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Journal of Library and Information Science in Agriculture ›› 2022, Vol. 34 ›› Issue (6): 36-49.doi: 10.13998/j.cnki.issn1002-1248.22-0114

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Scientific and Technical Literature Data Management System Based on Life Cycle Model

CHANG ZhiJun1,2, XU LiYuan1,*, YU QianQian1, ZHANG JianYong1,2, WANG YongJi3   

  1. 1. National Science Library, Chinese Academy Sciences, Beijing 100190;
    2. Department of Library Information and Archives Management, National Science Library, Chinese Academy of Sciences, Beijing 100049;
    3. State Key Laboratory of Computer Science Institute of Software, The Chinese Academy of Sciences, Beijing 100190
  • Received:2022-03-01 Online:2022-06-05 Published:2022-07-08

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Abstract: [Purpose/Significance] Scientific and technical (S&T) literature data resources are characterized with wide coverage, large quantity, many types, fast update and strong timeliness. In order to improve the effect and security of S&T literature data management, this paper studies the S&T literature management system based on the data life cycle model. [Method/Process] This paper explores the management mode of S&T documents, constructs the life cycle system of S&T documents based on the data management process, and expounds the data management tools and methods from the stages of data creation, data storage, data pre-processing, data calculation, data service, data archiving and data destruction. In the data creation stage, specific data access forms are formulated for different sources and data types, and personalized data creation tools are built to receive data completely. In the data storage stage, a unified document metadata storage system is developed by analyzing the characteristics and shortcomings of various types of data, so as to better explain and organize scientific and technological document data. In the data pre-processing stage, various tools are built to realize the formatting pre-processing, parsing, conversion, structuring and other operations of various types of data. In the data computing stage, data enrichment processing, entity relationship extraction and knowledge graph construction are mainly completed. Data provides services through a unified service interface. Data archiving completes data archiving and saving. In the data destruction phase, unnecessary data is safely destroyed. [Results/Conclusions] In this paper, the management and practice based on the life cycle of S&T literature were first carried out based on the core data set Web Of Science BP data , and then explored from the seven phases of creation, storage, pre-processing, calculation, service, archiving and destruction. Finally, based on the DAMA data quality evaluation principle, the comprehensive evaluation and evaluation of the data management effect were carried out from the six dimensions of integrity, uniqueness, real-time, validity, accuracy and consistency. The receiving integrity of data was 100%, and the non-null integrity of data was 59.75%. The uniqueness of data reached 99.23%. The real time of data was controllable. The validity of data met the constraint conditions. The accuracy of the data reached 100%. The consistency of data reached 90%. It basically solved the problem that data can be effectively managed and applied in each life cycle stage. Finally, the management model was verified to take effect and achieve desirable service effect.

Key words: life cycle management, scientific and technical (S&T) literature, data management, big data governance, knowledge graph

CLC Number: 

  • TN919
[1] 朱扬勇, 叶雅珍. 从数据的属性看数据资产[J]. 大数据, 2018, 4(6): 65-76.
ZHU Y Y, YE Y Z.Defining data assets based on the attributes of data[J]. Big data research, 2018, 4(6): 65-76.
[2] 云脑数据. 2020年25个令人印象深刻的大数据统计[EB/OL]. [2021-03-26]. https://zhuanlan.zhihu.com/p/360112834.
Dat@mind. 25 impressive big data staticstics in2020[EB/OL]. [2021-03-26]. https://zhuanlan.zhihu.com/p/360112834.
[3] 匡华恩. 地质科技文献的管理暨开发利用[J]. 资源信息与工程, 2018, 33(5): 205-206.
KUANG E H.Management and development and utilization of geological scientific and technological documents[J]. Resource information and engineering, 2018, 33(5): 205-206.
[4] Welcome to the cloud security alliance[EB/OL]. [2020-01-21].https://cloudsecurityalliance.org/.
[5] 刘燕, 杨林, 侯丽, 等. 基于USGS生命周期模型的肿瘤流行病学数据管理研究[J]. 中华医学图书情报杂志, 2017, 26(12): 7-14.
LIU Y, YANG L, HOU L, et al.Geographic survey(USGS) data life cycle model-based tumor epidemiology data management[J]. Chinese journal of medical library and information science, 2017, 26(12): 7-14.
[6] USGS data lifecycle overview[EB/OL]. [2018-01-21].https://www.usgs.gov/data-management/ data-lifecycle.
[7] Document, discover and interoperate[EB/OL]. [2020-01-21]. http://www.icpsr.umich.edu/DDI/index.html
[8] 张迎, 张志平, 梁冰. 科学数据管理应用模式的研究[J]. 情报工程, 2017, 3(4): 71-77.
ZHANG Y, ZHANG Z P, LIANG B.Research on scientific data management application model[J]. Technology intelligence engineering, 2017, 3(4): 71-77.
[9] 国务院办公厅. 国务院办公厅印发《科学数据管理办法》[EB/OL]. [2018-04-02]. http://www.gov.cn/xinwen/2018-04/02/content_5279295.htm.
General Office of the State Council. The General Office of the State Council issued the Measures for the Administration of Scientific Data[EB/OL].[2018-04-02]. http://www.gov.cn/xinwen/2018-04/02/content_5279295.htm.
[10] 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]. [2018-04-02]. http://www.gov.cn/zhengce/content/2018-04/02/content_5279272.htm.
General Office of the State Council. Notice of the General Office of the State Council on printing and distributing the Measures for the Administration of Scientific Data[EB/OL].[2018-04-02]. http://www.gov.cn/zhengce/content/2018-04/02/content_5279272.htm.
[11] 张洋, 肖燕珠. 生命周期视角下《科学数据管理办法》解读及其启示[J]. 图书馆学研究, 2019(15): 37-43, 13.
ZHANG Y, XIAO Y Z.Interpretation and englightenment on the Rules of Scientific Data Management from the perspective of life cycle[J]. Research on library science, 2019(15): 37-43, 13.
[12] KUMAR R, ROHITASH K B.Data life cycle management in big data analytics[J]. Procedia computer science, 2020, 173(1): 364-371.
[13] 张培风, 张连分. 全球科研范式变革下的图书馆科学数据管理服务创新——基于数据管理生命周期的视角[J]. 图书馆理论与实践, 2019(5): 39-48.
ZHANG P F, ZHANG L F.The service innovation of library scientif-ic data management under the changes of research paradigm - From the perspective of data life cycle[J]. Library theory and practice, 2019(5): 39-48.
[14] BASHARAT A M, SHEIKH M I, MIR S H.System development life cycle of e-learning content management systems[J]. International journal of knowledge management and practices, 2016, 4(2): 56-66.
[15] 刘南海. 基于DAMA体系运营商数据资产管理体系构建研究[J]. 电信网技术, 2016(9): 61-66.
LIU N Y.The research and practice of the data asset management for telecom operator based DAMA[J]. Information and coumunications technology, 2016(9): 61-66.
[16] 张静蓓, 任树怀. 国外科研数据知识库数据质量控制研究[J]. 图书馆杂志, 2016, 35(11): 38-44.
ZHANG J B, REN S H.Studies on data quality control of data repository abroad[J]. Library journal, 2016, 35(11): 38-44.
[17] 常志军, 钱力, 谢靖, 等. 基于分布式技术的科技文献大数据平台的建设研究[J]. 数据分析与知识发现, 2021, 5(3): 69-77.
CHANG Z J, QIAN L, XIE J, et al.Big data platform for sci-rech literature based on distributed technology[J]. Data analysis and knowledge discovery, 2021, 5(3): 69-77.
[18] 张建勇, 于倩倩, 黄永文, 等. NSTL统一文献元数据标准的设计与思考[J]. 数字图书馆论坛, 2016(2): 33-38.
ZHANG J Y, YU Q Q, HUANG Y W, et al.Metadata standard design of NSTL unified literature[J]. Digital library forum, 2016(2):33-38.
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