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Found 5 result(s)
In order to meet the needs of research data management for Peking University. The PKU library cooperate with the NSFC-PKU data center for management science, PKU science and research department, PKU social sciences department to jointly launch the Peking University Open Research Data Platform. PKU Open research data provides preservation, management and distribution services for research data. It encourage data owner to share data and data users to reuse data.
The UK Data Archive, based at the University of Essex, is curator of the largest collection of digital data in the social sciences and humanities in the United Kingdom. With several thousand datasets relating to society, both historical and contemporary, our Archive is a vital resource for researchers, teachers and learners. We are an internationally acknowledged centre of expertise in the areas of acquiring, curating and providing access to data. We are the lead partner in the UK Data Service (https://service.re3data.org/repository/r3d100010230) through which data users can browse collections online and register to analyse and download them. Open Data collections are available for anyone to use. The UK Data Archive is a Trusted Digital Repository (TDR) certified against the CoreTrustSeal (https://www.coretrustseal.org/) and certified against ISO27001 for Information Security (https://www.iso.org/isoiec-27001-information-security.html).
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The Informatics Research Data Repository is a Japanese data repository that collects data on disciplines within informatics. Such sub-categories are things like consumerism and information diffusion. The primary data within these data sets is from experiments run by IDR on how one group is linked to another.
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.