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Found 13 result(s)
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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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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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.
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.
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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RADAR4Culture is a low-threshold and easy-to use service for sustainable publication and preservation of cultural heritage research data. It offers free publication for any data type and format according to the FAIR principles, independent of the researcher´s institutional affiliation. Through persistent identifiers (DOI) and a guaranteed retention period of at least 25 years, the research data remain available, citable and findable long-term. Currently, the offer is aimed exclusively at researchers at publicly funded research institutions and (art) universities as well as non-commercial academies, galleries, libraries, archives and museums in Germany. No contract is required and no data publication fees are charged. The researchers are responsible for the upload, organisation, annotation and curation of research data as well as the peer-review process (as an optional step) and finally their publication.
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
The Sheffield Hallam University Research Data Repository (SHURDA) is an institutional catalogue of digital and non-digital datasets that are produced by researchers at SHU and preserved at the University or elsewhere.
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ITESO's Institutional Repository (ReI) is a digital repository that integrates the university's academic production, which manages, preserves and makes available in open access mode the works of researchers, professors and students of this university.
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Trove helps you find and use resources relating to Australia. It’s more than a search engine. Trove brings together content from libraries, museums, archives and other research organisations and gives you tools to explore and build.