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Found 23 result(s)
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
-----<<<<< 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.
Catena, the Digital Archive of Historic Gardens and Landscapes, is a collection of historic and contemporary images, including plans, engravings, and photographs, intended to support research and teaching in the fields of garden history and landscape studies. Created through the collaborative efforts of landscape historians and institutions, the initial offering of images is focused on the Villas as a Landscape Type.
Government of Yukon open data provides an easy way to find, access and reuse the government's public datasets. This service brings all of the government's data together in one searchable website. Our datasets are created and managed by different government departments. We cannot guarantee the quality or timeliness of all data. If you have any feedback you can get in touch with the department that produced the dataset. This is a pilot project. We are in the process of adding a quality framework to make it easier for you to access high quality, reliable data.
The Brown Digital Repository (BDR) is a place to gather, index, store, preserve, and make available digital assets produced via the scholarly, instructional, research, and administrative activities at Brown.
As one of the cornerstones of the U.S. Geological Survey's (USGS) National Geospatial Program, The National Map is a collaborative effort among the USGS and other Federal, State, and local partners to improve and deliver topographic information for the Nation. It has many uses ranging from recreation to scientific analysis to emergency response. The National Map is easily accessible for display on the Web, as products and services, and as downloadable data. The geographic information available from The National Map includes orthoimagery (aerial photographs), elevation, geographic names, hydrography, boundaries, transportation, structures, and land cover. Other types of geographic information can be added within the viewer or brought in with The National Map data into a Geographic Information System to create specific types of maps or map views.
IDEALS is an institutional repository that collects, disseminates, and provides persistent and reliable access to the research and scholarship of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students, and in some cases undergraduate students, can deposit their research and scholarship directly into IDEALS. Departments can use IDEALS to distribute their working papers, technical reports, or other research material. Contact us at https://www.ideals.illinois.edu/feedback for more information.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.
Digital Rocks is a data portal for fast storage and retrieval of images of varied porous micro-structures. It has the purpose of enhancing research resources for modeling/prediction of porous material properties in the fields of Petroleum, Civil and Environmental Engineering as well as Geology. This platform allows managing and preserving available images of porous materials and experiments performed on them, and any accompanying measurements (porosity, capillary pressure, permeability, electrical, NMR and elastic properties, etc.) required for both validation on modeling approaches and the upscaling and building of larger (hydro)geological models. Starting September 2021 we charge fees for publishing larger projects; projects < 2GB remain free: see user agreement https://www.digitalrocksportal.org/user-agreement/
RunMyCode is a novel cloud-based platform that enables scientists to openly share the code and data that underlie their research publications. The web service only requires a web browser as all calculations are done on a dedicated cloud computer. Once the results are ready, they are automatically displayed to the user.
<<<!!!<<< 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.
The UA Campus Repository is an institutional repository that facilitates access to the research, creative works, publications and teaching materials of the University by collecting, sharing and archiving content selected and deposited by faculty, researchers, staff and affiliated contributors.
cIRcle is an open access digital repository for published and unpublished material created by the UBC community and its partners. In BIRS there are thousands of mathematics videos, which are primary research data. Our repository is the largest source of mathematics data with more than 10TB of primary research by the best mathematicians in the world, coming from more than 600 institutions.
A Research Data Repository (RDR) for researchers in India. Any registered researchers of Indian Universities can manage their research data on eSHODHMANTHAN-RDR free of cost. This research data repository is configured to provide free of cost research data management services to existing and forthcoming researchers throughout their research life. eSHODHMANTHAN-RDR is powered by Dataverse project of Harvard University
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.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
ScholarSphere is an institutional repository managed by Penn State University Libraries. Anyone with a Penn State Access ID can deposit materials relating to the University’s teaching, learning, and research mission to ScholarSphere. All types of scholarly materials, including publications, instructional materials, creative works, and research data are accepted. ScholarSphere supports Penn State’s commitment to open access and open science. Researchers at Penn State can use ScholarSphere to satisfy open access and data availability requirements from funding agencies and publishers.
The Energy Data eXchange (EDX) is an online collection of capabilities and resources that advance research and customize energy-related needs. EDX is developed and maintained by NETL-RIC researchers and technical computing teams to support private collaboration for ongoing research efforts, and tech transfer of finalized DOE NETL research products. EDX supports NETL-affiliated research by: Coordinating historical and current data and information from a wide variety of sources to facilitate access to research that crosscuts multiple NETL projects/programs; Providing external access to technical products and data published by NETL-affiliated research teams; Collaborating with a variety of organizations and institutions in a secure environment through EDX’s ;Collaborative Workspaces