图书情报工作 ›› 2019, Vol. 63 ›› Issue (22): 129-140.DOI: 10.13266/j.issn.0252-3116.2019.22.014

• 知识组织 • 上一篇    下一篇

数据论文的内容规范性研究

黄国彬, 郑霞   

  1. 北京师范大学政府管理学院 北京 100875
  • 收稿日期:2019-04-14 修回日期:2019-07-12 出版日期:2019-11-20 发布日期:2019-11-20
  • 通讯作者: 郑霞(ORCID:0000-0002-9788-5823),硕士研究生,通讯作者,E-mail:zhengxia199405@163.com。
  • 作者简介:黄国彬(ORCID:0000-0001-9059-8285),副教授,硕士研究生导师,博士

Research on Content Normalization of Data Paper

Huang Guobin, Zheng Xia   

  1. School of Government, Beijing Normal University, Beijing 100875
  • Received:2019-04-14 Revised:2019-07-12 Online:2019-11-20 Published:2019-11-20

摘要: [目的/意义] 科学数据的规范化管理、引用和重用已受到学术界的广泛关注。在此背景下,用于促进科学数据合理使用的数据论文、数据期刊大量涌现。然而,数据论文目前尚未形成统一化、标准化的体例。本研究归纳和提炼当前在数据出版界较为活跃的数据期刊所发表的数据论文的内容框架和核心模块,以期为相关人员或机构在数据论文的撰写、使用和管理提供参考。[方法/过程] 综合应用内容分析法和比较研究法,依据科学数据使用者查找、获取与重用科学数据的思维模式,基于不同数据期刊发布的投稿指南或写作须知,从主题相关性、数据质量、数据产生及获取方法、应用场景、使用方法、补充说明6个维度剖析数据论文的内容框架和核心模块。[结果/结论] 目前并没有一种数据期刊的数据论文投稿指南或写作须知能够全部涵盖数据论文的所有模块;数据论文内容构成与传统学术论文的内容构成既有联系又有区别;数据论文内容框架的必备模块侧重于描述科学数据的突出特性;当前尚未形成体现科学数据特性的规范化描述框架。

关键词: 数据论文, 科学数据, 内容框架, 内容规范

Abstract: [Purpose/significance] The standardized management, citation and reuse of scientific data has attracted wide attention in academic circles. In this context, a large number of data papers and data journals have emerged to promote the rational use of scientific data. However, data paper has not yet formed a unified and standardized system. The study will summarize and refine the content framework and core modules of data paper published by data journals which are active in the research data publishing field, in order to provide reference for relevant personnel or organizations in writing, use and management of data papers.[Method/process] Comprehensive application of content analysis and comparative research methods, based on the thinking mode of scientific data users in searching, acquiring and reusing research data, and based on the submission guides or writing instructions issued by different data journals, the content framework and core modules of data paper were analyzed from six perspectives, including subject relevance, data quality, data generation and acquisition methods, application scenarios, usage methods and supplementary instructions.[Result/conclusion] At present, there is no submission guide or writing instructions of data journals that can fully cover all modules of data paper; the content composition of data paper is related to and different from that of traditional academic paper; the essential module of content framework of data paper focuses on describing the prominent characteristics of scientific data; a normalized description framework for features of scientific data is still on the way.

Key words: data paper, scientific data, content framework, content normalization

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