In 2023, 0.27 percent of surveyed internet users in Luxembourg used the internet to access public databases and registers, up from 0.23 percent in 2022.
The statistic depicts the assessment of U.S. public libraries regarding the importance of public libraries in the U.S. as a service provider for education resources and databases. 35.2 percent of the responding public libraries stated that the this (Education resources and databases for home schooling) service was one of the most important.
https://www.ons.gov.uk/aboutus/whatwedo/statistics/requestingstatistics/approvedresearcherschemehttps://www.ons.gov.uk/aboutus/whatwedo/statistics/requestingstatistics/approvedresearcherscheme
The Public Health Research Database (PHRD) is a linked asset which currently includes Census 2011 data; Mortality Data; Hospital Episode Statistics (HES); GP Extraction Service (GPES) Data for Pandemic Planning and Research data. Researchers may apply for these datasets individually or any combination of the current 4 datasets.
The purpose of this dataset is to enable analysis of deaths involving COVID-19 by multiple factors such as ethnicity, religion, disability and known comorbidities as well as age, sex, socioeconomic and marital status at subnational levels. 2011 Census data for usual residents of England and Wales, who were not known to have died by 1 January 2020, linked to death registrations for deaths registered between 1 January 2020 and 8 March 2021 on NHS number. The data exclude individuals who entered the UK in the year before the Census took place (due to their high propensity to have left the UK prior to the study period), and those over 100 years of age at the time of the Census, even if their death was not linked. The dataset contains all individuals who died (any cause) during the study period, and a 5% simple random sample of those still alive at the end of the study period. For usual residents of England, the dataset also contains comorbidity flags derived from linked Hospital Episode Statistics data from April 2017 to December 2019 and GP Extraction Service Data from 2015-2019.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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Activity data for small molecules are invaluable in chemoinformatics. Various bioactivity databases exist containing detailed information of target proteins and quantitative binding data for small molecules extracted from journals and patents. In the current work, we have merged several public and commercial bioactivity databases into one bioactivity metabase. The molecular presentation, target information, and activity data of the vendor databases were standardized. The main motivation of the work was to create a single relational database which allows fast and simple data retrieval by in-house scientists. Second, we wanted to know the amount of overlap between databases by commercial and public vendors to see whether the former contain data complementing the latter. Third, we quantified the degree of inconsistency between data sources by comparing data points derived from the same scientific article cited by more than one vendor. We found that each data source contains unique data which is due to different scientific articles cited by the vendors. When comparing data derived from the same article we found that inconsistencies between the vendors are common. In conclusion, using databases of different vendors is still useful since the data overlap is not complete. It should be noted that this can be partially explained by the inconsistencies and errors in the source data.
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Provides a list of all the datasets available in the Public Data Inventory for the Small Business Administration.
Al-Sweady Public Inquiry Witness Database. This Microsoft Access Database holds contact details for Witnesses who were required to attend the Public Inquiry.
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
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This data from USAFacts provides US COVID-19 case and death counts by state and county. This data is sourced from the CDC, and state and local health agencies. For more information, see the USAFacts site on the Coronavirus. Interactive data visualizations are also available via USAFacts. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery . This dataset has significant public interest in light of the COVID-19 crisis. All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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Boston Public Schools (BPS) schools for the school year 2018-2019. Updated September 2018.
https://www.wiseguyreports.com/pages/privacy-policyhttps://www.wiseguyreports.com/pages/privacy-policy
BASE YEAR | 2024 |
HISTORICAL DATA | 2019 - 2024 |
REPORT COVERAGE | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
MARKET SIZE 2023 | 29.79(USD Billion) |
MARKET SIZE 2024 | 37.25(USD Billion) |
MARKET SIZE 2032 | 222.12(USD Billion) |
SEGMENTS COVERED | Deployment Model ,Data Model ,Database Type ,Database Service ,Regional |
COUNTRIES COVERED | North America, Europe, APAC, South America, MEA |
KEY MARKET DYNAMICS | Rising adoption of cloudbased solutions Increasing demand for data storage and analytics Growing need for cost optimization Emergence of new technologies such as Kubernetes and Serverless Growing popularity of open source databases |
MARKET FORECAST UNITS | USD Billion |
KEY COMPANIES PROFILED | Google ,Amazon Web Services ,DataStax ,MongoDB ,Red Hat ,Couchbase ,Instaclustr ,Cockroach Labs ,Yugabyte ,Redis Labs ,Platform9 ,VMware Tanzu ,Microsoft ,Clustrix |
MARKET FORECAST PERIOD | 2024 - 2032 |
KEY MARKET OPPORTUNITIES | Hybrid and Multicloud Adoption Growing Demand for Edge Computing Increasing Focus on Data Security Adoption of CloudNative Analytics Expansion into Emerging Markets |
COMPOUND ANNUAL GROWTH RATE (CAGR) | 25.01% (2024 - 2032) |
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Publicly accessible databases often impose query limits or require registration. Even when I maintain public and limit-free APIs, I never wanted to host a public database because I tend to think that the connection strings are a problem for the user.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
is designed
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
The NIHR is one of the main funders of public health research in the UK. Public health research falls within the remit of a range of NIHR Research Programmes, NIHR Centres of Excellence and Facilities, plus the NIHR Academy. NIHR awards from all NIHR Research Programmes and the NIHR Academy that were funded between January 2006 and the present extraction date are eligible for inclusion in this dataset. An agreed inclusion/exclusion criteria is used to categorise awards as public health awards (see below). Following inclusion in the dataset, public health awards are second level coded to one of the four Public Health Outcomes Framework domains. These domains are: (1) wider determinants (2) health improvement (3) health protection (4) healthcare and premature mortality.More information on the Public Health Outcomes Framework domains can be found here.This dataset is updated quarterly to include new NIHR awards categorised as public health awards. Please note that for those Public Health Research Programme projects showing an Award Budget of £0.00, the project is undertaken by an on-call team for example, PHIRST, Public Health Review Team, or Knowledge Mobilisation Team, as part of an ongoing programme of work.Inclusion criteriaThe NIHR Public Health Overview project team worked with colleagues across NIHR public health research to define the inclusion criteria for NIHR public health research awards. NIHR awards are categorised as public health awards if they are determined to be ‘investigations of interventions in, or studies of, populations that are anticipated to have an effect on health or on health inequity at a population level.’ This definition of public health is intentionally broad to capture the wide range of NIHR public health awards across prevention, health improvement, health protection, and healthcare services (both within and outside of NHS settings). This dataset does not reflect the NIHR’s total investment in public health research. The intention is to showcase a subset of the wider NIHR public health portfolio. This dataset includes NIHR awards categorised as public health awards from NIHR Research Programmes and the NIHR Academy. This dataset does not currently include public health awards or projects funded by any of the three NIHR Research Schools or any of the NIHR Centres of Excellence and Facilities. Therefore, awards from the NIHR Schools for Public Health, Primary Care and Social Care, NIHR Public Health Policy Research Unit and the NIHR Health Protection Research Units do not feature in this curated portfolio.DisclaimersUsers of this dataset should acknowledge the broad definition of public health that has been used to develop the inclusion criteria for this dataset. This caveat applies to all data within the dataset irrespective of the funding NIHR Research Programme or NIHR Academy award.Please note that this dataset is currently subject to a limited data quality review. We are working to improve our data collection methodologies. Please also note that some awards may also appear in other NIHR curated datasets. Further informationFurther information on the individual awards shown in the dataset can be found on the NIHR’s Funding & Awards website here. Further information on individual NIHR Research Programme’s decision making processes for funding health and social care research can be found here.Further information on NIHR’s investment in public health research can be found as follows: NIHR School for Public Health here. NIHR Public Health Policy Research Unit here. NIHR Health Protection Research Units here. NIHR Public Health Research Programme Health Determinants Research Collaborations (HDRC) here. NIHR Public Health Research Programme Public Health Intervention Responsive Studies Teams (PHIRST) here.
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About Data.gov.au is the central source of Australian open government data. Anyone can access the public data published by federal, state and local government agencies. Data.gov.au are not responsible for creating, maintaining and updating these published datasets. Agencies are the custodians of the data they collect, and they make decisions about how it can be shared safely. They are often guided by legislation and policy requirements that can define what and how data can be shared. This data is a national resource that holds considerable value for growing the economy, improving service delivery and transforming policy outcomes. In addition to government data, you can also find publicly-funded research data and datasets from private institutions that are in the public interest. The federal government's Data and Digital Government Strategy requires all government agencies to make non-sensitive data open by default.
Maps of sediment fractions for the US Gulf of Mexico (GOM) and the US South Atlantic (SA) are provided as csv files. The spatial resolution of each output file is 1km and uses compositional kriging with input from the dbSEABED and usSEABED databases which compiles public seafloor datasets. Output CSV files include the fraction of sand, mud, and gravel as well as standard deviations of each.
In 2024, the survey underscores the continued dominance of data warehouses within cloud storage solutions. With 67 percent of respondents utilizing them, it is evident that businesses value the extensive analytical capabilities and structured data organization that data warehouses provide. This trend signals a persistent need for centralized repositories for data storage and analytics to support strategic decision-making. DBaaS relational databases gain traction The survey reveals a rising preference for database-as-a-service (DBaaS) relational databases. This shift suggests that organizations are increasingly seeking the scalability, ease of maintenance, and reduced administrative overhead that DBaaS solutions provide. People are using DBaaS more because they want to make databases easier and spend more time on important things. Oracle leads this segment among the database management systems providers. PaaS adoption accelerates A key finding from the survey is the marked increase in the adoption of cloud providers' platform-as-a-service (PaaS) offerings. This trend speaks volumes about a broader transformation; companies are decisively moving towards cloud-based platforms for their data needs. PaaS provides convenient building blocks for application development and deployment, accelerating innovation and time-to-market.
This CBIS-DDSM (Curated Breast Imaging Subset of DDSM) is an updated and standardized version of the Digital Database for Screening Mammography (DDSM) . The DDSM is a database of 2,620 scanned film mammography studies. It contains normal, benign, and malignant cases with verified pathology information. The scale of the database along with ground truth validation makes the DDSM a useful tool in the development and testing of decision support systems. The CBIS-DDSM collection includes a subset of the DDSM data selected and curated by a trained mammographer. The images have been decompressed and converted to DICOM format. Updated ROI segmentation and bounding boxes, and pathologic diagnosis for training data are also included. A manuscript describing how to use this dataset in detail is available at https://www.nature.com/articles/sdata2017177.
Published research results from work in developing decision support systems in mammography are difficult to replicate due to the lack of a standard evaluation data set; most computer-aided diagnosis (CADx) and detection (CADe) algorithms for breast cancer in mammography are evaluated on private data sets or on unspecified subsets of public databases. Few well-curated public datasets have been provided for the mammography community. These include the DDSM, the Mammographic Imaging Analysis Society (MIAS) database, and the Image Retrieval in Medical Applications (IRMA) project. Although these public data sets are useful, they are limited in terms of data set size and accessibility.
For example, most researchers using the DDSM do not leverage all its images for a variety of historical reasons. When the database was released in 1997, computational resources to process hundreds or thousands of images were not widely available. Additionally, the DDSM images are saved in non-standard compression files that require the use of decompression code that has not been updated or maintained for modern computers. Finally, the ROI annotations for the abnormalities in the DDSM were provided to indicate a general position of lesions, but not a precise segmentation for them. Therefore, many researchers must implement segmentation algorithms for accurate feature extraction. This causes an inability to directly compare the performance of methods or to replicate prior results. The CBIS-DDSM collection addresses that challenge by publicly releasing an curated and standardized version of the DDSM for evaluation of future CADx and CADe systems (sometimes referred to generally as CAD) research in mammography.
Please note that the image data for this collection is structured such that each participant has multiple patient IDs. For example, participant 00038 has 10 separate patient IDs which provide information about the scans within the IDs (e.g. Calc-Test_P_00038_LEFT_CC, Calc-Test_P_00038_RIGHT_CC_1). This makes it appear as though there are 6,671 patients according to the DICOM metadata, but there are only 1,566 actual participants in the cohort.
U.S. Government Workshttps://www.usa.gov/government-works
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This file contains governmental receipts for 1962 through the current budget year, as well as four years of projections. It can be used to reproduce many of the totals published in the Budget and examine unpublished details below the levels of aggregation published in the Budget.
LexisNexis provides access to electronic legal and non-legal research databases to the Agency's attorneys, administrative law judges, law clerks, investigators, and certain non-legal staff (e.g. staff in the Office of Public Affairs). The agency requires access to the following types of electronic databases: Legal databases, Non-legal databases, Public Records databases, and Financial databases.
In 2023, 0.27 percent of surveyed internet users in Luxembourg used the internet to access public databases and registers, up from 0.23 percent in 2022.