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Found 18 result(s)

Grand Challenge Data Collection

Carnegie Mellon University Multi-Modal Activity Database

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The CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.

Alternative Fuels Data Center

AFDC

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The Alternative Fuels Data Center (AFDC) is a comprehensive clearinghouse of information about advanced transportation technologies. The AFDC offers transportation decision makers unbiased information, data, and tools related to the deployment of alternative fuels and advanced vehicles. The AFDC launched in 1991 in response to the Alternative Motor Fuels Act of 1988 and the Clean Air Act Amendments of 1990. It originally served as a repository for alternative fuel performance data. The AFDC has since evolved to offer a broad array of information resources that support efforts to reduce petroleum use in transportation. The AFDC serves Clean Cities stakeholders, fleets regulated by the Energy Policy Act, businesses, policymakers, government agencies, and the general public.

GEON

GEONGRID

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-----<<<<< The repository is no longer available. This record is out-dated. >>>>>----- GEON is an open collaborative project that is developing cyberinfrastructure for integration of 3 and 4 dimensional earth science data. GEON will develop services for data integration and model integration, and associated model execution and visualization. Mid-Atlantic test bed will focus on tectonothermal, paleogeographic, and biotic history from the late-Proterozoicto mid-Paleozoic. Rockies test bed will focus on integration of data with dynamic models, to better understand deformation history. GEON will develop the most comprehensive regional datasets in test bed areas.

CAIDA Data

The Cooperative Association for Internet Data Analysis

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The Cooperative Association for Internet Data Analysis (CAIDA) is a collaborative undertaking among organizations in the commercial, government, and research sectors aimed at promoting greater cooperation in the engineering and maintenance of a robust, scalable global Internet infrastructure.It is an independent analysis and research group with particular focus on: Collection, curation, analysis, visualization, dissemination of sets of the best available Internet data, providing macroscopic insight into the behavior of Internet infrastructure worldwide, improving the integrity of the field of Internet science, improving the integrity of operational Internet measurement and management, informing science, technology, and communications public policies.

Archives of programs and data for physics

Archives for physics

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>>>!!!<<< 2018-01-18: no data nor programs can be found >>>!!!<<< These archives contain public domain programs for calculations in physics and other programs that we suppose about will help during work with computer. Physical constants and experimental or theoretical data as cross sections, rate constants, swarm parameters, etc., that are necessary for physical calculations are stored here, too. Programs are mainly dedicated to computers compatible with PC IBM. If programs do not use graphic units it is possible to use them on other computers, too. It is necessary to reprogram the graphic parts of programs in the other cases.

Spec Patterns

Specification Patterns

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Specification Patterns is an online repository for information about property specification for finite-state verification. The intent of this repository is to collect patterns that occur commonly in the specification of concurrent and reactive systems.

Cornell Activity Datasets: CAD-60 & CAD-120

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<<<!!!<<< The repository is no longer available. >>>!!!>>>

Haldimand County Open Data

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This is Haldimand County's public platform for exploring and downloading open data, discovering and building apps, and engaging to solve important local issues. You can analyze and combine Open Datasets using maps, as well as develop new web and mobile applications.

Prognostics Center of Excellence Data Set Repository

PCoE Datasets

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NASA's Prognostics Center of Excellence hosts the Prognostics Data Repository to provide data used in the development of prognostic algorithms, and time series of nominal to failed states. Data are donated from universities, agencies, or companies on an ongoing process.

Academic Torrents

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Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.

CEPDB

The Harvard Clean Energy Project Database

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-----<<<<< The repository is no longer available. This record is out-dated. The Matter lab provides the archived database version of 2012 and 2013 at https://www.matter.toronto.edu/basic-content-page/data-download. Data linked from the World Community Grid - The Clean Energy Project see at https://www.worldcommunitygrid.org/research/cep1/overview.do and on fighshare https://figshare.com/articles/dataset/moldata_csv/9640427 >>>>>----- The Clean Energy Project Database (CEPDB) is a massive reference database for organic semiconductors with a particular emphasis on photovoltaic applications. It was created to store and provide access to data from computational as well as experimental studies, on both known and virtual compounds. It is a free and open resource designed to support researchers in the field of organic electronics in their scientific pursuits. The CEPDB was established as part of the Harvard Clean Energy Project (CEP), a virtual high-throughput screening initiative to identify promising new candidates for the next generation of carbon-based solar cell materials.

Reality Commons

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Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.

SeedMe

Stream, Encode, Explore and Disseminate My Experiments

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<<<!!!<<< All user content from this site has been deleted. Visit SeedMeLab (https://seedmelab.org/) project as a new option for data hosting. >>>!!!>>> SeedMe is a result of a decade of onerous experience in preparing and sharing visualization results from supercomputing simulations with many researchers at different geographic locations using different operating systems. It’s been a labor–intensive process, unsupported by useful tools and procedures for sharing information. SeedMe provides a secure and easy-to-use functionality for efficiently and conveniently sharing results that aims to create transformative impact across many scientific domains.

Ocean Networks Canada

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Ocean Networks Canada maintains several observatories installed in three different regions in the world's oceans. All three observatories are cabled systems that can provide power and high bandwidth communiction paths to sensors in the ocean. The infrastructure supports near real-time observations from multiple instruments and locations distributed across the Arctic, NEPTUNE and VENUS observatory networks. These observatories collect data on physical, chemical, biological, and geological aspects of the ocean over long time periods, supporting research on complex Earth processes in ways not previously possible.

Informatics Research Data Repository

IDR

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The Informatics Research Data Repository is a Japanese data repository that collects data on disciplines within informatics. Such sub-categories are things like consumerism and information diffusion. The primary data within these data sets is from experiments run by IDR on how one group is linked to another.

Registry of Open Data on AWS

Registry of Open Data on Amazon Web Services

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The Registry of Open Data on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge to their users. 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.

VENUS in the Salish Sea

VENUS

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>>>!!!<<<VENUS coastal network, is now part of the Ocean Networks Canada Observatory>>>!!!<<< VENUS is a cabled undersea laboratory for ocean researchers and explorers. VENUS delivers real time information from seafloor instruments via fibre optic cables to the University of Victoria, BC. You can see ocean data live, recent and archived as well as learn more about on-going research

CKAN @ IoT Lab

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IoT Lab is a research platform exploring the potential of crowdsourcing and Internet of Things for multidisciplinary research with more end-user interactions. IoT Lab is a European Research project which aims at researching the potential of crowdsourcing to extend IoT testbed infrastructure for multidisciplinary experiments with more end-user interactions. It addresses topics such as: - Crowdsourcing mechanisms and tools; - “Crowdsourcing-driven research”; - Virtualization of crowdsourcing and testbeds; - Ubiquitous Interconnection and Cloudification of testbeds; - Testbed as a Service platform; - Multidisciplinary experiments; - End-user and societal value creation; - Privacy and personal data protection.