How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

The Global Fire Assimilation System (GFAS) assimilates fire radiative power (FRP) observations from satellite-based sensors to produce daily estimates of emissions from wildfires and biomass burning. FRP is a measure of the energy released by the fire and is therefore a measure of how much vegetation is burned.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days (monthly means are available around the 6th of each month). In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 monthly mean data on single levels from 1940 to present".

Single prediction that uses

observations
prior information about the Earth-system
ECMWF's highest-resolution model

HRES Direct model output Products offers "High Frequency products"

4 forecast runs per day (00/06/12/18) (see dissemination schedule for details)
Hourly steps to step 144 for all four runs

Not all post-processed Products are available at 06/18 runs or in hourly steps.

SummaryThe rate of confirmed COVID-19 cases among Marylanders per 100,000 people statewide.DescriptionThe MD COVID-19 cases per 100K population, statewide layer is the rate of confirmed daily COVID-19 cases among Marylanders per 100,000 people statewide. This rate is a 7-day average, calculated using the sum of the CasesByCounty layer and the 2019 estimated county populations (Maryland Department of Planning).COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

ERA5 is the fifth generation ECMWF atmospheric reanalysis of the global climate. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset. ERA5 replaces its predecessor, the ERA-Interim reanalysis. ERA5 MONTHLY provides aggregated values for each month for seven ERA5 climate reanalysis parameters: 2m air temperature, 2m dewpoint temperature, total precipitation, mean sea level pressure, surface pressure, 10m u-component of wind and 10m v-component of wind. Additionally, monthly minimum and maximum air temperature at 2m has been calculated based on the hourly 2m air temperature data. Monthly total precipitation values are given as monthly sums. All other parameters are provided as monthly averages. ERA5 data is available from 1940 to three months from real-time, the version in the EE Data Catalog is available from 1979. More information and more ERA5 atmospheric parameters can be found at the Copernicus Climate Data Store. Provider's Note: Monthly aggregates have been calculated based on the ERA5 hourly values of each parameter.

SummaryThe cumulative number of COVID-19 serology testing results among Maryland residents.DescriptionThe MD COVID-19 serology testing data layer is a collection of cumulative COVID-19 serology test results. Total numbers are broken down into positive and negative results. These numbers refer to people tested, not individual tests, some people have had multiple tests. For people with both a negative and a positive test, the positive result is counted. Inconclusive/indeterminate test results are not included in the total. The numbers are updated weekly.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

SummaryThe cumulative number of Maryland residents who tested negative for COVID-19.DescriptionThe MD COVID-19 - Number of Persons Tested Negative data layer is a collection of the number of people statewide who have tested negative for COVID-19 reported each day by each local health department via the NEDSS system.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

SummaryThe cumulative number of COVID-19 positive Maryland residents who have been released from home isolation.DescriptionThe MD COVID-19 - Total Number Released from Isolation data layer is a collection of the statewide cumulative total of individuals who tested positive for COVID-19 that have been reported each day by each local health department via the ESSENCE system as having been released from home isolation. As "recovery" can mean different things as people experience COVID-19 disease to varying degrees of severity, MDH reports on individuals released from isolation. "Released from isolation" refers to those who have met criteria and are well enough to be released from home isolation. Some of these individuals may have been hospitalized at some point.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

Content

The Global Financial Inclusion Database provides 800 country-level indicators of financial inclusion summarized for all adults and disaggregated by key demographic characteristics-gender, age, education, income, and rural residence. Covering more than 140 economies, the indicators of financial inclusion measure how people save, borrow, make payments and manage risk.

The reference citation for the data is: Demirguc-Kunt, Asli, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden. 2015. “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, DC.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore the World Bank using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using the World Bank's APIs and Kaggle's API.

Cover photo by ZACHARY STAINES on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Content

This set of contract awards includes data on commitments against contracts that were reviewed by the Bank before they were awarded (prior-reviewed Bank-funded contracts) under IDA/IBRD investment projects and related Trust Funds. This dataset does not list all contracts awarded by the Bank, and should be viewed only as a guide to determine the distribution of major contract commitments among the Bank's member countries. "Supplier Country" represents place of supplier registration, which may or not be the supplier's actual country of origin. Information does not include awards to subcontractors nor account for cofinancing. The Procurement Policy and Services Group does not guarantee the data included in this publication and accepts no responsibility whatsoever for any consequences of its use. The World Bank complies with all sanctions applicable to World Bank transactions.

Visit Bank’s Procurement page for more information: http://go.worldbank.org/9KQZWXNOI0

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore World Bank's Financial Data using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

This dataset is distributed under a Creative Commons Attribution 3.0 IGO license.

Cover photo by Ed Robertson on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

This dataset is distributed under Creative Commons Attribution 3.0 IGO

Content

Relevant indicators drawn from the World Development Indicators, reorganized according to the goals and targets of the Sustainable Development Goals (SDGs). These indicators may help to monitor SDGs, but they are not always the official indicators for SDG monitoring.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore the World Bank using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using the World Bank's APIs and Kaggle's API.

Cover photo by NA on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Deprecated as of 4/21/2023On 4/27/2023 several COVID-19 datasets were retired and no longer included in public COVID-19 data dissemination. For more information, visit https://imap.maryland.gov/pages/covid-dataSummaryThe cumulative number of COVID-19 vaccinations for persons aged 65+ within a single Maryland jurisdiction: Persons fully vaccinated and those who have received at least one dose.DescriptionThe MD COVID-19—Persons 65+ Fully Vaccinated layer represents the number of people in each Maryland jurisdiction aged 65 and older who have either received at least one dose of COVID-19 vaccine in a two-dose regimen or are fully vaccinated (have either received a single shot regimen or have completed the second dose in a two-dose regimen), reported each day into ImmuNet.CDC COVID10 Vaccinations in the United States,CountyCOVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

This point layer contains monthly summaries of daily temperatures (means, minimums, and maximums) and precipitation levels (sum, lowest, and highest) for the period January 1981 through December 2010 for weather stations in the Global Historical Climate Network Daily (GHCND). Data in this service were obtained from web services hosted by the Applied Climate Information System ( ACIS). ACIS staff curate the values for the U.S., including correcting erroneous values, reconciling data from stations that have been moved over their history, etc. The data were compiled at Esri from publicly available sources hosted and administered by NOAA. Because the ACIS data is updated and corrected on an ongoing basis, the date of collection for this layer was Jan 23, 2019. The following process was used to produce this dataset:Download the most current list of stations from ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt. Import this into Microsoft Excel and save as CSV. In ArcGIS, import the CSV as a geodatabase table and use the XY Event layer tool to locate each point. Using a detailed U.S. boundary extract the points that fall within the 50 U.S. States, the District of Columbia, and Puerto Rico. Using Python with DA.UpdateCursor and urllib2 access the ACIS Web Services API to determine whether each station had at least 50 monthly values of temperature data for each station. Delete the other stations. Using Python add the necessary field names and acquire all monthly values for the remaining stations. Thus, there are stations that have some missing data. Using Python Add fields and convert the standard values to metric values so both would be present. Thus, there are four sets of monthly data in this dataset: Monthly means, mins, and maxes of daily temperatures - degrees Fahrenheit. Monthly mean of monthly sums of precipitation and the level of precipitation that was the minimum and maximum during the period 1981 to 2010 - mm. Temperatures in 3a. in degrees Celcius. Precipitation levels in 3b in Inches. After initially publishing these data in a different service, it was learned that more precise coordinates for station locations were available from the Enhanced Master Station History Report (EMSHR) published by NOAA NCDC. With the publication of this layer these most precise coordinates are used. A large subset of the EMSHR metadata is available via EMSHR Stations Locations and Metadata 1738 to Present. If your study area includes areas outside of the U.S., use the World Historical Climate - Monthly Averages for GHCN-D Stations 1981 - 2010 layer. The data in this layer come from the same source archive, however, they are not curated by the ACIS staff and may contain errors. Revision History: Initially Published: 23 Jan 2019 Updated 16 Apr 2019 - We learned more precise coordinates for station locations were available from the Enhanced Master Station History Report (EMSHR) published by NOAA NCDC. With the publication of this layer the geometry and attributes for 3,222 of 9,636 stations now have more precise coordinates. The schema was updated to include the NCDC station identifier and elevation fields for feet and meters are also included. A large subset of the EMSHR data is available via EMSHR Stations Locations and Metadata 1738 to Present. Cite as: Esri, 2019: U.S. Historical Climate - Monthly Averages for GHCN-D Stations for 1981 - 2010. ArcGIS Online, Accessed

The world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolongued development arc in Sub-Saharan Africa.

The global number of internet users in was forecast to continuously increase between 2024 and 2029 by in total 1.3 billion users (+23.66 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 7 billion users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.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 internet users in countries like the Americas and Asia.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 149 zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than 394 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 two 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 19.2 percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached 6.7 zettabytes.

As a result of the continued annual growth in global air traffic passenger demand, the number of airplanes that were involved in accidents is on the increase. Although the United States is ranked among the 20 countries with the highest quality of air infrastructure, the U.S. reports the highest number of civil airliner accidents worldwide. 2020 was the year with more plane crashes victims, despite fewer flights The number of people killed in accidents involving large commercial aircraft has risen globally in 2020, even though the number of commercial flights performed last year dropped by 57 percent to 16.4 million. More than half of the total number of deaths were recorded in January 2020, when an Ukrainian plane was shot down in Iranian airspace, a tragedy that killed 176 people. The second fatal incident took place in May, when a Pakistani airliner crashed, killing 97 people. Changes in aviation safety In terms of fatal accidents, it seems that aviation safety experienced some decline on a couple of parameters. For example, there were 0.37 jet hull losses per one million flights in 2016. In 2017, passenger flights recorded the safest year in world history, with only 0.11 jet hull losses per one million flights. In 2020, the region with the highest hull loss rate was the Commonwealth of Independent States. These figures do not take into account accidents involving military, training, private, cargo and helicopter flights.

In 2022, the number of deaths due to road accidents in India among victims between 25 to 35 years amounted to nearly 42.6 thousand, the most compared to other age groups. That year, there were over 169 thousand accidental fatalities across the south Asian country. Over-speeding was the leading contributor of accidents. Combined, state and national highways recorded around 258 thousand road accidents in 2022. This number had dropped significantly in 2016, before increasing again in recent years.

Accident demographics

The Indian subcontinent ranked first in terms of road accident deaths according to the World Road Statistics which comprised of 199 countries. A majority of victims were two-wheeler commuters. Additionally, pedestrians made up a high share of victims as well, reflecting the lack of infrastructure, be it improper footpaths and the lack of foot-over bridges or negligence of traffic rules. About 70 percent of the road accidents in India accounted for about six percent of the global road traffic accidents.

Accident prevention

Poor enforcement of fines, in addition to mild punishments and corruption encourages drivers, especially among young Indians, to engage in rash driving. Accident awareness programs were initiated by the government among the motorists, along with the National Road Safety Policy to encourage safe transport, strict enforcement of safety laws and fines and establishment of road safety database.

During the third quarter of 2024, data breaches exposed more than 422 million records worldwide. Since the first quarter of 2020, the highest number of data records were exposed in the first quarter of 202, more than 818 million data sets. Data breaches remain among the biggest concerns of company leaders worldwide. The most common causes of sensitive information loss were operating system vulnerabilities on endpoint devices. Which industries see the most data breaches? Meanwhile, certain conditions make some industry sectors more prone to data breaches than others. According to the latest observations, the public administration experienced the highest number of data breaches between 2021 and 2022. The industry saw 495 reported data breach incidents with confirmed data loss. The second were financial institutions, with 421 data breach cases, followed by healthcare providers. Data breach cost Data breach incidents have various consequences, the most common impact being financial losses and business disruptions. As of 2023, the average data breach cost across businesses worldwide was 4.45 million U.S. dollars. Meanwhile, a leaked data record cost about 165 U.S. dollars. The United States saw the highest average breach cost globally, at 9.48 million U.S. dollars.