Priorities for Data Curation Education: Data Center Partnerships and Long-Tail Science


October 9, 2012


Carole Palmer


University of Illinois at Urbana-Champaign


For science to fully exploit digital data in new and innovative ways, research data will need to be collected, curated, and made accessible and usable across domains. The need for workforce development in data curation systems and services has been recognized for many years, and education programs are beginning to mature. But to continue to build strong programs in this emerging field, current data curation practice and research needs to underpin goals for professional education.

Having established a specialization in data curation in 2006, we have assessed our program’s progress to date and identified areas in need of further development to respond to trends in e-science. Analysis of student placements shows interesting trends in the institutions hiring data curation specialists and the nature of the positions, and evaluation of internships provided in national data centers has suggested important areas for further investment. In addition, our recent research on disciplinary differences in data sharing and the value of long-tail data in the sciences has direct implications for further development of data curation curriculum.