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Found 6 result(s)
Research Data Australia, the flagship service of the Australian National Data Service (ANDS), provides a comprehensive window into the Australian Research Data Commons. Research Data Australia is an Internet-based discovery service designed to provide rich connections between data, projects, researchers and institutions, and promote visibility of Australian research data collections in search engines. ANDS is partnering with research institutions and data producing agencies to bring about four transformations to data - unmanaged to managed, disconnected to connected, invisible to findable and single use to reusable - that will enable Australia's research data to become a national strategic resource to support better, more efficient and defensible research, and improved policy input. We do not store the data itself here but provide descriptions of, and links to, the data from our data publishing partners. ANDS is funded by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS) and the Education Investment Fund (EIF) Super Science Initiative.
The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
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.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
The Research Data Repository is the University of Essex's online data repository where research data resulting from research taking place within the university can be deposited, published and made accessible to the research community.
The National Trauma Data Bank® (NTDB) is the largest aggregation of trauma registry data ever assembled. The goal of the NTDB is to inform the medical community, the public, and decision makers about a wide variety of issues that characterize the current state of care for injured persons. Registry data that is collected from the NTDB is compiled annually and disseminated in the forms of hospital benchmark reports, data quality reports, and research data sets. Research data sets that can be used by researchers. To gain access to NTDB data, researchers must submit requests through our online application process