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Found 39 result(s)
Country
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.
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
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.
Country
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.
SUNScholarData is an institutional research data repository which can be used for the registration, archival storage, sharing and dissemination of research data produced or collected in relation to research conducted under the auspices of Stellenbosch University. The repository has a public interface which can be used for finding content. It also has private user accounts which can be used by Stellenbosch University users in order to upload, share or publish their research data. In addition to this Stellenbosch University researchers can also use SUNScholarData in order to collaborate with researchers from other institutions whilst working on their research projects. The repository creates a medium through which Stellenbosch University’s research data can be made findable and accessible. It also facilitates the interoperability and re-usability of the university’s research data.
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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.
Country
heidICON is provided by Heidelberg University Library and is the "Virtual Slide Collection" in progress of organization of Heidelberg University. In addition to record graphic material on current interest for research and teaching, the University departments and institutes can digitize and transfer their already existing slide collections.
The Longitudinal Aging Study Amsterdam (LASA) at the VU University and VU University Medical Centre is initiated by the Ministry of Health, Welfare and Sports in 1991 to determine predictors and consequences of ageing. LASA focuses on, physical, emotional, cognitive and social functioning in late life, the connections between these aspects, and the changes that occur in the course of time
The University of Cape Town (UCT) uses Figshare for institutions for their data repository, which was launched in 2017 and is called ZivaHub: Open Data UCT. ZivaHub serves principal investigators at the University of Cape Town who are in need of a repository to store and openly disseminate the data that support their published research findings. The repository service is provided in terms of the UCT Research Data Management Policy. It provides open access to supplementary research data files and links to their respective scholarly publications (e.g. theses, dissertations, papers et al) hosted on other platforms, such as OpenUCT.
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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.
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Arquivo.pt is a research infrastructure that preserves millions of files collected from the web since 1996 and provides a public search service over this information. It contains information in several languages. Periodically it collects and stores information published on the web. Then, it processes the collect data to make it searchable, providing a “Google-like” service that enables searching the past web (English user interface available at https://arquivo.pt/?l=en). This preservation workflow is performed through a large-scale distributed information system and can also accessed through API (https://arquivo.pt/api).
IBICT is providing a research data repository that takes care of long-term preservation and archiving of good practices, so that researchers can share, maintain control and get recognition for your data. The repository supports research data sharing with Quote persistent data, allowing them to be played. The Dataverse is a large open data repository of all disciplines, created by the Institute for Quantitative Social Science at Harvard University. IBICT the Dataverse repository provides a means available for free to deposit and find specific data sets stored by employees of the institutions participating in the Cariniana network.
The figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.