The Bath and North East Somerset Council has one of the largest databases in the world on the production and trade of minerals. The dataset contains annual production statistics by mass for more than 70 mineral commodities covering the majority of economically important and internationally-traded minerals, metals and mineral-based materials. For each commodity the annual production statistics are recorded for individual countries, grouped by continent. Import and export statistics are also available for years up to 2002. Maintenance of the database is funded by the Science Budget and output is used by government, private industry and others in support of policy, economic analysis and commercial strategy. As far as possible the production data are compiled from primary, official sources. Quality assurance is maintained by participation in such groups as the International Consultative Group on Non-ferrous Metal Statistics. Individual commodity and country tables are available for sale on request.

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.

Nigeria NG: Imports: % of Total Goods Imports: The Arab World data was reported at 3.044 % in 2016. This records an increase from the previous number of 2.432 % for 2015. Nigeria NG: Imports: % of Total Goods Imports: The Arab World data is updated yearly, averaging 0.909 % from Dec 1962 (Median) to 2016, with 54 observations. The data reached an all-time high of 3.228 % in 1996 and a record low of 0.189 % in 1985. Nigeria NG: Imports: % of Total Goods Imports: The Arab World data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Imports. Merchandise imports from economies in the Arab World are the sum of merchandise imports by the reporting economy from economies in the Arab World. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

This dataset provides high-resolution gridded temperature and precipitation observations from a selection of sources. Additionally the dataset contains daily global average near-surface temperature anomalies. All fields are defined on either daily or monthly frequency. The datasets are regularly updated to incorporate recent observations. The included data sources are commonly known as GISTEMP, Berkeley Earth, CPC and CPC-CONUS, CHIRPS, IMERG, CMORPH, GPCC and CRU, where the abbreviations are explained below. These data have been constructed from high-quality analyses of meteorological station series and rain gauges around the world, and as such provide a reliable source for the analysis of weather extremes and climate trends. The regular update cycle makes these data suitable for a rapid study of recently occurred phenomena or events. The NASA Goddard Institute for Space Studies temperature analysis dataset (GISTEMP-v4) combines station data of the Global Historical Climatology Network (GHCN) with the Extended Reconstructed Sea Surface Temperature (ERSST) to construct a global temperature change estimate. The Berkeley Earth Foundation dataset (BERKEARTH) merges temperature records from 16 archives into a single coherent dataset. The NOAA Climate Prediction Center datasets (CPC and CPC-CONUS) define a suite of unified precipitation products with consistent quantity and improved quality by combining all information sources available at CPC and by taking advantage of the optimal interpolation (OI) objective analysis technique. The Climate Hazards Group InfraRed Precipitation with Station dataset (CHIRPS-v2) incorporates 0.05° resolution satellite imagery and in-situ station data to create gridded rainfall time series over the African continent, suitable for trend analysis and seasonal drought monitoring. The Integrated Multi-satellitE Retrievals dataset (IMERG) by NASA uses an algorithm to intercalibrate, merge, and interpolate “all'' satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators over the entire globe at fine time and space scales for the Tropical Rainfall Measuring Mission (TRMM) and its successor, Global Precipitation Measurement (GPM) satellite-based precipitation products. The Climate Prediction Center morphing technique dataset (CMORPH) by NOAA has been created using precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively. Then, geostationary IR data are used as a means to transport the microwave-derived precipitation features during periods when microwave data are not available at a location. The Global Precipitation Climatology Centre dataset (GPCC) is a centennial product of monthly global land-surface precipitation based on the ~80,000 stations world-wide that feature record durations of 10 years or longer. The data coverage per month varies from ~6,000 (before 1900) to more than 50,000 stations. The Climatic Research Unit dataset (CRU v4) features an improved interpolation process, which delivers full traceability back to station measurements. The station measurements of temperature and precipitation are public, as well as the gridded dataset and national averages for each country. Cross-validation was performed at a station level, and the results have been published as a guide to the accuracy of the interpolation. This catalogue entry complements the E-OBS record in many aspects, as it intends to provide high-resolution gridded meteorological observations at a global rather than continental scale. These data may be suitable as a baseline for model comparisons or extreme event analysis in the CMIP5 and CMIP6 dataset.

As of June 2024, 71 percent of countries worldwide had data privacy legislation in place. Furthermore, nine percent had the legislation drafted. Overall, 15 percent of markets worldwide had no data privacy legislation yet, and five percent have not provided any data on such laws.

The World Bank Open Data site provides an entry-point into the World Bank's Data Bank. It includes demographic, developmental, time-series and geospatial data from the Data Bank's data catalogue.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

Based on a March 2023 global survey, the United Arab Emirates reported the highest share of respondents who trusted travel companies towards handling personal data, with over 70 percent of the sample in that country stating so. By contrast, the study showed that respondents from the United States recorded the highest level of distrust.

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 ***. The United States ranked second, with *** user accounts, while Czechia followed, with *** accounts. The data breach density in Denmark, Switzerland, and Italy was relatively lower.

The Gridded Population of the World, Version 3 (GPWv3): Centroids consists of estimates of human population counts and densities for the years 1990, 1995, 2000, 2005, 2010, and 2015 by administrative Unit centroid location. The centroids are based on the 399,781 input administrative Units used in GPWv3. In addition to population counts and variables, the centroids have associated administrative Unit names and the land area of contained within the administrative Unit. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).

The World Wide Lightning Location Network (WWLLN) has monitored global lightning since late 2004. Since 2013, the number of global WWLLN sensors has remained largely consistent. This WWLLN Monthly Thunder Hour dataset is calculated from lightning detections from 1 January 2013 onward and is an ongoing dataset. A thunder hour is an hour during which thunder can be heard at a given location. Thunder hours represent a historical measure of lightning occurrence and a metric of thunderstorm frequency that is comparatively less sensitive to geographic variations in the detection capabilities of a lightning location system. Thunder hours are the number of hours in a given month during which at least two WWLLN strokes were observed within 15 km of each grid point. Each file includes the monthly accumulated thunder hours for one year. The data are provided at 0.05° latitude and longitude resolution.

The Global Hawk Navigation EPOCH dataset consists of the real-time navigation and housekeeping data that was acquired by various instruments aboard the Global Hawk during the East Pacific Origins and Characteristics of Hurricanes (EPOCH) project. EPOCH was a NASA program manager training opportunity directed at training NASA young scientists in conceiving, planning, and executing a major airborne science field program. The goals of the EPOCH project were to sample tropical cyclogenesis or intensification of an Eastern Pacific hurricane and to train the next generation of NASA Airborne Science Program leadership. The data files are available from July 27, 2017 through August 31, 2017 in CSV format with associated KML browse files.

In 2023, 62 percent of surveyed internet users worldwide expressed concerns regarding organizational use of AI. A further 60 percent said they had already lost trust in companies because of their use of AI. However, some 48 percent of the survey respondents said AI can positively impact and help improve our lives. Furthermore, 54 percent said they would share anonymized personal data to improve AI products.

As of January 2025, around 13.7 percent of paid iOS apps admitted collecting data from users engaging with their mobile products. In comparison, approximately 53 percent of free-to-download iOS apps reported they collect private data from users worldwide, while approximately 86 percent of paid apps have not declared whether they collect users' privacy data.

This dataset contains occurrence data of flora and fauna species. From the Netherlands on a 5 x 5 km scale, data from other countries are exact. Observations from Belgium are excluded and can be accessed on GBIF through Natuurpunt and Natagora. It summarizes the observations recorded by >175.000 volunteers.

The World Health Survey was implemented by WHO in 2002–2004 in partnership with 70 countries to generate information on the health of adult populations and health systems. The total sample size in these cross-sectional studies includes over 300,000 individuals. Survey materials and data are available through the WHO World Health Survey Data Archive accessible from the WHS webpage. (From the WHO World Health Survey webpage).

Network and loading data for a real-world distribution network in the North-East of England.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

This data set describes a global land/water mask for satellite ocean color studies in a medium resolution (~230m/pixel; or 480 pixels per degree of longitude or latitude). Please acknowledge any use of this data set by citing the following reference:

K. Mikelsons, M. Wang, X. Wang, and L. Jiang, Global land mask for satellite ocean color remote sensing, Remote Sens. Environ., 257, 112356 (2021). https://doi.org/10.1016/j.rse.2021.112356

This data set was derived from five data sources described in the following references:

[1] Carroll, M. L., Townshend, J. R., DiMiceli, C. M., Noojipady, P., and Sohlberg, R. A. (2009), A new global raster water mask at 250 m resolution, Int. J. Digit. Earth, 2, 291–308.

[2] Carroll, M. L., DiMiceli, C. M., Townshend, J. R., Sohlberg, R. A., Elders, A. I., Devadiga, S., Sayer, A. M., and Levy, R. C. (2017), Development of an operational land water mask for MODIS Collection 6, and influence on downstream data products, Int. J. Digit. Earth, 10, 207–218.

[3] Pekel, J. F., Cottam, A., Gorelick, N., and Belward, A. S. (2016), High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422.

[4] Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., and Townsend, J. R. G. (2013), High-resolution global maps of 21st-century forest cover change, Science, 342, 850–853.

[5] www.OpenStreetMap.org

Dataset is taken from https://www.kaggle.com/unsdsn/world-happiness but updated with a column named "Continent".