When asked about "Attitudes towards the internet", most Japanese respondents pick "I'm concerned that my data is being misused on the internet" as an answer. 35 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

This Website Statistics dataset has four resources showing usage of the Lincolnshire Open Data website. Web analytics terms used in each resource are defined in their accompanying Metadata file.

• Website Usage Statistics: This document shows a statistical summary of usage of the Lincolnshire Open Data site for the latest calendar year.

• Website Statistics Summary: This dataset shows a website statistics summary for the Lincolnshire Open Data site for the latest calendar year.

• Webpage Statistics: This dataset shows statistics for individual Webpages on the Lincolnshire Open Data site by calendar year.

• Dataset Statistics: This dataset shows cumulative totals for Datasets on the Lincolnshire Open Data site that have also been published on the national Open Data site Data.Gov.UK - see the Source link.

  Note: Website and Webpage statistics (the first three resources above) show only UK users, and exclude API calls (automated requests for datasets). The Dataset Statistics are confined to users with javascript enabled, which excludes web crawlers and API calls.

These Website Statistics resources are updated annually in January by the Lincolnshire County Council Business Intelligence team. For any enquiries about the information contact opendata@lincolnshire.gov.uk.

The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.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 smartphone users in countries like Australia & Oceania and Asia.

When asked about "Attitudes towards the internet", most Chinese respondents pick "It is important to me to have mobile internet access in any place" as an answer. 48 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

When asked about "Attitudes towards the internet", most Mexican respondents pick "It is important to me to have mobile internet access in any place" as an answer. 56 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

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

The National Broadband Data represents coverage information across Canada for existing broadband service providers with their associated technology types. The coverage information is aggregated and deployed over a grid of hexagons, which cover areas of roughly 25 square km each. Broadband Internet service availability is provided for download/upload speed markers (5/1, 10/2, 25/5 and 50/10 Mbps) where more than 75% of total dwellings covered within the hexagon have access to broadband service offerings meeting these markers. In order to improve the granularity of the broadband data, ISED and the CRTC are providing aggregated and anonymous broadband services data based on the pseudo-household statistical model, hence achieving higher precision in depicting the broadband Internet service availability. This information is available below under the "NBD PHH Speeds" resource. For more information on the pseudo-household statistical model, refer to the Pseudo-Household Demographic Distribution dataset. A representation of broadband services per 250m road segments is now available for download under the “NBD Roads” resource. To generate this dataset, the NBD PHH Speeds information was projected over the nearest road arc from Statistics Canada’s Road Network File, and those roads were spliced in approximately 250m segments. NEW: The data has been augmented to include new presentation layers as published on the National Broadband Map.

The USGS National Hydrography Dataset (NHD) downloadable data collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. For additional information on NHD, go to https://www.usgs.gov/core-science-systems/ngp/national-hydrography.

DWR was the steward for NHD and Watershed Boundary Dataset (WBD) in California. We worked with other organizations to edit and improve NHD and WBD, using the business rules for California. California's NHD improvements were sent to USGS for incorporation into the national database. The most up-to-date products are accessible from the USGS website. Please note that the California portion of the National Hydrography Dataset is appropriate for use at the 1:24,000 scale.

For additional derivative products and resources, including the major features in geopackage format, please go to this page: https://data.cnra.ca.gov/dataset/nhd-major-features Archives of previous statewide extracts of the NHD going back to 2018 may be found at https://data.cnra.ca.gov/dataset/nhd-archive.

In September 2022, USGS officially notified DWR that the NHD would become static as USGS resources will be devoted to the transition to the new 3D Hydrography Program (3DHP). 3DHP will consist of LiDAR-derived hydrography at a higher resolution than NHD. Upon completion, 3DHP data will be easier to maintain, based on a modern data model and architecture, and better meet the requirements of users that were documented in the Hydrography Requirements and Benefits Study (2016). The initial releases of 3DHP include NHD data cross-walked into the 3DHP data model. It will take several years for the 3DHP to be built out for California. Please refer to the resources on this page for more information.

The FINAL,STATIC version of the National Hydrography Dataset for California was published for download by USGS on December 27, 2023. This dataset can no longer be edited by the state stewards. The next generation of national hydrography data is the USGS 3D Hydrography Program (3DHP).

Questions about the California stewardship of these datasets may be directed to nhd_stewardship@water.ca.gov.

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

A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.

This dataset contains files and materials in support of the California's Groundwater Live website. California's Groundwater Live is a user-friendly platform that allows users to view and interact with the latest information on groundwater in California. California's Groundwater Live website can be found at: https://sgma.water.ca.gov/CalGWLive/.

The City requires permits for commercial and residential development, such as new single-family homes, commercial construction, remodels, additions and related activity like trade (mechanical, electrical, and plumbing) work. City review ensures that construction projects adhere to the City’s adopted Building Codes and the Unified Development Code to enhance the health and safety for you, your family and our community.

The datasets below are provided as-is as a record of building activity in San Antonio. For any additional information not contained below, or for information and documentation related to building activity, a request for information (“open records request”) is needed; please refer to the City of San Antonio Open Government Request site at https://www.sa.gov/Directory/Departments/CE/Open-Records-Request to submit a request.

The following datasets related to regulated drinking water system facilities in California have been developed and are available for the purpose of the March 23, 2023, OEDP workshop. The main purpose of the workshop is to engage community members and researchers in understanding datasets maintained and shared by the California State Water Resources Control Board Drinking Water Program and explore possibilities for their use and enhancement. Input from this workshop could be used to inform recommendations OEDP makes to partnering organizations about how to collect, share, and structure their open datasets. Conversations could also support community organizations in using water datasets to inform programming, policy advocacy, or organizing.

Making clinical audit data transparent In his transparency and open data letter to Cabinet Ministers on 7 July 2011, the Prime Minister restated the commitment to make clinical audit data available from the national audits within the National Clinical Audit and Patient Outcomes Programme. The National Lung Cancer Audit (NLCA) was identified as the pilot for this data release. The data was released in an open and standardised format for the first time in December 2011, and each year onward, data from the National Lung Cancer Audit will be made available in CSV format. The data are also being made available on the data.gov website. Covering all Strategic Clinical Networks and NHS Trusts in England, the data from the audit includes information about data completeness, audit process and outcome measures. The data will be available in a pdf format with the National Lung Cancer Audit 2014 annual report. What information is being made available? Measures about the process of care given to patients Information about care outcomes and treatment. The data also provides Audit participation by Trust and data completeness for the key fields. This data does not list data about individual patients nor does it contain any patient identifiable data. Using and interpreting the data Data from the National Lung Cancer Audit requires careful interpretation, and the information should not be looked at in isolation when assessing standards of care. Data is analysed either by cancer network or by place first seen in secondary care for the calendar year 2013 (except where noted). As a result, some trusts that only provide some specialist treatments for patients and do not routinely supply diagnostic data are not properly represented in these data. This is because all the analyses of the NLCA to date have been carried out by 'place first seen' and clinical networks. The 'place first seen' most closely represents the Clinical Multi-Disciplinary Team (MDT) which makes the first treatment decisions (in partnership with representatives from the specialist centres who sit on these peripheral MDTs). We largely know the population base for these MDTs and that number provides the 'denominator' for the outcome measures. It is much more difficult to define a population denominator for specialist centres and the treatment they provide is usually only one part of a complex care pathway. So taking the raw data at face value gives a very distorted picture both of their activity and performance. Accessing the data The data are being made available on the data.gov website. Each year three files of data from the National Lung Cancer Audit will be made available in CSV format. Trusts and Networks are identified by name and their national code. What does the data cover? The data measure levels of completeness for data submitted to the NLCA and measures of performance in the audit at trust level for key performance measures for assessing standards of care for lung cancer in secondary care. Details of these standards can be found in appendix 2 of the NLCA report. Are all Trusts included? All Trusts in England that manage patients diagnosed with lung cancer (excluding mesothelioma) are included. The audit also covers Wales. What period does the data cover? This data were extracted from the NLCA database in July 2014 and covers patients first seen in the calendar year 2013 (except where noted).

The dataset contains a hierarchal listing of New York State counties, cities, towns, and villages, as well as official locality websites

Your website loading page is pretty useful – it tells your site users that yes, your site is really loading normally. But it’s also probably at least a little bit boring. And while there’s nothing terrible about a boring loading screen – boring still works – it does mean you’re wasting valuable space, particularly in […]