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Found 3 result(s)

MatDB

MatDatabase

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MatDB is a database application for experimentally measured engineering materials data. It supports open, registered, and restricted access. It presently hosts more than 20.000 unique data sets coming mainly from European and Member State research programmes. It supports web interfaces for entering, browsing, and retrieving data. MatDB is also enabled for innovative services, including data citation and interoperability standards. The data citation service relies on DataCite DOIs. The historic data sets are being enabled for citation. For all new projects where MatDB is used for managing project data, end-users are encouraged to request DataCite DOIs. There is though no obligation as regards the access level as it is considered sufficient simply that the data sets are made discoverable through data citation. The service that relies on interoperability standards leverages the outputs from a series of CEN Workshops that aim to deliver Standards-compliant data formats for engineering materials data. In this context, MatDB is used to validate and demonstrate said formats with a view to promoting their adoption. MatDB is part of the ODIN Portal https://odin.jrc.ec.europa.eu/alcor/

ODIN

Online Data & Information Network for Energy

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The ODIN Portal hosts scientific databases in the domains of structural materials and hydrogen research and is operated on behalf of the European energy research community by the Joint Research Centre, the European Commission's in-house science service providing independent scientific advice and support to policies of the European Union. ODIN contains engineering databases (Mat-Database, Hiad-Database, Nesshy-Database, HTR-Fuel-Database, HTR-Graphit-Database) and document management sites and other information related to European research in the area of nuclear and conventional energy.

OpenML

Open Machine Learning

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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.