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Found 294 result(s)
!!!! <<<< The Community Data Portal (CDP) has been retired after nearly 15 years of service and is no longer available. Data can now be found here: DASH Search: https://data.ucar.edu/ . Please contact us with questions or concerns: datahelp@ucar.edu >>>> !!!! The Community Data Portal (CDP) is a collection of earth science datasets from NCAR, UCAR, UOP, and participating organizations.
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Three parts of a database provide published and unpublished chemical analysis results of archaeological ceramics. These are the results of forty years of applying WD-XRF and other mineralogical and physical laboratory methods to the analysis of sherds from excavations and museums. Drawing on some 30,000 analyses from research projects in Europe, Turkey, the near East, and Sudan, the part published here covers the results of three long-term projects: Early pottery in Thessaly, Greece (1,305 records), Firmalampen and other Roman lamps (1,666 records), and Roman and other pottery produced in Central Europe (4,043 records). This collated information provides an opportunity to work directly on published and unpublished data. These can be used as chemical reference groups for comparison for fine ware classification and in provenance studies.
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.
Yoda publishes research data on behalf of researchers that are affiliated with Utrecht University, its research institutes and consortia where it acts as a coordinating body. Data packages are not limited to a particular field of research or license. Yoda publishes data packages via Datacite. To find data publications use: https://public.yoda.uu.nl/ , or the Datacite search engine: https://search.datacite.org/repositories/delft.uu
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
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The Libraries offer members of the Université de Montréal community the opportunity to publish their research data in a Dataverse repository space
The NREL Data Catalog is where descriptive information (i.e., metadata) is maintained about public data resulting from federally funded research conducted by the National Renewable Energy Laboratory (NREL) researchers and analysts. Our Goal: Making Federally Funded Data Publicly Available NREL's mission is to develop clean energy and energy efficiency technologies and practices, advance related science and engineering, and provide knowledge and innovations to integrate energy systems at all scales. The NREL Data Catalog helps accomplish this by ensuring the data behind the science and engineering are well-documented and useful to the scientific community at large.
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Dataverse for faculty, researchers, and students at St. Francis Xavier University or affiliated institutions. Hosted by Borealis.
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GEOFON seeks to facilitate cooperation in seismological research and earthquake and tsunami hazard mitigation by providing rapid transnational access to seismological data and source parameters of large earthquakes, and keeping these data accessible in the long term. It pursues these aims by operating and maintaining a global network of permanent broadband stations in cooperation with local partners, facilitating real time access to data from this network and those of many partner networks and plate boundary observatories, providing a permanent and secure archive for seismological data. It also archives and makes accessible data from temporary experiments carried out by scientists at German universities and institutions, thereby fostering cooperation and encouraging the full exploitation of all acquired data and serving as the permanent archive for the Geophysical Instrument Pool at Potsdam (GIPP). It also organises the data exchange of real-time and archived data with partner institutions and international centres.
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
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The Concordia University Dataverse is a research data repository for Concordia faculty, students, and staff. Files are held in a secure environment on Canadian servers.
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The Academic Data Repository of the National University of Rosario (RDA- UNR) allows for sharing, storing, accessing, exploring, and citing research data managed by UNR professors, researchers and students so as to make these data visible and promote its use and reutilization, ensuring its long-term preservation. It is a self-publishing repository, i.e. users upload, organize, describe and publish their own data with the assistance of a team of curators, user guides and training sessions.
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.
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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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The MacEwan University Data Repository provides a place to store, share, and explore data and supports the teaching and scholarly activity of MacEwan University.
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The University of Northern British Columbia Dataverse is a research data repository for research data from UNBC researchers. Files are held in a secure environment on Canadian servers. The platform makes it possible for researchers to deposit data, create appropriate metadata, and version documents as they work. Researchers can choose to make content available publicly, to specific individuals, or to keep it locked.
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KU Leuven RDR (pronounced "RaDaR") is KU Leuven's Research Data Repository, built on Dataverse.org - open source repository software built by Harvard University. RDR gives KU Leuven researchers a one-stop platform to upload, describe, and share their research data, conveniently and with support from university staff.
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On this server you'll find 127 items of primary data of the University of Munich. Scientists / students of all faculties of LMU and of institutions that cooperate with the LMU are invited to deposit their research data on this platform.
Research data from University of Pretoria. This data repository facilitates data publishing, sharing and collaboration of academic research, allowing UP to manage and in some cases showcase its data to the wider research community. Previously UPSpace (https://repository.up.ac.za/) was used for both datasets and research outputs. Now UP Research Data Repository is dedicated for datasets.
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.