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The NCAA Student-Athlete Experiences Data Archive provides access to data about student athletes and will grow to include a handful of user-friendly data collections related to graduation rates; team-level Academic Progress Rates in Division I; and individual-level data on the experiences of current and former student-athletes from the NCAA's Growth, Opportunities, Aspirations and Learning of Students in college study (GOALS), and the Study of College Outcomes and Recent Experiences (SCORE). In the long run, the NCAA expects to follow this initial release with the publication of as much data as possible from its archives. The data is used by college presidents, athletic personnel, faculty, student-athlete groups, media members, and researchers in looking at issues related to intercollegiate athletics and higher education.
The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.
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.