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Found 70 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.
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GBIF is an international organisation that is working to make the world's biodiversity data accessible everywhere in the world. GBIF and its many partners work to mobilize the data, and to improve search mechanisms, data and metadata standards, web services, and the other components of an Internet-based information infrastructure for biodiversity.
GBIF makes available data that are shared by hundreds of data publishers from around the world. These data are shared according to the GBIF Data Use Agreement, which includes the provision that users of any data accessed through or retrieved via the GBIF Portal will always give credit to the original data publishers.
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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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HepSim is a public repository with Monte Carlo simulations for particle-collision experiments. It contains predictions from leading-order (LO) parton shower models, next-to-leading order (NLO) and NLO with matched parton showers. It also includes Monte Carlo events after fast ("parametric") and full (Geant4) detector simulations and event reconstruction.
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SODHA is the federal Belgian data archive for social sciences and the digital humanities. SODHA is a new service of the State Archives of Belgium and acts as the Belgian service provider for the Consortium of European Social Science Data Archives (CESSDA).
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RAVE (RAdial Velocity Experiment) is a multi-fiber spectroscopic astronomical survey of stars in the Milky Way using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO). The RAVE collaboration consists of researchers from over 20 institutions around the world and is coordinated by the Leibniz-Institut für Astrophysik Potsdam. As a southern hemisphere survey covering 20,000 square degrees of the sky, RAVE's primary aim is to derive the radial velocity of stars from the observed spectra. Additional information is also derived such as effective temperature, surface gravity, metallicity, photometric parallax and elemental abundance data for the stars. The survey represents a giant leap forward in our understanding of our own Milky Way galaxy; with RAVE's vast stellar kinematic database the structure, formation and evolution of our Galaxy can be studied.
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Dataverse to host followup observations of galaxy clusters identified in South Pole Telescope SZ Surveys. This includes: 1) GMOS spectroscopy of low to moderate redshift galaxy clusters taken as a part of NOAO Large Survey Program 11A-0034 (PI: Christopher Stubbs).
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The Arctic Permafrost Geospatial Centre (APGC) is an Open Access Circum-Arctic Geospatial Data Portal that promotes, describes and visualizes geospatial permafrost data. A data catalogue and a WebGIS application allow to easily discover and view data and metadata. Data can be downloaded directly via link to the publishing data repository.
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Agri-environmental Research Data collection is part of the University of Guelph Research Data Repositories (University of Guelph Dataverse). The purpose of this collection is to provide access to, and long-term stewardship of, agricultural and environmental data created at or in cooperation with the University of Guelph.
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CERN, DESY, Fermilab and SLAC have built the next-generation High Energy Physics (HEP) information system, INSPIRE. It combines the successful SPIRES database content, curated at DESY, Fermilab and SLAC, with the Invenio digital library technology developed at CERN. INSPIRE is run by a collaboration of CERN, DESY, Fermilab, IHEP, IN2P3 and SLAC, and interacts closely with HEP publishers, arXiv.org, NASA-ADS, PDG, HEPDATA and other information resources.
INSPIRE represents a natural evolution of scholarly communication, built on successful community-based information systems, and provides a vision for information management in other fields of science.
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Podlasie digital repository of natural science data
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The Museum is committed to open access and open science, and has launched the Data Portal to make its research and collections datasets available online. It allows anyone to explore, download and reuse the data for their own research. Our natural history collection is one of the most important in the world, documenting 4.5 billion years of life, the Earth and the solar system. Almost all animal, plant, mineral and fossil groups are represented. These datasets will increase exponentially. Under the Museum's ambitious digital collections programme we aim to have 20 million specimens digitised in the next five years.
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Welcome to the National Yang Ming Chiao Tung University Dataverse research data knowledge management website, where you can learn how to obtain, upload, cite and explore research data in the National Yang Ming Chiao Tung University Dataverse.
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As a research data hub for social and economic history, Emporion enables the free and standards-compliant publication of time series, historical statistical and panel data, georeferenced vector data, text mining analyses and data papers. Emporion is also open to contributions from the fields of business and environmental history and the history of technology. Emporion's supporting institutions are the DFG Priority Programme 1859 'Experience and Expectations. Historical Foundations of Economic Behavior' and the Gesellschaft für Sozial- und Wirtschaftsgeschichte in conjunction with the Staatsbibliothek zu Berlin – Preußischer Kulturbesitz.
Subject(s)
- Water Research
- Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
- Bioinformatics and Theoretical Biology
- Water Research
- Urbanism, Spatial Planning, Transportation and Infrastructure Planning, Landscape Planning
- Geosciences (including Geography)
- Natural Sciences
- Basic Biological and Medical Research
- Biology
- Life Sciences
- Construction Engineering and Architecture
- Construction Engineering and Architecture
- Engineering Sciences
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4TU.ResearchData, previously known as 4TU.Centre for Research Data, is a research data repository dedicated to the science, engineering and design disciplines. It offers the knowledge, experience and the tools to manage, publish and find scientific research data in a standardized, secure and well-documented manner. 4TU.ResearchData provides the research community with:
Customised advice and support on research data management;
A long-term repository for scientific research data;
Support for current research projects;
Tools to enhance reuse of research data.
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Open access to macromolecular X-ray diffraction and MicroED datasets. The repository complements the Worldwide Protein Data Bank. SBDG also hosts reference collection of biomedical datasets contributed by members of SBGrid, Harvard and pilot communities.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
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The Odum Institute Archive Dataverse contains social science data curated and archived by the Odum Institute Data Archive at the University of North Carolina at Chapel Hill. Some key collections include the primary holdings of the Louis Harris Data Center, the National Network of State Polls, and other Southern-focused public opinion data.
Please note that some datasets in this collection are restricted to University of North Carolina at Chapel Hill affiliates. Access to these datasets require UNC ONYEN institutional login to the Dataverse system.
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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
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The GEOROC data repository hosts research data within the scope of the GEOROC database: geochemical compositions of rocks, glasses, minerals and inclusions from all geological settings on Earth. The repository is curated by the Digital Geochemical Data Infrastructure (DIGIS) project at Göttingen University.
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The Research Data Center (RDC) “International Survey Programs“ provides researchers with data, services, and consultation on a number of important international study series which are under intensive curation by GESIS. They all cover numerous countries and, quite often, substantial time spans. The RDC provides optimal data preparation and access to a wide scope of data and topics for comparative analysis.
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The Slovenian Social Science Data Archives (Slovenski Arhiv Družboslovnih podatkov - ADP) were established in 1997 as an organizational unit within the Institute of Social Sciences at the Faculty of Social Sciences, University of Ljubljana. Its tasks are to acquire significant data sources within a wide range of social science disciplines of interest to Slovenian social scientists, review and prepare them for digital preservation, and to disseminate them for further scientific, educational and other purposes.
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WDC for STP, Moscow collects, stores, exchanges with other WDCs, disseminates the publications, sends upon requests data on the following Solar-Terrestrial Physics disciplines: Solar Activity and Interplanetary Medium, Cosmic Rays, Ionospheric Phenomena, Geomagnetic Variations.
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The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.
- Current projects
- EOSC FAIR-IMPACT
- re3data COREF
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To the extent possible under law,
re3data.org
has waived all copyright and related or neighboring rights to
the database entries of re3data.org.
-
Except where otherwise noted, content on this site is licensed under a
Creative Commons Attribution 4.0 International License
.
- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-05-18
