中国科技期刊研究 ›› 2018, Vol. 29 ›› Issue (12): 1229-1233. doi: 10.11946/cjstp.201807040597

• 质量建设 • 上一篇    下一篇

采编系统数据辅助办刊决策分析

任艳青1),王雪峰2),翁彦琴1,)3)()   

  1. 1) 中国科学院文献情报中心,北京市海淀区北四环西路33号 100190
    2) 中国科学院物理研究所《物理学报》编辑部,北京市海淀区中关村南三街8号 100190
    3) 中国科学院大学图书情报与档案管理系,北京市海淀区北四环西路33号 100190
  • 收稿日期:2018-07-04 修回日期:2018-10-18 出版日期:2018-12-15 发布日期:2018-12-15
  • 通讯作者: 翁彦琴 E-mail:wengyq@mail.las.ac.cn
  • 作者简介:任艳青(ORCID:0000-0002-2870-665X),博士,副编审,E-mail: yanqingren1128@163.com。|王雪峰,博士,副编审。
  • 基金资助:
    中国科协科技期刊青年编辑业务研究择优支持项目“数字化环境下科技期刊增值服务模式探析”(castqk2017-qnkt-04)

Analysis of journal policy based on the data of editorial system

REN Yanqing1),WANG Xuefeng2),WENG Yanqin1,)3)()   

  1. 1) National Science Library, Chinese Academy of Sciences, 33 Beisihuan Xilu, Haidian District, Beijing 100190, China
    2) Editorial Office of Acta Physica Sinica, Institute of Physics, Chinese Academy of Sciences, 8 South Third Street, Zhongguancun, Haidian District, Beijing 100190, China
    3) Department of Library, Information and Archives Management, University of Chinese Academy of Sciences, 33 Beisihuan Xilu, Haidian District, Beijing 100190, China
  • Received:2018-07-04 Revised:2018-10-18 Online:2018-12-15 Published:2018-12-15
  • Contact: WENG Yanqin E-mail:wengyq@mail.las.ac.cn

摘要:

【目的】将科技期刊采编过程中产生的数据反馈于办刊的决策过程中,使期刊出版和管理成为闭环,促进期刊质量和影响力的提高。【方法】通过深入分析采编系统中存在的收发稿件数据和评审数据,挖掘数据映射出的实际问题。【结果】对采编系统中数据的分析和深入挖掘,有助于进一步优化期刊的收稿方向,合理地统筹安排刊期与专刊组织频次,提高期刊同行评议的效率,通过挖掘核心作者与机构,可有目标、有针对性地做好期刊的宣传推广。【结论】采编系统的数据为办刊决策提供了量化的数据支撑,对相关数据的深入分析和挖掘,有助于明确期刊的办刊思路和方向,对办刊具有一定的指导意义。

关键词: 科技期刊, 数据分析, 采编系统, 数据挖掘, 办刊决策

Abstract:

[Purposes] This paper aims to feed the data generated during the process of collecting and editing of scientific journals into the decision-making process, make the journal publication and management become a closed-loop, which will help to promote the improvement of journal quality and influence. [Methods] Through in-depth analysis of the manuscript data and review data, we found some help and guidance to the journals. [Findings] The data analysis can give some instructions to optimize the distribution of scientific subjects, arrange the frequency of the publication and special issues, improve the efficiency of the peer review, and find the core authors and mining core institutions. [Conclusions] The method of data analysis of editorial system provides the quantitative data support for the decision-making, and the in-depth analysis and excavation of the relevant data helps to clarify the direction of journal running, and has a certain guiding significance to the journal operation.

Key words: Scientific journal, Data analysis, Editorial system, Data mining, Decision-making of journal operation