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Found 7 result(s)
eCrystals - Southampton is the archive for Crystal Structures generated by the Southampton Chemical Crystallography Group and the EPSRC UK National Crystallography Service.
>>>!!!<<< As stated 2017-08-28 NEEShub is no longer available. >>>!!!<<< >>>!!!<<< NEES.org is no longer available. The NEES published projects from the Project Warehouse can be found in the DesignSafe Data Depot https://www.designsafe-ci.org/data/browser/public/nees.public/. The NEES Databases https://datacenterhub.org/resources/395 are being transitioned to DataHub https://datacenterhub.org/ . Please visit DesignSafe https://www.designsafe-ci.org/ for all other inquiries. >>>!!!<<< NEES network features 14 geographically-distributed, shared-use laboratories that support several types of experimental work: geotechnical centrifuge research, shake table tests, large-scale structural testing, tsunami wave basin experiments, and field site research
This project is an open invitation to anyone and everyone to participate in a decentralized effort to explore the opportunities of open science in neuroimaging. We aim to document how much (scientific) value can be generated from a data release — from the publication of scientific findings derived from this dataset, algorithms and methods evaluated on this dataset, and/or extensions of this dataset by acquisition and incorporation of new data. The project involves the processing of acoustic stimuli. In this study, the scientists have demonstrated an audiodescription of classic "Forrest Gump" to subjects, while researchers using functional magnetic resonance imaging (fMRI) have captured the brain activity of test candidates in the processing of language, music, emotions, memories and pictorial representations.In collaboration with various labs in Magdeburg we acquired and published what is probably the most comprehensive sample of brain activation patterns of natural language processing. Volunteers listened to a two-hour audio movie version of the Hollywood feature film "Forrest Gump" in a 7T MRI scanner. High-resolution brain activation patterns and physiological measurements were recorded continuously. These data have been placed into the public domain, and are freely available to the scientific community and the general public.
Edinburgh DataShare is an online digital repository of multi-disciplinary research datasets produced at the University of Edinburgh, hosted by the Data Library in Information Services. Edinburgh University 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.
The Henry A. Murray Research Archive is Harvard's endowed, permanent repository for quantitative and qualitative research data at the Institute for Quantitative Social Science, and provides physical storage for the entire IQSS Dataverse Network. Our collection comprises over 100 terabytes of data, audio, and video. We preserve in perpetuity all types of data of interest to the research community, including numerical, video, audio, interview notes, and other data. We accept data deposits through this web site, which is powered by our Dataverse Network software
The EELS database is a public interactive consultable web repository of outer-shell and inner-shell excitation spectra from Electron Energy Loss Spectroscopy and X-Ray experiments, which forms a reference catalog of fine structures for materials. Each spectrum is available with a full set of recording parameters providing a complete overview of the working conditions. The database must also be seen as a research tool for EEL spectroscopists, theoreticians, students, or private firms and a central “location” for the growing EELS community.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis.