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Found 30 result(s)
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DUnAs is the institutional research data repository of the University of Aveiro. This repository is intended to share, archive, preserve, cite, access, and explore research data produced in the university scientific research activities.
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
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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.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
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.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
Junar provides a cloud-based open data platform that enables innovative organizations worldwide to quickly, easily and affordably make their data accessible to all. In just a few weeks, your initial datasets can be published, providing greater transparency, encouraging collaboration and citizen engagement, and freeing up precious staff resources.
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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.
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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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Lingnan Dataverse serves as an institutional research data repository for Lingnan University in Hong Kong. It provides a secure platform for the Lingnan research community to deposit, share, and publish their research datasets, and supports data reuse by the global research community.
DataON is Korea's National Research Data Platform. It provides integrated search of metadata for KISTI's research data and domestic and international research data and links to raw data. DataON allows users (researchers, policy makers, etc.) to perform the following tasks: Easily search for various types of research data in all scientific fields. By registering research results, research data can be posted and cited. Build a community among researchers and enable collaborative research. It provides a data analysis environment that allows one-stop analysis of discovered research data.
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Research Data Australia is the data discovery service of the Australian Research Data Commons (ARDC). The ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program. Research Data Australia helps you find, access, and reuse data for research from over one hundred Australian research organisations, government agencies, and cultural institutions. We do not store the data itself here but provide descriptions of, and links to, the data from our data publishing partners.
The online digital research data repository of multi-disciplinary research datasets produced at the University of Nottingham, hosted by Information Services and managed and curated by Libraries, Research & Learning Resources. University of Nottingham 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.
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.
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TUdatalib is the institutional repository of the TU Darmstadt for research data. It enables the structured storage of research data and descriptive metadata, long-term archiving (at least 10 years) and, if desired, the publication of data including DOI assignment. In addition there is a fine granular rights and role management.
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ResearchGate is a network where 15+ million scientists and researchers worldwide connect to share their work. Researchers can upload data of any type and receive DOIs, detailed statistics and real-time feedback. In Data discovery Section of ResearchGate you can explore the added datasets.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.
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DBT is the institutional repository of the FSU Jena, the TU Ilmenau and the University of Erfurt as well as members of the other Thuringian universities and colleges can publish scientific documents in the DBT. In individual cases, land users (via the ThULB Jena) can also archive documents in the DBT.