The Registry of Open Data on AWS contains publicly available datasets that are available for access from AWS resources. Note that datasets in this registry are available via AWS resources, but they are not provided by AWS; these datasets are owned and maintained by a variety of government organizations, researchers, businesses, and individuals. This dataset contains derived forms of the data in https://github.com/awslabs/open-data-registry that have been transformed for ease of use with machine interfaces. Currently, only the ndjson form of the registry is populated here.

The Data Exchange Platform Services Marketsize was valued at USD 1.3 billion in 2023 and is projected to reach USD 7.5 billion by 2032, exhibiting a CAGR of 19.15 % during the forecast period. The market of data exchange platform services includes services that are required to provide strict capability of exchanging data between various organizations, systems, and/or applications. They include an integration hub used for accepting, transforming, and routing data in real time according to its source and format. Besides, there are several use cases associated with Data Exchange platforms, including Inter-Organization Data Sharing, Cloud-Application Integration, and From Cloud to On-Prem, Off-Prem Applications Data Transfer. These include financing, medical, sales and industrial production, statistic and analytical, provision of goods and services, as well as meeting clients’ requirements. These trends include the need for cloud as a scale-out solution, data management, and security issues, and some disciplines have different need-states for platforms. To utilize data as a competitive tool, the market of the data exchange platform services is gradually developing at this moment and a new market is being formed. Recent developments include: November 2019: Amazon Web Services (AWS) partnered with Deloitte to help customers securely find, subscribe to, and use third-party data in the cloud using AWS Data Exchange, a new service that can help address unique healthcare issues. March 2020: Google Cloud Platform (GCP) launched Anthos, a new platform that enables businesses to run their applications across multiple clouds and on-premises environments. Anthos includes a data exchange feature that allows businesses to share data between their applications, regardless of where they are deployed.. Key drivers for this market are: Increasing Adoption of Cloud-based Managed Services to Drive Market Growth. Potential restraints include: Misuse of Virtual Currency and Security Attacks Confines the Adoption of Cryptocurrencies. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

A multidisciplinary repository of public data sets such as the Human Genome and US Census data that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. If you have a public domain or non-proprietary data set that you think is useful and interesting to the AWS community, please submit a request and the AWS team will review your submission and get back to you. Typically the data sets in the repository are between 1 GB to 1 TB in size (based on the Amazon EBS volume limit), but they can work with you to host larger data sets as well. You must have the right to make the data freely available.

The Data Marketplace Platform market is experiencing robust growth, driven by the increasing demand for data-driven decision-making across various industries. The market's expansion is fueled by several key factors, including the proliferation of big data, the rising adoption of cloud-based solutions, and the growing need for data monetization strategies. Businesses are increasingly seeking efficient and secure ways to access, share, and analyze diverse datasets, leading to a surge in demand for platforms that facilitate these processes. Furthermore, the development of advanced analytics and AI/ML capabilities further enhances the value proposition of these platforms, attracting both data buyers and sellers. Competition is fierce, with established tech giants like Microsoft, Oracle, and AWS alongside specialized data marketplace providers vying for market share. The market is segmented by data type (structured, unstructured), deployment model (cloud, on-premise), and industry vertical (finance, healthcare, retail, etc.), each exhibiting unique growth trajectories. A conservative estimate suggests a market size of approximately $5 billion in 2025, growing at a CAGR of 25% over the forecast period (2025-2033). This growth is expected to be driven by increasing cloud adoption, improved data security measures, and the emergence of innovative business models within the data marketplace ecosystem. The competitive landscape is characterized by both large established players and nimble startups. Successful players are those that offer comprehensive solutions encompassing data discovery, secure access control, data governance, and advanced analytics capabilities. Geographic expansion and strategic partnerships are crucial for achieving sustainable growth. While the market enjoys significant growth potential, challenges remain including data privacy concerns, data quality issues, and the need to establish trust and transparency within the marketplace ecosystem. Addressing these challenges effectively will be critical for the continued success and expansion of the Data Marketplace Platform market. The robust growth forecast suggests significant opportunities for both established players and new entrants to capitalize on this expanding market.

This dataset can be used to test Minimal Viable Product 2 from Research Data Exchange. This means that the data can only be analyzed in a closed and secure environment and that the output will be checked before it is shared with the data requester. The link to access the data can be found in the references. The data contains customer sentiments regarding Baby products purchased on Amazon.com, on the basis of their written reviews. The data is used for an assignment from the master track Behavioural Data Science, which be found on Kaggle, see reference.

Malawi Internet Usage: Device Vendor Market Share: Mobile: Amazon data was reported at 0.000 % in 01 May 2024. This stayed constant from the previous number of 0.000 % for 30 Apr 2024. Malawi Internet Usage: Device Vendor Market Share: Mobile: Amazon data is updated daily, averaging 0.000 % from Apr 2024 (Median) to 01 May 2024, with 9 observations. The data reached an all-time high of 0.080 % in 27 Apr 2024 and a record low of 0.000 % in 01 May 2024. Malawi Internet Usage: Device Vendor Market Share: Mobile: Amazon data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Malawi – Table MW.SC.IU: Internet Usage: Device Vendor Market Share.

Automated Weather Station and AWS-like networks are the primary source of surface-level meteorological data in remote polar regions. These networks have developed organically and independently, and deliver data to researchers in idiosyncratic ASCII formats that hinder automated processing and intercomparison among networks. Moreover, station tilt causes significant biases in polar AWS measurements of radiation and wind direction. Researchers, network operators, and data centers would benefit from AWS-like data in a common format, amenable to automated analysis, and adjusted for known biases. This project addresses these needs by developing a scientific software workflow called "Justified AWS" (JAWS) to ingest Level 2 (L2) data in the multiple formats now distributed, harmonize it into a common format, and deliver value-added Level 3 (L3) output suitable for distribution by the network operator, analysis by the researcher, and curation by the data center. Polar climate researchers currently face daunting problems including how to easily: 1. Automate analysis (subsetting, statistics, unit conversion) of AWS-like L2 ASCII data. 2. Combine or intercompare data and data quality from among unharmonized L2 datasets. 3. Adjust L2 data for biases such as AWS tilt angle and direction. JAWS addresses these common issues by harmonizing AWS L2 data into a common format, and applying accepted methods to quantify quality and estimate biases. Specifically, JAWS enables users and network operators to 1. Convert L2 data (usually ASCII tables) into a netCDF-based L3 format compliant with metadata conventions (Climate-Forecast and ACDD) that promote automated discovery and analysis. 2. Include value-added L3 features like the Retrospective, Iterative, Geometry-Based (RIGB) tilt angle and direction corrections, solar angles, and standardized quality flags. 3. Provide a scriptable API to extend the initial L2-to-L3 conversion to newer AWS-like networks and instruments. Polar AWS network experts and NSIDC DAAC personnel, each with decades of experience, will help guide and deliberate the L3 conventions implemented in Stages 2-3. The project will start on July 1, 2017 at entry Technology Readiness Level 3 and will exit on June 30, 2019 at TRL 6. JAWS is now a heterogeneous collection of scripts and methods developed and validated at UCI over the past 15 years. At exit, JAWS will comprise three modular stages written in or wrapped by Python, installable by Conda: Stage 1 ingests and translates L2 data into netCDF. Stage 2 annotates the netCDF with CF and ACDD metadata. Stage 3 derives value-added scientific and quality information. The labor-intensive tasks include turning our heterogeneous workflow into a robust, standards-compliant, extensible workflow with an API based on best practices of modern scientific information systems and services. Implementation of Stages 1-2 may be straightforward though tedious due to the menagerie of L2 formats, instruments, and assumptions. The RIGB component of Stage 3 requires ongoing assimilation of ancillary NASA data (CERES, AIRS) and use of automated data transfer protocols (DAP, THREDDS). The immediate target recipient elements are polar AWS network managers, users, and data distributors. L2 borehole data suffers from similar interoperability issues, as does non-polar AWS data. Hence our L3 format will be extensible to global AWS and permafrost networks. JAWS will increase in situ data accessibility and utility, and enable new derived products (both are AIST goals). The PI is a long-standing researcher, open source software developer, and educator who understands obstacles to harmonizing disparate datasets with NASA interoperability recommendations. Our team participates in relevant geoscience communities, including ESDS working groups, ESIP, AGU, and EarthCube.

A collection of downscaled climate change projections, derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Taylor et al. 2012] and across the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs) [Meinshausen et al. 2011]. The NASA Earth Exchange group maintains the NEX-DCP30 (CMIP5), NEX-GDDP (CMIP5), and LOCA (CMIP5).

The NASA Earth Exchange (NEX) Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Taylor et al. 2012] and across the two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs) [Meinshausen et al. 2011] developed for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The dataset is an ensemble of projections from 21 different models and two RCPs (RCP 4.5 and RCP 8.5), and provides daily estimates of maximum and minimum temperatures and precipitation using a daily Bias-Correction - Spatial Disaggregation (BCSD) method (Thrasher, et al., 2012). The data spans the entire globe with a 0.25 degree (~25-kilometer) spatial resolution for the periods from 1950 through 2005 (Historical) and from 2006 to 2100 (Climate Projections).

The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed through the Earth System Grid Federation. The purpose of this dataset is to provide a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions.

Norway Internet Usage: Device Vendor Market Share: Mobile: Amazon data was reported at 0.000 % in 22 Aug 2024. This stayed constant from the previous number of 0.000 % for 21 Aug 2024. Norway Internet Usage: Device Vendor Market Share: Mobile: Amazon data is updated daily, averaging 0.000 % from Aug 2024 (Median) to 22 Aug 2024, with 9 observations. The data reached an all-time high of 0.050 % in 18 Aug 2024 and a record low of 0.000 % in 22 Aug 2024. Norway Internet Usage: Device Vendor Market Share: Mobile: Amazon data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Norway – Table NO.SC.IU: Internet Usage: Device Vendor Market Share.

In the fourth quarter of 2024, the most popular vendor in the cloud infrastructure services market, Amazon Web Services (AWS), controlled ** percent of the entire market. Microsoft Azure takes second place with ** percent market share, followed by Google Cloud with ** percent market share. Together, these three cloud vendors account for ** percent of total spend in the fourth quarter of 2024. Organizations use cloud services from these vendors for machine learning, data analytics, cloud native development, application migration, and other services. AWS Services Amazon Web Services is used by many organizations because it offers a wide variety of services and products to its customers that improve business agility while being secure and reliable. One of AWS’s most used services is Amazon EC2, which lets customers create virtual machines for their strategic projects while spending less time on maintaining servers. Another important service is Amazon Simple Storage Service (S3), which offers a secure file storage service. In addition, Amazon also offers security, website infrastructure management, and identity and access management solutions. Cloud infrastructure services Vendors offering cloud services to a global customer base do so through different types of cloud computing, which include infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Further, there are different cloud computing deployment models available for customers, namely private cloud and public cloud, as well as community cloud and hybrid cloud. A cloud deployment model is defined based on the location where the deployment resides, and who has access to and control over the infrastructure.

The Real-time Data Transfer Service market is experiencing robust growth, driven by the increasing demand for immediate data access across diverse sectors. The market size in 2025 is estimated at $15 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033. This significant expansion is fueled by several key factors. The proliferation of IoT devices and the rise of big data analytics necessitate the swift and reliable transfer of large datasets. Furthermore, industries like healthcare, finance, and manufacturing are increasingly reliant on real-time data for critical decision-making, fueling the demand for high-performance, low-latency solutions. Cloud-based solutions are dominating the market, offering scalability and cost-effectiveness compared to on-premise solutions. However, concerns regarding data security and regulatory compliance pose significant challenges to market growth. The competitive landscape is characterized by both established technology giants and specialized providers, leading to continuous innovation and competitive pricing. Geographical expansion is also a significant driver, with North America currently holding the largest market share due to early adoption and technological advancement, followed by Europe and Asia-Pacific, which are expected to witness substantial growth in the coming years. The segmentation of the market by application reveals a diverse range of industries leveraging real-time data transfer services. Healthcare and Life Sciences represent a major segment, driven by the need for immediate access to patient data and the growing adoption of telehealth. Manufacturing utilizes real-time data for optimized production processes and predictive maintenance. Transportation and Logistics rely on instant data for efficient supply chain management and real-time tracking. The Energy and Utilities sector benefits from real-time data monitoring for grid optimization and enhanced operational efficiency. Finally, the Public Sector utilizes real-time data for improved citizen services and enhanced public safety. This varied application across industries signifies the widespread adoption and critical role of real-time data transfer services in the modern digital economy. The ongoing development of advanced technologies like 5G and edge computing is expected to further accelerate market expansion in the forecast period.

This data contains in-phase and quadrature waveforms of AWS-1 LTE uplink emissions collected at NASA Langley Research Center's Langley Research Antenna System. The collection campaign is part of the NASCTN effort on AWS-3 LTE impacts on Aeronautical Mobile Telemetry https://www.nist.gov/programs-projects/aws-3-lte-impacts-amt. The work is detailed in the NTIA Technical Report TR-21-553 In-Situ Captures of AWS-1 LTE for Aeronautical Mobile Telemetry System Evaluation available at https://www.its.bldrdoc.gov/publications/details.aspx?pub=3262 . Additional pertinent details on recording parameter settings are outlined in the format provided in NTIA Technical Memo TM-21-553 available at https://www.its.bldrdoc.gov/publications/details.aspx?pub=3261 .

The global data catalog market is experiencing steady growth, driven by the increasing volume and complexity of enterprise data. As organizations face the challenge of managing multiple data sources and ensuring data quality and governance, the adoption of data catalogs has become increasingly important. According to market research, the total value of the market in 2025 was approximately $2.61 billion, with a projected CAGR of 2.50% from 2025 to 2033. This growth is primarily attributed to the growing need for data-driven decision-making and the proliferation of big data and artificial intelligence (AI) technologies. Key industry trends indicate a growing emphasis on cloud-based data catalog solutions, as well as the integration of AI and machine learning (ML) capabilities. These technologies enhance the automation and efficiency of data cataloging processes, while providing advanced features such as data lineage tracking and data quality monitoring. Furthermore, the convergence of data catalog solutions with other enterprise applications, such as data governance and data analytics platforms, creates opportunities for comprehensive data management and improved data utilization. The competitive landscape is characterized by a mix of established vendors and emerging players, with companies such as Tamr Inc, Collibra NV, TIBCO Software Inc, and IBM Corporation holding significant market share. Ongoing innovations and strategic acquisitions are shaping the market dynamics, as vendors strive to differentiate their offerings and meet evolving customer requirements. The global data catalog market size was valued at USD 2.0 billion in 2022 and is expected to expand at a compound annual growth rate (CAGR) of 24.3% from 2023 to 2030, reaching USD 12.0 billion by 2030. Recent developments include: November 2022 - Amazon EMR customers can now use AWS Glue Data Catalog from their streaming and batch SQL workflows on Flink. The AWS Glue Data Catalog is an Apache Hive metastore-compatible catalog. With this release, Companies can directly run Flink SQL queries against the tables stored in the Data Catalog., September 2022 - Syniti, a global leader in enterprise data management, updated new data quality and catalog capabilities available in its industry-leading Syniti Knowledge Platform, building on the enhancements in data migration and data matching added earlier this year. The Syniti Knowledge Platform now includes data quality, catalog, matching, replication, migration, and governance, all available under one login in a single cloud solution. It provides users with a complete and unified data management platform enabling them to deliver faster and better business outcomes with data they can trust., August 2022 - Oracle Cloud Infrastructure collaborated with Anaconda, the world's most recognized data science platform provider. By permitting and integrating the latter company's repository throughout OCI Machine Learning and Artificial Intelligence services, the collaboration aimed to give safe, open-source Python and R tools and packages.. Key drivers for this market are: Growing adoption of Cloud Based Solutions, Solutions Segment is Expected to Hold a Larger Market Size. Potential restraints include: Lack of Standardization and Security Concerns. Notable trends are: Solutions Segment is Expected to Hold a Larger Market Size.

Global, aggregated physical air quality data from public data sources provided by government, research-grade and other sources. These awesome groups do the hard work of measuring these data and publicly sharing them, and our community makes them more universally-accessible to both humans and machines.

The Data Catalog Marketsize was valued at USD 878.8 USD million in 2023 and is projected to reach USD 2749.95 USD million by 2032, exhibiting a CAGR of 17.7 % during the forecast period. Data catalog is another concept that is used to refer to a unified list of all the data resources within an organization and their descriptions that are crucial in the course of data search. It can also sort data, effectively making it easier to find and use data sets that the user requires. based on their usage, data catalogs can be distinguished into business, technical, and operation catalogs; business use for business intelligence, technical for providing metadata for technical use, and operational use for tracking operational data. Some of the significant elements of data catalogs are data lineage, metadata management, search and discovery features, data governance, and collaboration. They are actively utilized in industries for increasing data quality, satisfying the requirements of compliance, and optimizing the analysis to support better decision-making and increase efficiency in business operations. Recent developments include: February 2024 – Collibra launched Collibra AI Governance, built on their Data Intelligence Platform, enabling organizations to deliver trusted AI effectively through the use of Collibra Data Catalog. It aided teams in collaborating for compliance, improved model performance, reduced risk, and led to faster production timelines., September 2023 – AWS Lake Formation launched a Hybrid Access Module for the AWS Glue Data Catalog, allowing users to selectively enable Lake Formation for tables and databases without interrupting existing users or workloads. This feature provided flexibility and an integral path for enabling Lake Formation, reducing the need for coordination among owners and consumers., July 2023 – Teradata acquired Stemma Technologies to enhance its analytics capabilities, particularly in data discovery and delivery. Stemma’s automated data catalog bolstered Teradata’s offerings, aiming to improve user experience and accelerate ML and AI analytics growth., June 2023 – Acryl Data secured USD 21 million in Series A funding led by 8VC to enhance its open-source data catalog platform. This investment enhanced their cloud offerings and expanded their vision towards a data control plane., May 2023 – data.world launched its new Data Catalog Platform, integrating generative AI bots to enhance data discovery. With over 2 million users, the platform aimed to make data discovery and knowledge unlocking accessible to users of all expertise levels., February 2023 – data.world, a data governance platform, launched the first AI Lab for the data catalog industry. This Artificial Intelligence (AI) Lab would be important in bringing partners and customers together to enhance data team productivity using AI technology., November 2022 – Amazon Web Services (AWS) launched DataZone, a new machine learning-based data management service to help enterprises catalog, share, govern, and discover their data quickly.. Key drivers for this market are: Exponential Growth of Data Volume and Data Analytics to Fuel Market Growth. Potential restraints include: High Initial Deployment Cost and Privacy Concerns to Hinder Market Growth. Notable trends are: Growing Adoption of AI and Automation Technologies to Amplify Market Growth.

This data package contains raw leaf gas exchange data used to support the publication "Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin," Phytochemistry, in-press. Data was collected from 162 individuals, distributed among 25 botanical families and 113 species, from four sites in the Amazon. The data was collected using a modified portable photosynthesis system for environmental control coupled to a thermal desorption tube for volatile isoprenoid collections. Collected TD tube samples were analysed in Manaus, Brazil, using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). The dataset includes both photosynthesis and isoprene/monoterpene emission rates from leaves under standard environmental conditions as well as controlled light response curves.For detailed methods and raw data, refer to the publication and related material cited in Dataset References. This dataset was originally published on the NGEE Tropics Archive and is being mirrored on ESS-DIVE for long-term archival

These datasets contain peer-to-peer trades from various recommendation platforms.

Metadata includes

• peer-to-peer trades

• have and want lists

• image data (tradesy)