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Found 12 result(s)
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Bilkent University Institutional Repository (BUIR), a service of Bilkent University Libraries, collects, preserves, and distributes the intellectual output of Bilkent University. Faculty, staff, and students are invited to deposit their research and scholarship. Departments, administrative units, programs, and centers are invited to use the Institutional Repository to distribute their working papers, technical reports, conference proceedings, and other research material.
In order to meet the needs of research data management for Peking University. The PKU library cooperate with the NSFC-PKU data center for management science, PKU science and research department, PKU social sciences department to jointly launch the Peking University Open Research Data Platform. PKU Open research data provides preservation, management and distribution services for research data. It encourage data owner to share data and data users to reuse data.
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.
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.
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.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.