Portal stores health data from participants from across the United States. Provides interactive Data Browser where anyone can learn about the type and quantity of data that All of Us collects. Users can explore aggregate data including genomic variants, survey responses, physical measurements, electronic health record information, and wearables data.

Internet Usage: Browser Market Share: Tablet: Coc Coc data was reported at 0.000 % in 27 Mar 2024. This stayed constant from the previous number of 0.000 % for 26 Mar 2024. Internet Usage: Browser Market Share: Tablet: Coc Coc data is updated daily, averaging 0.000 % from Mar 2024 (Median) to 27 Mar 2024, with 9 observations. The data reached an all-time high of 0.040 % in 23 Mar 2024 and a record low of 0.000 % in 27 Mar 2024. Internet Usage: Browser Market Share: Tablet: Coc Coc data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s United States – Table US.SC.IU: Internet Usage: Browser Market Share.

United States Internet Usage: Browser Market Share: All Platforms: Whale Browser data was reported at 0.010 % in 02 Jan 2025. This stayed constant from the previous number of 0.010 % for 01 Jan 2025. United States Internet Usage: Browser Market Share: All Platforms: Whale Browser data is updated daily, averaging 0.010 % from Dec 2024 (Median) to 02 Jan 2025, with 7 observations. The data reached an all-time high of 0.010 % in 02 Jan 2025 and a record low of 0.010 % in 02 Jan 2025. United States Internet Usage: Browser Market Share: All Platforms: Whale Browser data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s United States – Table US.SC.IU: Internet Usage: Browser Market Share.

In October 2025, Microsoft's Edge browser had a market share of 10.45 percent in the United States. Edge was first publicly released in July 2015, with the consumer release of Windows 10. However, Chrome held a majority of the market share, with around 71 percent in the same month. What are web browsers? A web browser is a software application for visualizing websites, documents and data. The most popular current browsers are Google Chrome, Apple’s Safari, Microsoft Edge, and Firefox. Historically one of the large players in the segment, Internet Explorer has unfortunately lost its tight grip on the web browser market.As shown by the graph at hand, Google Chrome has been the most popular browser in the United States since December 2013. In other countries, Google Chrome has also taken up a dominating role. In the European browser market, Chrome and Safari have established strong market positions with 61 and 11.4 percent, respectively. On a worldwide scale, Chrome provided a share of around 64 percent in the global web browser market as of December 2021.

This module incorporates an outdoor lesson, a hands-on lesson, and a web-based tool developed by the US Environmental Protection Agency (EPA) called the Eco-Health Relationship Browser. All of the files below are part of EPA Report # EPA/600/R-18/186.

This collection provides users with data about R&D expenditure and R&D personnel broken down by the following institutional sectors: business enterprise (BES); government (GOV); higher education (HES); private non-profit (PNP), total of all sectors.

The R&D expenditure is broken down by source of funds; sector of performance; type of costs; type of R&D; fields of research and development (FORD); https://circabc.europa.eu/ui/group/c1b49c83-24a7-4ff2-951c-621ac0a89fd8/library/b4b841e5-d200-41bc-8f23-d0b1e034f689?p=1&n=10&sort=modified_DESC">socio-economic objectives (NABS 2007) and by regions (https://showvoc.op.europa.eu/#/datasets/ESTAT_Nomenclature_of_Territorial_Units_for_Statistics/data">NUTS 2 level). The business enterprise sector is further broken down by economic activity (https://showvoc.op.europa.eu/#/datasets/ESTAT_Statistical_Classification_of_Economic_Activities_in_the_European_Community_Rev._2/data">NACE Rev.2); size class; industry orientation.

R&D personnel data are broken down by professional position; sector of performance; educational attainment level; sex; field of research and development (https://www.oecd.org/innovation/frascati-manual-2015-9789264239012-en.htm">FORD); regions (https://showvoc.op.europa.eu/#/datasets/ESTAT_Nomenclature_of_Territorial_Units_for_Statistics/data">NUTS 2 level); for the business enterprise sector is further broken down in size class and economic activity (NACE Rev.2). Researchers are further broken down by age class and citizenship.

The periodicity of R&D data are every two years, except for the key R&D indicators (R&D expenditure, R&D personnel (in Full Time Equivalent - FTE) and Researchers (in FTE) by sectors of performance) which are transmitted annually by the EU Member States (from 2003 onwards based on a legal obligation). Some other breakdowns of the data may appear on an annual basis based on voluntary data provisions.

The data are collected through sample or census surveys, from administrative registers or through a combination of sources.

R&D data are available for following countries and country groups:

• All EU Member States; Candidate Countries; EFTA Countries; The Organisation for Economic Cooperation and Development (OECD) is data provider for the United States of America, Japan, South Korea and China.
• Country groups: EU Member States, Euro Area States.

R&D data are compiled in accordance to the guidelines laid down in OECD (2015), https://www.oecd.org/publications/frascati-manual-2015-9789264239012-en.htm">Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities and the European business statistics methodological manual for R&D statistics – 2023 edition - Manuals and guidelines - Eurostat

In October 2025, Safari was the most popular mobile internet browser in the United States, with a market share of over ** percent. Google Chrome came as a close second, with around **** percent of market share. U.S. browser market Considering Apple iPhone’s high user rate in the United States, it is no wonder that Safari, the browser pre-installed on every iPhone, is also widely used. When it comes to the overall browser market, however, Safari’s leading status gets lost: Chrome is the number one internet browser in the United States with a market share of about ** percent, while Safari trails as a second with around **** percent share. Safari lags even further behind in the desktop browser market, with only around **** percent share. This correlates to Apple’s standing in the PC market: ranked as number four in the market as of the first quarter of 2025, Apple’s Mac computers enjoy a relatively niche yet loyal user group. With a nearly ** percent share, Chrome is the dominating figure in the U.S. desktop browser market.

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, _domain-specific databases, and the top journals compare how much data is in institutional vs. _domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find _domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered. Search methods We first compiled a list of known _domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were _domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of _domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared _domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review: Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection. Not even one quarter of the _domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation. See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

In December 2024, Microsoft's Edge browser had a market share of ***** percent in the United States. Edge was first publicly released in July 2015, with the consumer release of Windows 10. However, Chrome held a majority of the market share, with almost ** percent in the same month. What are web browsers? A web browser is a software application for visualizing websites, documents and data. The most popular current browsers are Google Chrome, Apple’s Safari, Microsoft Edge, and Firefox. Historically one of the large players in the segment, Internet Explorer has unfortunately lost its tight grip on the web browser market.As shown by the graph at hand, Google Chrome has been the most popular browser in the United States since December 2013. In other countries, Google Chrome has also taken up a dominating role. In the European browser market, Chrome and Safari have established strong market positions with ** and **** percent, respectively. On a worldwide scale, Chrome provided a share of around ** percent in the global web browser market as of December 2021.

These data identify and provide information on surface and underground coal mines in the United States in 2023. The attribute data for this point dataset come from the U.S. Energy Information Administration, Form EIA-7A, Coal Production and Preparation Report and the U.S. Department of Labor, Mine Safety and Health Administration, Form 7000-2, Quarterly Mine Employment and Coal Production Report. It includes operating surface and underground coal mines in the United States. Additional coal mine data can be found on EIA Coal Data Browser

This is a list of over 325 venues, across the five boroughs that actively distribute free safer sex products. Product availability varies by venue.

The NYC Condom Availability Program maintains a robust list of active venues where New York City (NYC) residents may access free safer sex products across all 5 boroughs of NYC. This list is updated through a variety of mechanisms supported by the NYC Department of Health and Mental Hygiene (NYC DOHMH). At minimum, different sub-sets of this dataset are updated monthly by several vetted DOHMH contracted agencies. Other subsets of this dataset are updated in real-time by NYC Safer Sex Portal users. This entire dataset is refreshed in OpenData on a daily basis. This dataset shows where New York City residents can access NYC free safer sex products throughout the five boroughs. Each row represents pertinent information related to a single venue which distributes NYC safer sex products. This data is collected and maintained to populate the NYC HealthMap (https://a816-healthpsi.nyc.gov/NYCHealthMap/home/) and may be used by other safer sex product [condom/lubricant] locators or map publically available locations. This dataset does not represent all locations which received orders of free safer sex products from NYC DOHMH nor have the listed venues [locations] been endorsed by NYC DOHMH. Furthermore, while the data is sourced from the NYC HealthMap there could be a lag between what is visible inside the HealthMap’s user interface and what is seen on OpenData. The NYC HealthMap is updated ~hourly while OpenData is updated daily. If there are data discrepancies between your export and what is seen inside OpenData’s “View Data” please clear your browsing history/cache and restart your browser.

This map shows which areas have concentrations of high risk businesses in the event of an economic downturn. Areas in red have a higher concentration of one or more of the five categories (by NAICS code): Clothing/Accessory stores, General Merchandise stores, Arts/Entertainment/Recreation, Accommodation, and Food Service/Drinking Places. The popup breaks down count of businesses per category and percent of businesses for the area. Data is 2019 vintage and available by county, tract, and block group. Overall, in the US, these 5 categories make up 11.8% of total businesses.Esri's Business Summary Data: Esri's Business Locations data is extracted from a comprehensive list of businesses licensed from Infogroup. It summarizes the comprehensive list of businesses from Infogroup for select NAICS and SIC summary categories by geography and includes total number of businesses, total sales, and total number of employees for a trade area.Esri's U.S. 2019 Data: Population, age, income, race, home value, spending, business, and market potential are among the topics included in the data suite. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies. To browse, all data variables available within Esri's demographics explore the Data Browser. Additional Esri Resources:Get StartedEsri DemographicsU.S. 2019 Esri Updated DemographicsBusiness Summary DataMethodologies

in search of latest crude oil consumption data I found out very interesting data regarding macroeconomics data on the topics such as real gross state product , Industrial Output ,Real personal income .... and much more region wise and year wise.

I found this dataset very interesting regarding in which field or sectors which region has grown how and how the growth is during 2019 - 2020- 2021 though covid factor would have been more visible if it were a quarterly data but also wanted to include 1999 and 2008 and 2012-2014 major periods and observe how it affected this data points. most of the data and columns are self- explanatory, we can visit the official site for more info.

the credit goes to: US Energy Information Administration https://www.eia.gov/outlooks/steo/data/browser/#/?v=4&f=A&s=&start=2000&end=2022&map=&maptype=0&ctype=linechart&linechart=CGSP_NEC~CGSP_MAC~CGSP_ENC~CGSP_WNC~CGSP_SAC~CGSP_ESC~CGSP_WSC~CGSP_MTN~CGSP_PAC&id=

please check out the line graphs which explain a lot on the offical site!

This map shows the market potential for an adult to have recycled products in the last 12 months in the U.S. in 2019 in a multiscale map (by country, state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level.Market Potential Index and count of adults expected to have recycled products in the last 12 monthsMarket Potential Index and count of adults expected to have participated in or contributed to environmental groups/causes in the last 12 monthsEsri's 2019 Market Potential (MPI) data measures the likely demand for a product or service in an area. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. An MPI compares the demand for a specific product or service in an area with the national demand for that product or service. The MPI values at the US level are 100, representing average demand for the country. A value of more than 100 represents higher demand than the national average, and a value of less than 100 represents lower demand than the national average. For example, an index of 120 implies that demand in the area is 20 percent higher than the US average; an index of 80 implies that demand is 20 percent lower than the US average. See Market Potential database to view the methodology statement and complete variable list.Esri's Civic Activities & Political Affiliation Data Collection includes data on the likelihood to participate in various civic activities such as voting, fundraising, and recycling, as well as data on political affiliations. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product, activity, or service. See the United States Data Browser to view complete variable lists for each Esri demographics collection.Additional Esri Resources:U.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic mapsPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This shows the market potential for an adult to regularly eat organic food in the U.S. in 2021 in a multiscale map (by country, state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Market Potential Index and count of adults expected to regularly eat organic foodMarket Potential Index and count of adults expected to follow various dietary habitsEsri's 2021 Market Potential (MPI) data measures the likely demand for a product or service in an area. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. An MPI compares the demand for a specific product or service in an area with the national demand for that product or service. The MPI values at the US level are 100, representing average demand for the country. A value of more than 100 represents higher demand than the national average, and a value of less than 100 represents lower demand than the national average. For example, an index of 120 implies that demand in the area is 20 percent higher than the US average; an index of 80 implies that demand is 20 percent lower than the US average. See Market Potential database to view the methodology statement and complete variable list.Esri's Psychographics & Advertising Data Collection includes measurements of environmental concern, buying habits such as propensity to buy American products, likelihood to have healthy habits, and advertisement awareness. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. See the United States Data Browser to view complete variable lists for each Esri demographics collection.Additional Esri Resources:U.S. 2021/2026 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic mapsPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This site is for browsing WGS (Whole Genome Shotgun) genomes, TSA (Transcriptome Shotgun Assemblies) and TLS (Targeted Locus Study) sets. WGS sequences are incomplete genomes that have been sequenced by a whole genome shotgun strategy. TSA sequences are transcript sequences that have been computationally assembled from primary RNA sequence data. TLS sequences are large-scale marker gene sequencing studies.

Please consult WGS Submission or TSA Submission pages for more details. https://www.ncbi.nlm.nih.gov/genbank/wgs https://www.ncbi.nlm.nih.gov/genbank/tsa

United States Internet Usage: Browser Market Share: Desktop: Whale Browser data was reported at 0.000 % in 08 Jan 2025. This records a decrease from the previous number of 0.010 % for 07 Jan 2025. United States Internet Usage: Browser Market Share: Desktop: Whale Browser data is updated daily, averaging 0.010 % from Sep 2023 (Median) to 08 Jan 2025, with 70 observations. The data reached an all-time high of 0.020 % in 05 Jan 2025 and a record low of 0.000 % in 08 Jan 2025. United States Internet Usage: Browser Market Share: Desktop: Whale Browser data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s United States – Table US.SC.IU: Internet Usage: Browser Market Share.

The indicator measures the share of the population aged 16 and over reporting unmet needs for medical care due to one of the following reasons: ‘Financial reasons’, ‘Waiting list’ and ‘Too far to travel’ (all three categories are cumulated). Self-reported unmet needs concern a person’s own assessment of whether he or she needed medical examination or treatment (dental care excluded), but did not have it or did not seek it. The data stem from the EU Statistics on Income and Living Conditions (EU SILC). Note on the interpretation: The indicator is derived from self-reported data so it is, to a certain extent, affected by respondents’ subjective perception as well as by their social and cultural background. Another factor playing a role is the different organisation of health care services, be that nationally or locally. All these factors should be taken into account when analysing the data and interpreting the results. Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

BrowserAgent ChatML Dataset (SFT/RFT)

This dataset contains ChatML-style multi-turn dialogues for a browser agent task. The data is prepared as JSON Lines so it can be previewed directly with the Hugging Face Hub Data Visualizer and loaded with the datasets library.

  Links

Paper Github

  Files

sft.jsonl — SFT split (one JSON object per line) rft.jsonl — RFT split (one JSON object per line)

  Schema

Each record is a JSON object containing:

messages:… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/BrowserAgent-Data.

The dataset contained in this project was used to train and test a binary classification machine learning model. This model was used to develop an information retrieval system for retrieving web pages containing relevant information regarding past flash flood events in the US. Researchers and practitioners can use this system to understand more about the flash flooding phenomenon, investigate past flash flooding phenomena, and perform further analyses like causal, and risk, among others. This dataset provides an opportunity to anyone interested to improve upon the performance of the information retrieval system, by using it to train and test more new machine learning models.

Credits to the Authors- Wilkho, Rohan Singh; Gharaibeh, Nasir; Chang, Shi; Zou, Lei

Click here