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Found 9 result(s)

ASU Library Research Data Repository

Arizona State University Dataverse

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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.

Materials Data Repository

MDR

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MDR is a data repository to collect and store papers, presentation materials, and related materials data to accumulate and release them in a form suitable for the promotion of materials research and materials informatics. Users can search the documents and the data from information (metadata) such as sample, instrument, method, and from the full text of the deposited data, to browse and download them freely. User registration is not required and there is no charge for use.

Australian Bureau of Meteorology data catalogue

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Meteorology, atmospheric science and oceanography, forecasts, current and historical observations for weather, water, space weather data; data analyses and reports.

National Genomic Resources Repository

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National Genomic Resources Repository is established as an institutional framework for methodical and centralized efforts to collect, generate, conserve and distribute genomic resources for agricultural research.

UC Irvine Machine Learning Repository

UCI Machine Learning Repository

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The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.

GIGA Research Data

GIGA Metadata Database

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The GIGA (German Institute of Global and Area Studies) researchers generate a large number of qualitative and quantitative research data. On this page you will find descriptions of this research data ("metadata") as well as information about the available access options. To facilitate its reuse, and to enhance research transparency, a large part of the GIGA research data is published in datorium, a repository hosted by the GESIS Leibniz Institute for the Social Sciences: https://www.re3data.org/repository/r3d100011062 Our objective is to offer free access to as much of our data as possible, to guarantee the possibility of its citation, and to secure its safe storage. Metadata of research data that cannot be published open access due to its sensitivity is also shown on this page.

Yabelana

University of KwaZulu-Natal research repository

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Yabelana is a data repository of the University of KwaZulu-Natal (UKZN) which was developed to preserve, manage and share UKZN-Researchers research data; which include figures, datasets, software/code, images, videos, posters presentations.

XNAT CENTRAL

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XNAT CENTRAL is a publicly accessible datasharing portal at Washinton University Medical School using XNAT software. XNAT provides neuroimaging data through a web interface and a customizable open source platform. XNAT facilitates data uploads and downloads for data sharing, processing and organization. NOTICE: Central XNAT will be decommissioned on October 15, 2023. New project creation is no longer permitted.

METIS

FMI’s Research Data Repository

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Finnish Meteorological Institute (FMI) research data repository METIS is provided by EUDAT and enables the institute data to be preserved, discovered, and accessed. FMI covers a wide range of research on weather, sea, climate and space. According to the FMI's Research Data policy , publicly funded research data must be made available to the widest possible audience (under CC BY license, at the minimum), as the best way to maximize the data impact but also to do justice to all the hard labor put into collecting, cleaning, and analyzing the data.