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Found 14 result(s)
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
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Dataverse for faculty, researchers, and students at St. Francis Xavier University or affiliated institutions. Hosted by Borealis.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
The Illinois Data Bank is a public access data repository that collects, disseminates, and provides persistent and reliable access to the research data of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students can deposit their research data directly into the Illinois Data Bank and receive a DOI for citation purposes.
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The purpose of the Social Data Repository (RDS) is to make available in the Internet social data, consisting of data sets and accompanying technical or methodological documentation. The use of Repository is open for everyone. The repository is operated by the University of Warsaw (Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw). Individual collections in the Social Data Repository are subject to editorial review by University of Warsaw or collection administrators, under separate rules for a given collection. In particular, the supervising editor for the collection “Archive of Quantitative Social Data” is the Team of the Archive of Quantitative Social Data.
The UCD Digital Library is a platform for exploring cultural heritage, engaging with digital scholarship, and accessing research data. The UCD Digital Library allows you to search, browse and explore a growing collection of historical materials, photographs, art, interviews, letters, and other exciting content, that have been digitised and made freely available.
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RepOD is a general-purpose repository for open research data, offering all members of the academic community in Poland the possibility to deposit their work. It is intended for scientific data from all disciplines of knowledge and in all formats. The purpose of RepOD is to create a place where research data can be safely stored and openly shared with others.
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The data repository aims to store, preserve and make available research data generated by the academic community, in open access - as open as possible, as closed as necessary.
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The Research Data Repository of FID move is a digital long-term repository for open data from the field of transport and mobility research. All datasets are provided with an open licence and are assigned a persistent DataCite DOI (Digital Object Identifier). Both data search and archiving are free. The Specialised Information Service for Mobility and Transport Research (FID move) has been set up by the Saxon State and University Library Dresden (SLUB) and the German TIB – Leibniz Information Centre for Science and Technology as part of the DFG funding programme "Specialised Information Services".
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
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Macromolecular Xtallography Raw Data Repository (MX-RDR) is a domain-specific digital repository of crystallographic open research data. The use of Repository is open for everyone.