CEIC and is reported by General Elections Commisions. The data is categorized under Indonesia Premium Database’s General Election – Table ID.GEC001: Legislative Election: People's Representative Counsil: Number of DPR Seats.

Full profile of 10,000 people in Israel - download here, data schema here, with more than 40 data points including - Full Name - Education - Location - Work Experience History and many more!

There are additionally millions more Israel people profiles available, visit the LinkDB product page here.

Our LinkDB database is an exhaustive database of publicly accessible LinkedIn people and companies profiles. It contains close to 500 Million people and companies profiles globally.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

The database offers a set of specific situations related to the use of urban public transport that represent a barrier for people with visual or hearing impairment. The database is based on the user experience of people with sensory disabilities in Brno. Although, it contains references to the realities of the Transport Company of the City of Brno, it describes situations that go beyond these locally specific realities and offers inspiration for developing more accessible urban public transport across the Czech Republic. It contains 178 unique barrier situations that were identified through in-depth interviews and focus groups with 30 visually and 20 hearing impaired users of the Brno City Transport Company's services conducted during 2023. The database mainly captures the variability of barrier situations, but does not address the frequency of their occurrence. Thus, situations that may occur very rarely or very often are juxtaposed.

TIAS 12036 First signed 01/17/1992 Last signed 01/17/1992 Entry into force (supplemented by last signed) 01/17/1992 stamped 92-29 C06549084 cover memo

BackgroundPatient and public involvement (PPI) in research is seen as key to ensuring applicability and impact. Undertaking PPI in people after brain injury has long been seen to be a challenge. In 2020 The NIHR Brain Injury MedTech Cooperative developed a programme with the aim of improving PPI involvement, impact and diversity in this population.MethodsThrough a process of iterative development, a PPI programme was created. It built on an existing underutilised database of people after brain injury and their carers who were interested in engaging with PPI and utilised video-calling software. It was led by a Brain injury Survivor acting as Facilitator with admin support from the MedTech Cooperative.ResultsTo date 14 PPI sessions were completed supporting a total of 17 projects. The diversity of the panel members was comparable to that of the population at large. However, further work is needed, especially in engaging people experiencing homelessness, people living outside of England and those with communication impairments. Feedback from researchers was positive and specific impacts are stated.ConclusionThrough the leadership of a facilitator who has an understanding of the lived experience of brain injury a PPI programme has been developed. The use of a video-calling platform enabled a wider representation then a face-to-face group would have and techniques such as shortened sessions and single project presentations ensured engagement and impact.

Provides data on people moving through space, including total number observed, gender breakdown, group size, and age groups.

The City of Seattle Department of Transportation (SDOT) is providing data from the public life studies it has conducted since 2017. These studies consist of measuring the number of people using public space and the types of activities present on select sidewalks across the city, as well as several parks and plazas. The data set is continually updated as SDOT and other parties conduct public life studies using Gehl Institute’s Public Life Data Protocol.

This dataset consists of four component spreadsheets and a GeoJSON file, which provide public life data as well as information about the study design and study locations:

1 Public Life Study: provides details on the different studies that have been conducted, including project information. https://data.seattle.gov/Transportation/Public-Life-Data-Study/7qru-sdcp

2 Public Life Location: provides details on the sites selected for each study, including various attributes to allow for comparison across sites. https://data.seattle.gov/Transportation/Public-Life-Data-Locations/fg6z-cn3y

3 Public Life People Moving: provides data on people moving through space, including total number observed, gender breakdown, group size, and age groups.

4 Public Life People Staying: provides data on people staying still in the space, including total number observed, demographic data, group size, postures, and activities. https://data.seattle.gov/Transportation/Public-Life-Data-People-Staying/5mzj-4rtf

5 Public Life Geography: A GeoJSON file with polygons of every location studied. https://data.seattle.gov/Transportation/Public-Life-Data-Geography/v4q3-5hvp

Please download and refer to the Public Life metadata document - in the attachment section below - for comprehensive information about all of the Public Life datasets.

China Urban Depositor Survey: % of Prefer Investment: Industry data was reported at 12.100 % in Sep 2016. This records a decrease from the previous number of 12.900 % for Jun 2016. China Urban Depositor Survey: % of Prefer Investment: Industry data is updated quarterly, averaging 13.000 % from Mar 2012 (Median) to Sep 2016, with 6 observations. The data reached an all-time high of 16.400 % in Mar 2012 and a record low of 12.100 % in Sep 2016. China Urban Depositor Survey: % of Prefer Investment: Industry data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under China Premium Database’s Household Survey – Table CN.HB: Urban Depositor Survey: The People's Bank of China.

China Entrepreneur Survey: Sales Revenue Collection: % of 'Difficult' Option data was reported at 8.800 % in Jun 2024. This records an increase from the previous number of 8.100 % for Mar 2024. China Entrepreneur Survey: Sales Revenue Collection: % of 'Difficult' Option data is updated quarterly, averaging 10.700 % from Jun 2013 (Median) to Jun 2024, with 45 observations. The data reached an all-time high of 27.600 % in Mar 2020 and a record low of 7.200 % in Dec 2021. China Entrepreneur Survey: Sales Revenue Collection: % of 'Difficult' Option data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OE: Entrepreneur Survey Report: The People's Bank of China.

Provides data on people staying still in the space, including total number observed, demographic data, group size, postures, and activities.

The City of Seattle Department of Transportation (SDOT) is providing data from the public life studies it has conducted since 2017. These studies consist of measuring the number of people using public space and the types of activities present on select sidewalks across the city, as well as several parks and plazas. The data set is continually updated as SDOT and other parties conduct public life studies using Gehl Institute’s Public Life Data Protocol.

This dataset consists of four component spreadsheets and a GeoJSON file, which provide public life data as well as information about the study design and study locations:

1 Public Life Study: provides details on the different studies that have been conducted, including project information. https://data.seattle.gov/Transportation/Public-Life-Data-Study/7qru-sdcp

2 Public Life Location: provides details on the sites selected for each study, including various attributes to allow for comparison across sites. https://data.seattle.gov/Transportation/Public-Life-Data-Locations/fg6z-cn3y

3 Public Life People Moving: provides data on people moving through space, including total number observed, gender breakdown, group size, and age groups. https://data.seattle.gov/Transportation/Public-Life-Data-People-Moving/7rx6-5pgd

4 Public Life People Staying: provides data on people staying still in the space, including total number observed, demographic data, group size, postures, and activities.

5 Public Life Geography: A GeoJSON file with polygons of every location studied. https://data.seattle.gov/Transportation/Public-Life-Data-Geography/v4q3-5hvp

Please download and refer to the Public Life metadata document - in the attachment section below - for comprehensive information about all of the Public Life datasets.

Indonesia Central Kalimantan: East Kotawaringin Regency: Total Valid Votes: People's Conscience Party, Hanura data was reported at 1,705.000 Unit in 2019. This records a decrease from the previous number of 6,671.000 Unit for 2014. Indonesia Central Kalimantan: East Kotawaringin Regency: Total Valid Votes: People's Conscience Party, Hanura data is updated yearly, averaging 4,188.000 Unit from Dec 2014 (Median) to 2019, with 2 observations. The data reached an all-time high of 6,671.000 Unit in 2014 and a record low of 1,705.000 Unit in 2019. Indonesia Central Kalimantan: East Kotawaringin Regency: Total Valid Votes: People's Conscience Party, Hanura data remains active status in CEIC and is reported by General Elections Commisions. The data is categorized under Indonesia Premium Database’s General Election – Table ID.GEG021: Legislative Election: People's Representative Council: Results of Vote Acquisition: Central Kalimantan.

North Sumatera: Nias Regency: Total Electors: Female data was reported at 47,527.000 Person in 2014. North Sumatera: Nias Regency: Total Electors: Female data is updated yearly, averaging 47,527.000 Person from Dec 2014 (Median) to 2014, with 1 observations. North Sumatera: Nias Regency: Total Electors: Female data remains active status in CEIC and is reported by General Elections Commisions. The data is categorized under Indonesia Premium Database’s General Election – Table ID.GEE002: Legislative Election: People's Representative Council: Total Electors and Voters: North Sumatera.