Changing Data Policies in China: Implications for Enabling FAIR Data
- 425 Downloads
As fundamental resources of research activities, data is vitally important for scientific progress and general social society. Thus, open data practices are becoming more prevalent and the adoption of the FAIR (Findable, Accessible, Interoperable, and Reusable) principles is fostering open access data from four general perspectives. This paper firstly analyzes the general benefits and necessities of open data and the FAIR principles. Then, data policies in China are described from four views. Subsequently, challenges and opportunities for data usability across disciplinary boundaries and levels of expertise are described. Finally, categories are presented for how data policies in China enable FAIR data in terms of the four views of Chinese data policies. Above all, FAIR data is a good beginning, and for FAIR open data, we still need more efforts on intrinsic data culture, trustworthiness, sustainability, and multilateral cooperation among various stakeholders, as well as consistent and effective approaches for adopting data policies.
KeywordsData policy FAIR Open data Research data China
This work is an outcome of the project of “International and National Scientific Data Resources Development Report in China 2018” (No. 2018DDJ1ZZ14) supported by the National Science and Technology Infrastructure Center, and the project “Decision Making Oriented Massive Data Resources Sharing and Governance” (No. 91546125) supported by National Natural Science Foundation of China, and “Big data resources pool and system portal” (No. XDA19020104) funded by the Chinese Academy of Sciences.
- CoreTrustSeal: Data Repositories Requirements (n.d.). https://www.coretrustseal.org/why-certification/requirements/. Accessed 8 Jan 2019
- Doshi, J.A., Hendrick, F.B., Graff, J.S., et al.: Data, data everywhere, but access remains a big issue for researchers: a review of access policies for publicly funded patient-level health care data in the United States. EDM Forum Community 4(2), 1–20 (2016). https://doi.org/10.13063/2327-9214.1204CrossRefGoogle Scholar
- HXMT: Data policy of HXMT (2018). http://www.hxmt.org/index.php/2013-03-22-08-08-48/docs/319-hxmt-data-polocy-of-hxmt. Accessed 29 Dec 2018. (in Chinese)
- Lamost: Lamost DR 6 V1 (2018). http://dr6.lamost.org/. Accessed 29 Dec 2018
- General Office of the State Council, China: Measures for Managing Scientific Data (2018). http://www.gov.cn/zhengce/content/2018-04/02/content_5279272.htm. Accessed 9 Jan 2019
- OECD: Business models for sustainable research data repositories. OECD Science, Technology and Industry Policy Papers, No. 47. OECD Publishing, Paris (2017). https://doi.org/10.1787/302b12bb-en
- Feng, H.: Interpretation of the first national level Measures for managing scientific data. People’s Daily, 8 April 2018. http://www.xinhuanet.com/politics/2018-04/08/c_1122647406.htm. Accessed 9 Jan 2019. (in Chinese)
- Wilkinson, M., Dumontier, M., Aalbersberg, I., et al.: The FAIR guiding principles for scientific data management and stewardship. Nat. Sci. Data 3(2016). https://doi.org/10.1038/sdata.2016.18