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Found 252 result(s)
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Jülich DATA is a registry service to index all research data created at or in the context of Forschungszentrum Jülich. As an institutionial repository, it may also be used for data and software publications.
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DaRUS, the data repository of the University of Stuttgart, offers a secure location for research data and codes, be it for the administration of own data, for exchange within a research group, for sharing with selected partners or for publishing.
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Built on the Islandora digital repository framework, the UPEI hosted Published and Archived Data (data.upei.ca) service provides researchers with a place to securely publish or archive their research datasets.
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Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. Kadi4Mat is the Karlsruhe Data Infrastructure for Materials Science, an open source software for managing research data. It is being developed as part of several research projects at the Institute for Applied Materials - Microstructure Modelling and Simulation (IAM-MMS) of the Karlsruhe Institute of Technology (KIT). The goal of this project is to combine the ability to manage and exchange data, the repository , with the possibility to analyze, visualize and transform said data, the electronic lab notebook (ELN). Kadi4Mat supports a close cooperation between experimenters, theorists and simulators, especially in materials science, to enable the acquisition of new knowledge and the development of novel materials. This is made possible by employing a modular and generic architecture, which allows to cover the specific needs of different scientists, each utilizing unique workflows. At the same time, this opens up the possibility of covering other research disciplines as well.
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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.
This classic collection of test cases for validation of turbulence models started as an EU / ERCOFTAC project led by Pr. W. Rodi in 1995. It is maintained by Dr. T. Craft at Manchester since 1999. Initialy limited to experimental data, computational results, and results and conclusions drawn from the ERCOFTAC Workshops on Refined Turbulence Modelling (SIG15). At the moment, each case should contain at least a brief description, some data to download, and references to published work. Some cases contain significantly more information than this.
FLOSSmole is a collaborative collection of free, libre, and open source software (FLOSS) data. FLOSSmole contains nearly 1 TB of data covering the period 2004 until now, about more than 500,000 different open source projects.
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.
Portal to Los Alamos Opacity Codes is your gateway to the set of opacity codes developed at the Los Alamos National Laboratory. The TOPS code has been developed to calculate multigroup opacities that can be written in a variety of formats for use in radiation transport codes. Arbitrary mixture of any elements for which OPLIB data exist is supported. Opacities of special mixtures that are important in astrophysical applications are also available as a separate option (Astrophysical opacities).
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.
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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.
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 repository KITopen is a key infrastructure service at KIT. Immediately KITopen not only allows the publication and archiving of publications, but also on research data from all disciplines and data types. The focus is on research data from publication projects that are specifically prepared for re-use.
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Trent University Dataverse is a research data repository for our faculty, students and staff. Files are held in a secure environment on Canadian servers. The platform makes it possible for researchers to deposit data, create appropriate metadata, and version documents as they work. Researchers can choose to make content available publicly, to specific individuals, or to keep it locked.
arthistoricum.net@heiDATA is the research data repository of arthistoricum.net (Specialized Information Service Art - Photography - Design). It provides art historians with the opportunity to permanently publish and archive research data in the field of art history in connection with an open access online publication (e.g. article, ejournal, ebook) hosted by Heidelberg University Library. All research data e.g. images, videos, audio files, tables, graphics etc. receive a DOI (Digital Object Identifier). The data publications can be cited, viewed and permanently linked to as distinct academic output.
The figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
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ISIDORE is a international search engine and a discovery platform for open science allowing the access to digital materials from social sciences and humanities (SSH). Open to all and especially to teachers, researchers, PhD students, and students, it relies on the principles of Web of data and provides access to data in free access (open access). By its vocation, ISIDORE will foster access to open access data produced by research and higher education institutions, laboratories and research teams: digital publication, documentary databases, digitized collections of research libraries, research notebooks and scientific event announcements. ISIDORE collects, enriches and highlights digital data and documents from the Humanities and Social Sciences while providing unified access to them. More information see: https://isidore.science/about
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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.