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Found 7 result(s)
The Archaeology Data Service supports research, learning and teaching with freely available, high quality and dependable digital resources. It does this by preserving digital data in the long term, and by promoting and disseminating a broad range of data in archaeology. The ADS promotes good practice in the use of digital data in archaeology, it provides technical advice to the research community, and supports the deployment of digital technologies.
The Australian National Corpus collates and provides access to assorted examples of Australian English text, transcriptions, audio and audio-visual materials. Text analysis tools are embedded in the interface allowing analysis and downloads in *.CSV format.
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 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