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Found 44 result(s)
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MDR is a data repository to collect and store papers, presentation materials, and related materials data to accumulate and release them in a form suitable for the promotion of materials research and materials informatics. Users can search the documents and the data from information (metadata) such as sample, instrument, method, and from the full text of the deposited data, to browse and download them freely. User registration is not required and there is no charge for use.
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Coquitlam’s Open Data Portal is available to everyone without restrictions with the goal of empowering citizens, helping small businesses, supporting the development community and enhancing service delivery. Search for data or explore popular data categories to preview, analyze and download datasets. Using the available APIs, you can interact with data directly through your own maps, tables and charts. You can also download city-wide data packages, LiDAR, aerial photographs, terrain and 3D digital elevation models.
The Comprehensive Epidemiologic Data Resource (CEDR) is the U.S. Department of Energy (DOE) electronic database comprised of health studies of DOE contract workers and environmental studies of areas surrounding DOE facilities. DOE recognizes the benefits of data sharing and supports the public's right to know about worker and community health risks. CEDR provides independent researchers and educators with access to de-identified data collected since the Department's early production years. Current CEDR holdings include more than 76 studies of over 1 million workers at 31 DOE sites. Access to these data is at no cost to the user.
The RIT DML captures, distributes and preserves RIT's digital products. Here you can find articles, working papers, preprints, technical reports, conference papers and data sets in various digital formats.
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With Open Science OVGU the Otto-von-Guericke University provides its scientists with a research data repository. Measurement data, laboratory values, survey data, methodical test procedures, etc. can be archived in Open Science OVGU and made available to the scientific community via Open Access.
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ScholarBank@NUS is the university's Institutional Repository (IR). Its goals are to collect, preserve and showcase the research output including research data of NUS researchers and departments.
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The UWA Profiles and Research Repository contains research publications, research datasets, theses, equipment, grants and activities created by researchers and postgraduates affiliated with the University of Western Australia (UWA). It is managed by the University Library and provides access to research datasets held at UWA. The information about each dataset has been provided by UWA research groups. Dataset metadata is harvested into Research Data Australia (RDA) https://researchdata.edu.au/.
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LeoPARD is the institutional repository of the Technical University of Braunschweig and is operated by the University Library. It is used for the publication of research results and documentation by scientists of the TU Braunschweig.
CiteSeerx is an evolving scientific literature digital library and search engine that focuses primarily on the literature in computer and information science. CiteSeerx aims to improve the dissemination of scientific literature and to provide improvements in functionality, usability, availability, cost, comprehensiveness, efficiency, and timeliness in the access of scientific and scholarly knowledge. Rather than creating just another digital library, CiteSeerx attempts to provide resources such as algorithms, data, metadata, services, techniques, and software that can be used to promote other digital libraries. CiteSeerx has developed new methods and algorithms to index PostScript and PDF research articles on the Web.
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National Data Repository (NDR) is a reliable and integrated data repository of Exploration and Production (E&P) data of Indian sedimentary basins. It offers a unique platform to all concerns of E&P with provisions for seamless access to reliable geo-scientific data for India. Streamlining all associated procedures, policies and workflows pertaining to data submission, data management, data retrieval for all concerned pertaining to government agencies, academia and research communities with restrictions. NDR is owned by the Government of India, hosted at Directorate General of Hydrocarbons (DGH), Ministry of Petroleum and Natural Gas (MoPNG). Objectively it operates with geological data, petrophysical data, natural gas, seismic data, well & log data, spatial data, Reservoir data, Gravity & Magnetic data. NDR maintains and preserve hydrocarbon exploration & production data in a standard and reusable manner, but can't made available to entitled users freely. One cannot get access independently.
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The Federated Research Data Repository (FRDR) is a bilingual publishing platform for sharing and preserving Canadian research data. It is a curated, general-purpose repository, custom built for large datasets.
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The Research Data Repository of the University of Mannheim invites all researchers and faculty of the University of Mannheim to archive their research data here in order to make it accessible through the Internet. All archived data sets receive DOIs (Digital Object Identifier) to make them accessible and citable. Using this repository is free of charge.
The SURF Data Repository is a user-friendly web-based data publication platform that allows researchers to store, annotate and publish research datasets of any size to ensure long-term preservation and availability of their data. The service allows any dataset to be stored, independent of volume, number of files and structure. A published dataset is enriched with complex metadata, unique identifiers are added and the data is preserved for an agreed-upon period of time. The service is domain-agnostic and supports multiple communities with different policy and metadata requirements.
DataStorre is an online digital repository of multi-disciplinary research datasets produced at the University of Stirling. University of Stirling researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.
Here you can find out more about Lancaster’s world-class research activities, view details of publications, outputs and awards and make contact with our researchers.
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.
Content type(s)
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.
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.
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The BAW is a research institute for the Federal Ministry of Transport and acts as an advisor to the federal government for issues of waterway engineering. In this role the BAW consumes and produces large volumes of data and information. As part of the implementation of Open Data legislation and in support of Open Data and Open Access principles, the BAW provides access to scientific data together with their metadata. The BAW-Datenrepository was developed as a point of access for hydraulic engineering experts, contractors and customers of the BAW as well as the general public. It is a source for quality-assured information and provides standardised, long-term access to waterway engineering data. The BAW-Datenrepository supports the targeted search for information and data and gives direct access to them. By publishing its scientific data, the BAW promotes transparency in public discourse as well as accountability of public administration enabling the data to create value beyond the BAW.
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HHU ResearchData enables researchers of Heinrich Heine University Düsseldorf to make their research data available to the scientific community.
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/
Mountain Scholar is an open access repository service that collects, preserves, and provides access to digitized library collections and other scholarly and creative works from several academic entities within the state of Colorado. Colorado State University research data from the fall of 2022 and forward is available in Dryad; CSU legacy research data prior to fall 2022 is in Mountain Scholar.
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RIUMA is the Institutional Repository of the University of Malaga whose objective is to facilitate and improve the visibility of the scientific and academic production of the University of Malaga, allowing open access to its contents and guaranteeing the preservation and conservation of this production. The collection includes articles, research data, scientific papers, teaching material, digitized old collection and other documents in different digital formats.