CKB hosts Data Science Symposium at Peking University

Apr 12, 2019 12:00 AM

On the 9th of April 2019, the China Chronic Disease Prospective Study, the China Kadoorie Biobank (CKB) hosted a large cohort data science symposium.

The data science symposium, a key component of the Sino-British CKB project data group exchange visit, was held in the Shuhua Building, School of Public Health, Peking University. Participants at the symposium included members of the Beijing and Oxford data groups, teachers and students of the Peking University School of Public Health, and peers in the domestic regional cohort and special disease cohort.

The symposium was hosted by Professor Zhan Siyan, Director of the Department of Epidemiology and Health Statistics, School of Public Health, Peking University. Professor Zhan Siyan opened the symposium with an overview on the importance of data quality and data management in enabling high quality research. Associate Professor Yu Canqing from Peking University and Sam Sansome from Oxford University then introduced the data management and data science work being undertaken at each institution. The director of the CKB Chinese Field Office, Bian Zheng shared the follow-up work of the CKB project and described the site management process in conjunction with the field data. Finally, data analysts (Daniel Avery and Rebecca Stevens) and data scientist (Alex Hacker) from Oxford University shared and exchanged their experience of managing and gaining insight from big data from the large-scale CKB cohort.

Following on from the symposium, a series of workshops were held at the National Coordinating Centre (NCC) Beijing over the next couple of days. Data group colleagues from the both the International Coordinating Centre (ICC) Oxford and the NCC were joined by experts and project leaders from other domestic studies. In-depth discussions and exchange of experience were shared on how to manage the big data from our large cohort.

As the largest natural population cohort in China, the CKB cohort aims to implement their data management standards across new population cohorts and take the lead in establishing a scientific, sustainable and standardised data management process and data sharing platform to provide an important reference for similar research in China.