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Found 60 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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The MacEwan University Data Repository provides a place to store, share, and explore data and supports the teaching and scholarly activity of MacEwan University.
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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DABAR (Digital Academic Archives and Repositories) is the key component of the Croatian e-infrastructure’s data layer. It provides technological solutions that facilitate maintenance of higher education and science institutions' digital assets, i.e., various digital objects produced by the institutions and their employees.
For datasets big and small; Store your research data online. Quickly and easily upload files of any type and we will host your research data for you. Your experimental research data will have a permanent home on the web that you can refer to.
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 University of Chile Research Data Repository preserves, disseminates and provides access to the research data generated by its academics and researchers, in order to give visibility, guarantee its preservation and facilitate its access and reuse.
The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.
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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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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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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.
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.
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.
The UBIRA eData repository is a multidisciplinary online service for the registration, preservation and publication of research datasets produced or collected at the University of Birmingham. It is part of the University of Birmingham Research Archive (UBIRA).
University of Alberta Dataverse is a service provided by the University of Albert Library to help researchers publish, analyze, distribute, and preserve data and datasets. Open for University of Alberta-affiliated researchers to deposit data.
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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.
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Science Data Bank is an open generalist data repository developed and maintained by the Chinese Academy of Sciences Computing and Network Information Center (CNIC). It promotes the publication and reuse of scientific data. Researchers and journal publishers can use it to store, manage and share science data.
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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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
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 Research Data Repository of the University of Mannheim invites all researchers and faculty of the University of Mannheim to archive their research data here in order to make it accessible through the Internet. All archived data sets receive DOIs (Digital Object Identifier) to make them accessible and citable. Using this repository is free of charge.
Content type(s)
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.