[Purpose/significance] The lack of research data metadata knowledge and efficient easy-to-use metadata creation services hinder the sharing and reuse of research data among researchers. Due to the large amount and wide user orientation of the generalist research data repository, the metadata creation service provided by it has references for improving the above dilemmas.[Method/process] Taking six generalist research data repositories recommended by Springer Nature and Scientific Data as samples, this paper investigated and analyzed their metadata creation services from two aspects of the service content composition and the service implementation mode, then summarized their service characteristics and advanced experiences.[Result/conclusion] The metadata creation service provided by the generalist research data repository has five characteristics of following the tradition but has some innovations, striving for simplicity and highlighting its own characteristics, paying attention to the popularization of metadata knowledge and ability transformation, fully ensuring data democracy, paying attention to the organization of related resources and encouraging data reference. Its service model not only pays attention to the ease and usefulness of service but also taking account of the popularization of metadata knowledge, above which have important enlightenment and references for the research data repository construction and metadata creation service design for library and information community in China.
Huang Guobin
,
Wang Tao
. Research on the Metadata Creation Service of the Generalist Research Data Repository[J]. Library and Information Service, 2021
, 65(21)
: 131
-140
.
DOI: 10.13266/j.issn.0252-3116.2021.21.020
[1] FERGUSON L. How and why researchers share data (and why they don't)[EB/OL].[2021-03-20]. https://doi.org/10.6084/m9.figshare.3468365.v1.
[2] TENOPIR C, ALLARD S, DOUGLASS K, et al. Data sharing by scientists:practices and perceptions[J]. PloS one, 2011, 6(6):e21101.
[3] TENOPIR C, DALTON E D, ALLARD S, et al. Changes in data sharing and data reuse practices and perceptions among scientists worldwide[J]. PloS one, 2015, 10(8):e0134826.
[4] Digital Science. The state of open data report 2019[EB/OL].[2021-04-27].https://figshare.com/articles/report/The_State_of_Open_Data_Report_2019/9980783?backTo=/collections/State_of_Open_Data/4046897.
[5] 肖潇,吕俊生.E-science环境下国外图书馆科学数据服务研究进展[J].图书情报工作,2012,56(17):53-58,114.
[6] 王翠萍,李佳潞.国外高校图书馆科学数据服务现状与启示——以五所高校图书馆为例[J].图书馆工作与研究,2017(10):31-36.
[7] 钱鹏,郑建明.高校科学数据组织与服务初探[J].情报理论与实践,2011,34(2):27-29.
[8] 邱春艳.期刊文献与科学数据的关联服务研究[J].情报资料工作,2014(2):63-66.
[9] 黄鑫,邓仲华.国外高校图书馆科学数据的元数据服务研究[J].图书与情报,2017(2):84-90.
[10] 胡芳.国外典型科学数据仓储实施的元数据方案及启示[J].图书与情报,2015(1):117-121.
[11] Springer Nature. Research data policies[EB/OL].[2021-01-21]. https://www.springernature.com/gp/authors/research-data-policy/recommended-repositories/.
[12] Springer Nature. Generalist repositories[EB/OL].[2020-12-09].https://www.springernature.com/gp/authors/research-data-policy/repositories-general/12327166.
[13] 中国科学院计算机网络中心.ScienceDB成为Springer Nature推荐通用存储库[EB/OL].[2021-01-26]. https://www.cas.cn/yx/202010/t20201010_4762415.shtml.
[14] DataCite Metadata Working Group. DataCite metadata schema documentation for the publication and citation of research data and other research outputs (Version 4.4).[EB/OL].[2021-04-16].https://doi.org/10.14454/3w3z-sa82.
[15] 杨波,胡立耘.用于社会科学信息组织的元数据标准——DDI[J].现代图书情报技术,2005(8):7-11.
[16] UK Data Service. Quarterly labour force survey, April-June, 2021[EB/OL].[2021-09-03]. https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8826#!/details.
[17] LIANG D J, ZHUANG M H, HU C Y, et al. China's greenhouse gas emissions for cropping systems from 1978-2016[EB/OL].[2021-09-04]. https://doi.org/10.1038/s41597-021-00960-5.
[18] Data Citation Synthesis Group. Joint declaration of data citation principles[EB/OL].[2021-02-26].https://www.force11.org/group/joint-declaration-data-citation-principles-final.
[19] 完颜邓邓.国外科学数据仓储元数据实践调查及启示[J].新世纪图书馆,2016(5):81-84.
[20] SINGH G, BHARATHI S, CHERVENAK A, et al. A metadata catalog service for data intensive applications[EB/OL].[2021-09-06]. https://dl.acm.org/doi/10.1145/1048935.1050184.
[21] ROBINSON N, JIMENEZ E, TORRES D. Analyzing data citation practices using the data citation index[J]. Journal of the Association for Information Science and Technology, 2016, 67(12):2964-2975.
[22] Dryad. Frequently asked questions[EB/OL].[2021-09-06]. https://datadryad.org/stash/faq.
[23] Figshare. Tutorials[EB/OL].[2021-09-05].https://help.figshare.com/section/tutorials.
[24] Harvard Dataverse. Dataset and file management[EB/OL].[2021-09-05]. https://guides.dataverse.org/en/5.6/user/dataset-management.html.
[25] Zenodo. Frequently asked questions[EB/OL].[2021-09-05]. https://help.zenodo.org/.
[26] Mendeley Data. How can we help you?[EB/OL].[2021-09-06]. https://data.mendeley.com/faq.
[27] Science Data Bank. Frequently asked questions[EB/OL].[2021-09-06].https://www.scidb.cn/en/faq.
[28] VINES T H, ANDREW R L, BOCK D G, et al. Mandated data archiving greatly improves access to research data[EB/OL].[2021-04-25]. https://doi.org/10.1096/fj.12-218164.
[29] NIH. Data management guidance for CISE proposals and awards[EB/OL].[2021-02-02].https://www.nsf.gov/cise/cise_dmp.jsp.
[30] 国务院办公厅.国务院办公厅关于印发科学数据管理办法的通知[EB/OL].[2021-04-20].http://www.gov.cn/zhengce/content/2018-04/02/content_5279272.htm.
[31] ANA V G. NIH figshare instance highlighted use cases[EB/OL].[2021-09-07]. https://figshare.com/articles/online_resource/NIH_Figshare_Instance_Highlighted_Use_Cases/12816464.
[32] 中国科学院科学传播局.国家标准《数据论文出版元数据》立项启动会召开[EB/OL].[2021-04-09]. http://www.bsc.cas.cn/sjdt/202103/t20210324_4782140.html.
