数据重用影响因素对仓储型数据管理平台发展方向的启示

doi:10.19788/j.issn.2096-6369.230302

Abstract

Abstract:

As a powerful tool and knowledge foundation for scientific research, scientific data have attracted the attention of researchers throughout its entire process of data behavior. Data reuse, as a key component, is of great significance for the development of scientific data management and sharing. Taking the Agricultural Environment Data Sharing Service Platform, developed by the Institute of Agricultural Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, as the starting point, the article introduces relevant research on data reuse and the evolution of the definition of scientific data reuse in terms of time dimension. From the perspective of the impact framework of data reuse, it analyzes the impact of researchers, scientific data, and data platforms on data reuse. Moreover, the article explores the popular and widely-used warehouse-based data management platform models, and proposes the next development inspiration, regarding to the current situation and problems of agricultural data sharing service platforms.

Key words: data reuse, influencing factors, warehouse type, data sharing

SUN YuXiao, LI YanLi, LI Feng, LI Bin. The Enlightenment of Factors Influencing Data Reuse on the Development Direction of Warehouse-Based Data Management Platforms[J].Journal of Agricultural Big Data, 2023, 5(3): 2-10.

Figures/Tables 7

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table 1

Fig. 6

References 18

[1]	Martin M E. The committee on national statistics: 10years later[J]. American Statistician, 1982, 36(2):103-108.
[2]	King G. Replication, replication[J]. PS: Political Science & Politics, 1995, 28(3) : 444-452.
[3]	Committee on issues in the transborder flow of scientific data[EB/OL].[2021-04-16]. http://www.Nap.edu/openbook.php?record_id=5504.
[4]	Karast I H, Baker K S. Digital data practices and the long term ecological research program growing global[J]. International Journal of Digital Curation, 2008, 3(2):42-58.DOI: https://doi.org/10.2218/ijdc.v3i2.57
[5]	Borgman C L. The conundrum of sharing research data[J]. Journal of the American Society for Information Science and Technology, 2011, 63(6):1059-1078. doi: 10.1002/asi.v63.6
[6]	尹文辰. 国内外科学数据重用理论研究与实践进展[J]. 山东图书馆学刊, 2022(2):7-14.
[7]	张潇月, 顾立平, 胡良霖. 国内外开放科研数据重用困境解决措施述评[J]. 图书馆, 2021,(3):80-89.
[8]	王雪, 杨波. 科学数据重复使用的学科差异性研究[J]. 情报杂志, 2021, 40(7):122-126.
[9]	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. doi: 10.1371/journal.pone.0134826.
[10]	文静, 何琳, 韩正彪. 科研人员科学数据重用意愿的影响因素研究[J]. 图书情报知识, 2019(1):11-20.DOI:10.13366/j.dik.2019.01.011.
[11]	魏银珍, 邓仲华, 杨改贞. 科研人员数据重用意愿的影响因素研究[J]. 图书馆理论与实践, 2020(3):11-16.
[12]	Piwowar H A, Vision T J. Data reuse and the open data citation advantage[J]. PeerJ, 2012, 1(3):e175.doi: 10.7717/peerj.175.
[13]	Park H, You S, Wolfram D. Informal data citation for data sharing and reuse is more common than formal data citation in biomedical fields[J]. Journal of the Association for Information Science and Technology, 2018, 69(11):1346-1354. doi: 10.1002/asi.2018.69.issue-11
[14]	Walli J C, Rolando E, BorgmanC L. If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology[J]. PLoS One, 2013, 8(7):e67332. doi: 10.1371/journal.pone.0067332
[15]	秦顺, 戴柏清. 国际科研数据政策导向解析[J]. 图书情报工作, 2022, 66(13):48-60. doi: 10.13266/j.issn.0252-3116.2022.13.005
[16]	王朔桓, 陈媛媛. 美国地理科学数据服务平台建设调查研究[J]. 图书馆学研究, 2018(8):46-54.
[17]	卢垚, 王鸑飞, 刘洪冰, 等. Mendeley Data平台开放科学数据实践及启示[J]. 数字图书馆论坛, 2021(9):19-26.
[18]	彭秀媛. 农业科学数据共享模式与技术系统研究[D]. 北京: 中国农业科学院, 2018.

平台系统	学科领域因素	年龄因素	数据质量和可靠性	元数据	数据易获得性
Figshare科研数据共享平台	√	√	√	√	√
Dryad数据库系统	√	√	√	√	√
ScienceDB	√	√	√	√	√

The Enlightenment of Factors Influencing Data Reuse on the Development Direction of Warehouse-Based Data Management Platforms

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 18

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZHANG MengMeng, WANG XiuJuan, KANG MengZhen, HUA Jing, WANG HaoYu, WANG FeiYue. A Novel Agricultural Data Sharing Mode Based on Rice Disease Identification [J]. Journal of Agricultural Big Data, 2023, 5(4): 13-23.
[2]	LI JiaLe, ZHANG Bin, HE ZiKang, YU GuoPing, ZHOU GuoMin, ZHANG JianHua. Analysis of Consumers' Cognitive Level of the "Three Products, One Label" of Agricultural Products and Influencing Factors: Based on a Questionnaire on Sanya City Residents [J]. Journal of Agricultural Big Data, 2023, 5(4): 86-94.
[3]	DUAN Bowen, WANG Juanle, SHI Lei, GAO Mengxu. Research and Analysis of Typical Databases in Major Frontier Fields at Domestic and International Level [J]. Journal of Agricultural Big Data, 2023, 5(1): 46-54.
[4]	Yuxiao Sun, Yanli Li, Feng Li, Qian Chen. Research and Development Suggestions on Scientific Data Sharing at Home and Abroad [J]. Journal of Agricultural Big Data, 2022, 4(2): 88-98.
[5]	Di Wu, Yong Wang, Dibing Sun, Jie Li, Kunsong Chen. Construction and Application of a Cold Chain Logistics Supervision Platform for Agricultural Products in Port Areas during the COVID-19 Pandemic [J]. Journal of Agricultural Big Data, 2022, 4(1): 62-68.
[6]	Yahui Fan, Liang Zhu, Hua Zhao, Jianhua Zheng. Research on Intellectual Property Protection of Scientific Data Sharing [J]. Journal of Agricultural Big Data, 2021, 3(4): 3-9.
[7]	Muhan Xue, Shuo Xu, Feng Lu, Yong Zhu, Jianguang Wu, Yigang Wang. Construction and Application of a Comprehensive Management Service Platform for Fishing Vessels and Fishing Ports [J]. Journal of Agricultural Big Data, 2021, 3(3): 45-54.
[8]	Jingchao Fan, Rui Man, Xianghe Zhang, Guomin Zhou. Research on Standards for sharing Metadata of National Agricultural Observation Data [J]. Journal of Agricultural Big Data, 2020, 2(4): 14-19.
[9]	Muhan Xue, Huiyuan Liu, Feng Lu, Qingzhao Jiang. Research on Opening sharing and Application of Fishery Scientific Observation Data [J]. Journal of Agricultural Big Data, 2020, 2(4): 29-37.
[10]	Zhongfu Sun, Juncheng Ma, Feixiang Zheng, Keming Du. Preliminary Exploration of Big Data Security Supported by Blockchain in Agriculture [J]. Journal of Agricultural Big Data, 2020, 2(2): 25-37.
[11]	Linying Mi, Chenzhou Cui, Dongwei Fan, Jinxin Hao, Yanjie Xue, Changhua Li, Shanshan Li, Boliang He, Yihan Tao, Jun Han, Yunfei Xu, Hanxi Yang, Sisi Yang, Lan He, Jie Ma, Liang Liu, Xiao Chen, Junyi Chen, Hailong Zhang, Feng Liu. Brief Analysis of Development Strategies for the National Astronomical Data Center [J]. Journal of Agricultural Big Data, 2019, 1(4): 37-45.
[12]	Lijun Xu, Yanmin Yao, Baohui Zhang, Guixia Yang, Ruirui Yan, Asiya, Xiaoni Liu, Xiaoping Xin. Research and Application of Grassland and Forage Science Database in China [J]. Journal of Agricultural Big Data, 2019, 1(4): 46-57.
[13]	Yaping Yang, Yi Wang, Yan Bai, Xiafang Yue, Jia Du, Yongqing Bai, Jiulin Sun. Development and Practice of the National Earth System Science Data Center in China [J]. Journal of Agricultural Big Data, 2019, 1(4): 5-13.
[14]	Yunting Li, Liangming Wen, Lili Zhang, Jianhui Li. The Status and Trends of Scientific Data Sharing Systems [J]. Journal of Agricultural Big Data, 2019, 1(4): 86-97.
[15]	Mengxu Wang Ruidan Wang Chao Xu Bo Shi Lei Gao. Thoughts on the Construction and Development of National Scientific Data Centers in China [J]. Journal of Agricultural Big Data, 2019, 1(3): 21-27.