As of June 2024, 98 percent of countries in Europe or 44 out of 45 countries, had data privacy legislation in place. Furthermore, nine percent had the legislation drafted. Nevertheless, 15 percent of markets worldwide had no data privacy legislation yet, and five percent have not provided any data on such laws.
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License information was derived automatically
This dataset provides values for WORLD reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Midyear population estimates and projections for all countries and areas of the world with a population of 5,000 or more // Source: U.S. Census Bureau, Population Division, International Programs Center// Note: Total population available from 1950 to 2100 for 227 countries and areas. Other demographic variables available from base year to 2100. Base year varies by country and therefore data are not available for all years for all countries. For the United States, total population available from 1950-2060, and other demographic variables available from 1980-2060. See methodology at https://www.census.gov/programs-surveys/international-programs/about/idb.html
The Global Data Regulation Diagnostic provides a comprehensive assessment of the quality of the data governance environment. Diagnostic results show that countries have put in greater effort in adopting enabler regulatory practices than in safeguard regulatory practices. However, for public intent data, enablers for private intent data, safeguards for personal and nonpersonal data, cybersecurity and cybercrime, as well as cross-border data flows. Across all these dimensions, no income group demonstrates advanced regulatory frameworks across all dimensions, indicating significant room for the regulatory development of both enablers and safeguards remains at an intermediate stage: 47 percent of enabler good practices and 41 percent of good safeguard practices are adopted across countries. Under the enabler and safeguard pillars, the diagnostic covers dimensions of e-commerce/e-transactions, enablers further improvement on data governance environment.
The Global Data Regulation Diagnostic is the first comprehensive assessment of laws and regulations on data governance. It covers enabler and safeguard regulatory practices in 80 countries providing indicators to assess and compare their performance. This Global Data Regulation Diagnostic develops objective and standardized indicators to measure the regulatory environment for the data economy across countries. The indicators aim to serve as a diagnostic tool so countries can assess and compare their performance vis-á-vis other countries. Understanding the gap with global regulatory good practices is a necessary first step for governments when identifying and prioritizing reforms.
80 countries
Country
Observation data/ratings [obs]
The diagnostic is based on a detailed assessment of domestic laws, regulations, and administrative requirements in 80 countries selected to ensure a balanced coverage across income groups, regions, and different levels of digital technology development. Data are further verified through a detailed desk research of legal texts, reflecting the regulatory status of each country as of June 1, 2020.
Mail Questionnaire [mail]
The questionnaire comprises 37 questions designed to determine if a country has adopted good regulatory practice on data governance. The responses are then scored and assigned a normative interpretation. Related questions fall into seven clusters so that when the scores are averaged, each cluster provides an overall sense of how it performs in its corresponding regulatory and legal dimensions. These seven dimensions are: (1) E-commerce/e-transaction; (2) Enablers for public intent data; (3) Enablers for private intent data; (4) Safeguards for personal data; (5) Safeguards for nonpersonal data; (6) Cybersecurity and cybercrime; (7) Cross-border data transfers.
100%
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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
Databank (databank.worldbank.org) is an online web resource that provides simple and quick access to collections of time series data. It has advanced functions for selecting and displaying data, performing customized queries, downloading data, and creating charts and maps. Users can create dynamic custom reports based on their selection of countries, indicators and years. They offer a growing range of free, easy-to-access tools, research and knowledge to help people address the world's development challenges. For example, the Open Data website offers free access to comprehensive, downloadable indicators about development in countries around the globe.
This selection includes data related to SPC member countries and territories for some of the indicators available in the original database published by the World Bank.
Find more Pacific data on PDH.stat.
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The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank
This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.
For more information, see the World Bank website.
Fork this kernel to get started with this dataset.
https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population
http://data.worldbank.org/data-catalog/ed-stats
https://cloud.google.com/bigquery/public-data/world-bank-education
Citation: The World Bank: Education Statistics
Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
Banner Photo by @till_indeman from Unplash.
Of total government spending, what percentage is spent on education?
Important Note: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer presents country boundaries; first-order (State/Province) internal administrative boundaries and names for most countries. The map was developed by Esri using administrative and city data from Esri; Garmin basemap layers for the world; HERE data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and Africa. Data for select areas of Africa and Pacific Island nations from ~1:288k to ~1:4k (~1:1k in select areas) was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.Select data for the World Boundaries and Places Map is provided by the GIS community. For details on the users who contributed data for this map via the Community Maps Program, view the list of Contributors for the World Boundaries and Places Map. This map is designed for use with maps with darker backgrounds, such as the World Imagery service. An alternate version of this service is also available, the World Boundaries and Places Alternate service, which is designed for overlaying on basemaps with lighter backgrounds, such as the World Shaded Relief service.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Worldwide Bureaucracy Indicators (WWBI) dataset from the World Bank.
The Worldwide Bureaucracy Indicators (WWBI) database is a unique cross-national dataset on public sector employment and wages that aims to fill an information gap, thereby helping researchers, development practitioners, and policymakers gain a better understanding of the personnel dimensions of state capability, the footprint of the public sector within the overall labor market, and the fiscal implications of the public sector wage bill. The dataset is derived from administrative data and household surveys, thereby complementing existing, expert perception-based approaches.
The World Bank introduced the dataset with a series of four blogs:
Can you replicate the figures in the blogs? Can you display any of the data more clearly than in the blogs?
wwbi_data.csv
variable | class | description |
---|---|---|
country_code | character | 3-letter ISO_3166-1 code |
indicator_code | character | code identifying the indicator of bureaucracy |
year | numeric | year of the data |
value | numeric | numeric value of the data |
wwbi_series.csv
variable | class | description |
---|---|---|
indicator_code | character | code identifying the indicator of bureaucracy |
indicator_name | character | name of the indicator |
wwbi_country.csv
variable | class | description |
---|---|---|
country_code | character | 3-letter ISO_3166-1 code |
short_name | character | short or common name for the country |
table_name | character | more alphabetically sortable name of the country |
long_name | character | full name of the country |
x2_alpha_code | character | 2-letter ISO_3166-1 code |
currency_unit | character | currency unit |
special_notes | character | special notes |
region | character | region |
income_group | character | low, lower middle, upper middle, or high income |
wb_2_code | character | alternate 2-letter code |
national_accounts_base_year | integer | national accounts base year |
national_accounts_reference_year | integer | national accounts reference year |
sna_price_valuation | character | UN system of national accounts price valuation |
lending_category | character | International Development Association (IDA), Interanational Bank of Reconstruction and Development (IBRD), a blend or neither |
other_groups | character | Heavily Indebted Poor Countries initiative (HIPC), or countries classified as the "Euro area" |
system_of_national_accounts | integer | which System of National Accounts methodology the country uses (1968, 1993, or 2008 version) |
balance_of_payments_manual_in_use | character | the version of the Balance of Payments Manual used by the country |
external_debt_reporting_status | character | estimate, preliminary, or actual |
system_of_trade | character | Under the general system imports include goods imported for domestic consumption and imports into bonded warehouses and free trade zones. Under the special system imports comprise goods imported for domestic consumption (including transformation and repair) and withdrawals for domestic consumption from bonded warehouses and free trade zones. Goods transported through a country en route to another are excluded. |
government_accounting_concept | character | government accounting concept |
imf_data_dissemination_standard | character | International Monetary Fund data-dissemination standard: Special Data Dissemination Standard (SDDS, 1996, created for countries |
that have or seek to have access to international markets), SDDS Plus (2012, the highest tier of data standards, intended for systemically important economies), enhanced GDDS (e-GDDS, 2015, encouraging participants to emphasize data publication) | ||
latest_household_survey | character | which household survey was most recently administered |
source_of_most_recent_income_and_expenditure_data | character | which survey serves as the basis for income and expenditure data |
vital_registration_complete | logical | whether the vital registration is complete |
latest_agricultural_census | integer | year of latest agricultural census |
latest_industrial_data | integer | year of latest industrial data |
latest_trade_data | in... |
In 2023, Russia ranked first in the world by data breach density. The number of breached e-mail accounts per thousand people in the country amounted to 542. The United States ranked second, with 285 user accounts, while Czechia followed, with 207 accounts. The data breach density in Denmark, Switzerland, and Italy was relatively lower.
Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
License information was derived automatically
The World Database on Protected Areas (WDPA) is the most comprehensive global database of marine and terrestrial protected areas, updated on a monthly basis, and is one of the key global biodiversity data sets being widely used by scientists, businesses, governments, International secretariats and others to inform planning, policy decisions and management. The WDPA is a joint project between UN Environment and the International Union for Conservation of Nature (IUCN). The compilation and management of the WDPA is carried out by UN Environment World Conservation Monitoring Centre (UNEP-WCMC), in collaboration with governments, non-governmental organisations, academia and industry. There are monthly updates of the data which are made available online through the Protected Planet website where the data is both viewable and downloadable. Data and information on the world's protected areas compiled in the WDPA are used for reporting to the Convention on Biological Diversity on progress towards reaching the Aichi Biodiversity Targets (particularly Target 11), to the UN to track progress towards the 2030 Sustainable Development Goals, to some of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) core indicators, and other international assessments and reports including the Global Biodiversity Outlook, as well as for the publication of the United Nations List of Protected Areas. Every two years, UNEP-WCMC releases the Protected Planet Report on the status of the world's protected areas and recommendations on how to meet international goals and targets. Many platforms are incorporating the WDPA to provide integrated information to diverse users, including businesses and governments, in a range of sectors including mining, oil and gas, and finance. For example, the WDPA is included in the Integrated Biodiversity Assessment Tool, an innovative decision support tool that gives users easy access to up-to-date information that allows them to identify biodiversity risks and opportunities within a project boundary. The reach of the WDPA is further enhanced in services developed by other parties, such as the Global Forest Watch and the Digital Observatory for Protected Areas, which provide decision makers with access to monitoring and alert systems that allow whole landscapes to be managed better. Together, these applications of the WDPA demonstrate the growing value and significance of the Protected Planet initiative.
This map presents transportation data, including highways, roads, railroads, and airports for the world.
The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.
You can add this layer on top of any imagery, such as the Esri World Imagery map service, to provide a useful reference overlay that also includes street labels at the largest scales. (At the largest scales, the line symbols representing the streets and roads are automatically hidden and only the labels showing the names of streets and roads are shown). Imagery With Labels basemap in the basemap dropdown in the ArcGIS web and mobile clients does not include this World Transportation map. If you use the Imagery With Labels basemap in your map and you want to have road and street names, simply add this World Transportation layer into your map. It is designed to be drawn underneath the labels in the Imagery With Labels basemap, and that is how it will be drawn if you manually add it into your web map.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset provides values for TOTAL NATURAL RESOURCES RENTS PERCENT OF GDP WB DATA.HTML reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset displays level 0 world administrative boundaries. It contains countries as well as non-sovereign territories (like, for instance, French overseas).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.
GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.
With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.
Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.
Primary Use Cases for GapMaps Live includes:
Some of features our clients love about GapMaps Live include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The database contains 11 index measures of linguistic similarity between 242 countries, both domestically and internationally. The domestic measures capture linguistic similarities present among populations within a single country while the international indexes capture language similarities between two different countries. The indexes, which are based on 6,674 languages, reflect three different dimensions of language: common official languages, common native and acquired spoken languages, and linguistic proximity across different languages. This database has many uses, such as in the study of bilateral flows—including FDI, migration, and international trade—as well as in regional or country level analyses. Version history: Version 2 (Dec. 2024): Version 2 of the Dataset added three additional indices (BPN, BPA, and BPS). It also corrected an issue with the calculation of the linguistic proximity indices in version 1; a small number of languages that terminated at the same point on a linguistic tree were unintentionally treated as being the same language and were omitted from the LPN, LPA, and LPS calculations. This omission affected relatively few indices overall and very few indices significantly. However, a small number of linguistic proximity indices are substantially larger after the correction. Finally, version 2 also reintroduced one language that had been inadvertently omitted in version 1, resulting in a small change to the index values for several countries, primarily in East and Southeast Asia. Version 1 (Mar. 2024): Initial release on Dataverse.
The Religious Characteristics of States Dataset (RCS) was created to fulfill the unmet need for a dataset on the religious dimensions of countries of the world, with the state-year as the unit of observation. The third phase, Chief Executives' Religions, provides data on religious affiliations of countries' 'chief executives,' i.e., their presidents, prime ministers, or other heads of state/government exercising largely real, not ceremonial, political power. The dataset, like others in the RCS data project, is designed expressly for easy merger with datasets of the Correlates of War and Polity projects, datasets by the United Nations, the Religion And State datasets by Jonathan Fox, and the ARDA national profiles.
Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.
The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.
National Coverage.
Individual
The target population is the civilian, non-institutionalized population 15 years and above. The sample is nationally representative.
Sample survey data [ssd]
The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.
Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid.
Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.
The sample size in Latvia was 1,006 individuals.
Face-to-face [f2f]
The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.
Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.
Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.
As of June 2024, 98 percent of countries in Europe or 44 out of 45 countries, had data privacy legislation in place. Furthermore, nine percent had the legislation drafted. Nevertheless, 15 percent of markets worldwide had no data privacy legislation yet, and five percent have not provided any data on such laws.