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Found 12 result(s)
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.
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.
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HilData is registered by Hildesheim University Library, The access is via registration to the data and to the repository. Research data is with regards to educational science. Research data are sensitive and cannot be made fully open. HILDE Online is integrated in HilData: https://www.uni-hildesheim.de/celeb/projekte/fallarchiv-hilde/hildeonline-streaming-server/ HilData is working on its metadata (exposing metadata via interfaces) w.r.t. the FAIR principles and data citation. HilData and HILDE Online provide long-term storage and access to research data. The research data repository provides restricted access to its data. The research data repository uses DOI to make its provided data persistent, unique and citable.
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
Country
The Tecnológico de Monterrey's Data Hub offers Open Data generated by our researchers and other initiatives. This initiative is sponsored by both the Living Lab & Data Hub of the Institute for the Future of Education (IFE and the Tecnologico de Monterrey's Research Office. This repository is organized by Institutes and Schools.
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
Country
<<<!!!<<< The digital archive of the Historical Data Center Saxony-Anhalt was transferred to the share-it repositor https://www.re3data.org/repository/r3d100013014 >>>!!!>>> The Historical Data Centre Saxony-Anhalt was founded in 2008. Its main tasks are the computer-aided provision, processing and evaluation of historical research data, the development of theoretically consolidated normative data and vocabularies as well as the further development of methods in the context of digital humanities, research data management and quality assurance. The "Historical Data Centre Saxony-Anhalt" sees itself as a central institution for the data service of historical data in the federal state of Saxony-Anhalt and is thus part of a nationally and internationally linked infrastructure for long-term data storage and use. The Centre primarily acquires individual-specific microdata for the analysis of life courses, employment biographies and biographies (primarily quantitative, but also qualitative data), which offer a broad interdisciplinary and international analytical framework and meet clearly defined methodological and technical requirements. The studies are processed, archived and - in compliance with data protection and copyright conditions - made available to the scientifically interested public in accordance with internationally recognized standards. The degree of preparation depends on the type and quality of the study and on demand. Reference studies and studies in high demand are comprehensively documented - often in cooperation with primary researchers or experts - and summarized in data collections. The Historical Data Centre supports researchers in meeting the high demands of research data management. This includes the advisory support of the entire life cycle of data, starting with data production, documentation, analysis, evaluation, publication, long-term archiving and finally the subsequent use of data. In cooperation with other infrastructure facilities of the state of Saxony-Anhalt as well as national and international, interdisciplinary data repositories, the Data Centre provides tools and infrastructures for the publication and long-term archiving of research data. Together with the University and State Library of Saxony-Anhalt, the Data Centre operates its own data repository as well as special workstations for the digitisation and analysis of data. The Historical Data Centre aims to be a contact point for very different users of historical sources. We collect data relating to historical persons, events and historical territorial units.