RDM: Exploration and Practices of Academic Libraries - Partnerships, Collaboration, Expertise

NIE, Hua (2016) RDM: Exploration and Practices of Academic Libraries - Partnerships, Collaboration, Expertise. Paper presented at: IFLA WLIC 2016 – Columbus, OH – Connections. Collaboration. Community in Session 221 - Science and Technology.

Bookmark or cite this item: https://library.ifla.org/id/eprint/1465
Language: English (Original)
Available under licence Creative Commons Attribution.


RDM: Exploration and Practices of Academic Libraries - Partnerships, Collaboration, Expertise

In recent years, RDM has become increasingly important under the context of Open Science and Open Data. The re3data.org already has over1500 data repositories registered. Based on the practice of Peking University Open Research Data Project, this paper will discuss issues of awareness and demands of data providers and users, data policies of both institutional and funding parties, investigation and selection of data management platform, localization of OSS, and the support and collaboration within institutions such as between administrative units and data owners. Peking University Library started planning the Open Research Data Project at the beginning of 2014. However, it seems that we lacked positive demands from the researchers, necessary institutional level policies and partners to cooperate with. After seeking support both internally and externally, and raising awareness of research data as an important format of academic output, Peking University got granted a NSFC (National Science Foundation of China) project with a part of it goes to development of Research Data Platform. With collaboration of the Institution of Social Science Survey and University Research Administration Units and after one year’s development, Peking University Open Research Data Platform launched at the end of 2015. Services provided include completed data capturing, managing and publishing, sharing and storing, DOI registration and authoritative data citing, access and copy right control mechanism, data version archiving, usage statistics, tracking and reporting, online data analysis and visualization plus digital fingerprint, Chinese and English bilingual interface. The Dataverse based platform opens fully to the academics and 2 months after its launch, 15 dataverses created including China Survey Data Archive, China Family Panel Studies, China Health and Retirement Longitudinal Study, Center for Bioinformatices, PKU, Visualization and Visual Analytics Research Group PKU, etc. More and more datasets have been capturing and open to reuse and cite.

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