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Found 11 result(s)
nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.
OHSU Digital Commons is a repository for the scholarly and creative work of Oregon Health & Science University. Developed by the OHSU Library, Digital Commons provides the university community with a platform for publishing and accessing content produced by students, faculty, and staff. OHSU Digital Commons documents the history and growth of the university, as well as current progress in education, research, and health care.
>>>!!!<<< On June 1, 2020, the Academic Seismic Portal repositories at UTIG were merged into a single collection hosted at Lamont-Doherty Earth Observatory. Content here was removed July 1, 2020. Visit the Academic Seismic Portal @LDEO! https://www.marine-geo.org/collections/#!/collection/Seismic#summary (https://www.re3data.org/repository/r3d100010644) >>>!!!<<<
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Library Open Access Repository (LOAR) is an open data repository established in 2016 as a service for storing and providing access to Danish research data. The service has the following key goals: Make data accessible to review for publications. Enable researchers to meet requirements for Danish and European grants. Ensure data privacy and removal of data as appropriate. Enable reuse of data where appropriate Researchers who upload data are expected to share the data using Creative Commons licenses.
<<<!!!<<< 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.
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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.
A central source for NEI biomedical digital objects including data sets, software and analytical workflow, metadata, standards, publications and more.
MD-SOAR is a shared digital repository platform for eleven colleges and universities in Maryland. It is currently funded by the University System of Maryland and Affiliated Institutions (USMAI) Library Consortium (usmai.org) and other participating partner institutions. MD-SOAR is jointly governed by all participating libraries, who have agreed to share policies and practices that are necessary and appropriate for the shared platform. Within this broad framework, each library provides customized repository services and collections that meet local institutional needs. Please follow the links below to learn more about each library's repository services and collections.
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With the KIT Whole-Body Human Motion Database, we aim to provide a simple way of sharing high-quality motion capture recordings of human whole-body motion. In addition, with the Motion Annotation Tool (https://motion-annotation.humanoids.kit.edu/ ), we aim to collect a comprehensive set of whole-body motions along with natural language descriptions of these motions (https://motion-annotation.humanoids.kit.edu/dataset/).