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Found 15 result(s)
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 National Science Digital Library provides high quality online educational resources for teaching and learning, with current emphasis on the sciences, technology, engineering, and mathematics (STEM) disciplines—both formal and informal, institutional and individual, in local, state, national, and international educational settings. The NSDL collection contains structured descriptive information (metadata) about web-based educational resources held on other sites by their providers. These providers have contribute this metadata to NSDL for organized search and open access to educational resources via this website and its services.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
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.
Country
TUL Open Research Data Repository (RDB.open) is a service addressed to the scientific and research community of the Lodz University of Technology. The main purpose of RDB.open is to collect, share and store the open research data, both during the research and after its completion, at least for the minimum period indicated by the funder or the scientists. The RDB.open is a place where research data can be openly shared, accessed and then reused by others.
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.
For datasets from individual researchers or research groups affiliated with Stockholm University, who do not want set up a separate Dataverse for a project or institution. Metadata provisions for Geospatial, Social Science, Humanities, Astronomy, Astrophysics, Life Sciences and Journals (all optional, by choice) are included. Data curation help from Stockholm University Library possible on request.