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Found 116 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.
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
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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.
With the Program EnviDat we develop a unified and managed access portal for WSL's rich reservoir of environmental monitoring and research data. EnviDat is designed as a portal to publish, connect and search across existing data but is not intended to become a large data centre hosting original data. While sharing of data is centrally facilitated, data management remains decentralised and the know-how and responsibility to curate research data remains with the original data providers.
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
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Lithuanian Data Archive for Social Sciences and Humanities (LiDA) is a virtual digital infrastructure for SSH data and research resources acquisition, long-term preservation and dissemination. All the data and research resources are documented in both English and Lithuanian according to international standards. Access to the resources is provided via Dataverse repository. LiDA curates different types of resources and they are published into catalogues according to the type: Survey Data, Aggregated Data (including Historical Statistics), Encoded Data (including News Media Studies), and Textual Data. Also, LiDA holds collections of social sciences and humanities data deposited by Lithuanian science and higher education institutions and Lithuanian state institutions (Data of Other Institutions). LiDA is hosted by the Centre for Data Analysis and Archiving of Kaunas University of Technology (data.ktu.edu).
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The Research Data Repository of the National University of La Plata is an online platform dedicated to the organization and dissemination of research data for the entire academic community of the UNLP. The objective of this platform is to gather and provide access to data generated from all areas of the UNLP to ensure its preservation, encourage reuse and maximize its impact.
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Launched in February 2020, data.sciencespo is a repository that offers visibility, sharing and preservation of data collected, curated and processed at Sciences Po. The repository is based on the Dataverse open-source software and organised into collections: CDSP Collection This collection managed by the Centre des données socio-politiques (CDSP) includes the catalogue of surveys, in the social science and humanities, processed and curated by CDSP engineers since 2005. This catalogue brings together surveys produced at Sciences Po and other French and international institutions. - Sciences Po collection (self-deposit) This collection, which is managed by the Direction des ressources et de l'information scientifique (DRIS), is intended to host data produced by researchers affiliated with Sciences Po, following the self-deposit process assisted by the Library's staff.
The ACSS Dataverse is a repository of interdisciplinary social science research data produced in and on the Arab region. The ACSS Dataverse, part of an initiative of the Arab Council for the Social Sciences in collaboration with the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill, preserves and facilitates access to social science datasets in and on the Arab region and is open to relevant research data deposits.
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Open At LaTrobe (OPAL) is La Trobe University’s official repository for Open Access materials generated by academic and professional staff and HDR students. These include publications and other research outputs, theses, open data, and educational resources. OPAL enables the storage, sharing, and selective publication of files and the assignment of a persistent DOI. Users maintain control over who can see their private files and all uploads are stored in La Trobe University approved storage. Access is via La Trobe University login credentials. La Trobe produces a wide range of useful datasets including supplementary data associated with publications and stand-alone datasets and collections.
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PRISM Dataverse is the institutional data repository of the University of Calgary, which has its purpose in digital archiving and sharing of research data from researchers. PRISM Dataverse is a data repository hosted through Borealis, a service of the Ontario Council of University Libraries and supported by University of Calgary's Libraries and Cultural Resources. PRISM Dataverse enables scholars to easily deposit data, create data-specific metadata for searchability and publish their datasets.
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The Repositori Ilmiah Nasional (RIN) is a means for storing, preserving, citing, analyzing and sharing research data. RIN acts as an online media in managing, storing and sharing research data. Researchers, data writers, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility. Researchers, agencies, and funders have full control over research data.
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FDAT is a research data repository hosted by the University of Tübingen, designed to facilitate long-term archiving and publication of research data. Managed by the Information, Communication and Media Center (IKM), it primarily caters to the humanities and social sciences, while welcoming researchers from all scientific disciplines at the university. Committed to high-quality data management, FDAT emphasizes the importance of adhering to the FAIR Data Principles, promoting findability, accessibility, interoperability, and reusability of the research data it contains.
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Created and managed by the Library, DataSpace@HKUST is the data repository and workspace service for HKUST research community. Faculty members and research postgraduate students can use the platform to store, share, organize, preserve and publish research data. It is built on Dataverse, an open source web application developed at Harvard’s Institute for Quantitative Social Science. Using Dataverse architecture, the repository hosts multiple "dataverses". Each dataverse contains datasets; while each dataset may contain multiple data files and the corresponding descriptive metadata.
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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.
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.
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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.
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.