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Journal of library and information science in agriculture ›› 2024, Vol. 36 ›› Issue (7): 76-87.doi: 10.13998/j.cnki.issn1002-1248.24-0416

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Attribution of Academic Contributions to Multiple Scientific Outputs from an Open Science Perspective

Leilei KOU   

  1. Institute of Tibetan Plateau Humanistic Environment, Lanzhou University, Lanzhou 730000
  • Received:2024-06-18 Online:2024-07-05 Published:2024-11-26

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Abstract:

[Purpose/Significance] In the open science environment, the mode of collaborative knowledge production is widely used, and the types of scientific outputs are becoming increasingly diverse. Therefore, effective identification and recognition of various contribution contents made by different contributors in open research is crucial to improve transparent disclosure and effective use of research output's contribution data. [Method/Process] Based on the systematic study of domestic and foreign scholarly contribution theories and practices, this study proposes a scholarly contribution analysis system for open science. From the perspective of the creation process of scientific research outputs, research on the attribution of scientific contributions is carried out, focusing on three aspects: the identification of contributors and contribution elements, the calculation of the degree of contribution, and the representation of contribution data. In addition, a paper from the open access platform PLoS One is selected as an empirical case to demonstrate the validity of the process and method of attributing scholarly contributions. It was found that the contribution score is inversely proportional to the number of contributors, i.e., the more the number of contributors, the less likely it is to have a high contribution score. The more contribution elements contributors participate in, the higher the contribution score they receive. If contributors participate in the same contribution elements, and their contribution scores may also be the same. For the same contribution factor, the higher the number of contributors, the lower the contribution degree of each contributor. This paper summarizes the application scenarios of academic contributions from three aspects: clearly distinguishing author and non-author contributors, establishing correlation between contribution data and other LOD ontologies, establishing attribution and responsibility mechanism for academic contributions, and improving the index system of scientific research evaluation. [Results/Conclusions] Academic contribution is an important part of the open science system. It is an inevitable trend to improve the openness and transparency of academic contributions to various scientific research results. However, existing methods for attributing contributions are scattered, lack systematicity, and mainly apply to a certain type of achievement, which has certain limitations in terms of disciplines and achievements. In the future, the applicability of the contribution attribution method can be improved by expanding the application objects of contributions to include research papers, scientific data, scientific software, preprints, scientific notes, and more, establishing a common contribution element system for all types of research outputs, and optimizing the method of calculating the contribution rate. Finally, it is necessary to continuously enrich and expand the application scope and application scenarios of scientific research output's contribution data.

Key words: open science, scientific research outputs, contribution data, contribution identification, contribution attribution

CLC Number: 

  • G252.6

Fig.1

Academic contribution analysis system for open science"

Table 1

Open research outputs at all stages"

研究阶段 成果产出 获取平台
规划准备

研究报告：包括研究构思和、项目规划设计等

研究协议：开展项目协作的研究协议

 Trello、protocols.io
研究实施 数据集：数据收集、数据处理和数据保存等各阶段的原始数据集和其他数据集 Zenodo
软件：在所有研究阶段创建和使用的各类软件 Github、GitLab、BitBucket、SourceForge
研究交流 研究组内部交流或与外部交流相关的所有成果，包括交流报告、出版物、会议演示文稿、工作流程、海报、预印本及其他出版物 学术会议、DOAJ

Table 2

Contribution ontology"

贡献本体 贡献者角色 编码格式
CRediT 概念化、数据管理、形式分析、资助获取、调查、方法、项目管理、资源、软件、监督、验证、可视化、撰写初稿、审阅及修订 JATS xml v1.2
SCoRO 调查角色、项目角色、数据角色、写作角色、组织角色 支持RDF/XML、Turtle、N-triple、JSON-LD
CRO 接收角色、咨询角色、作者角色、收集角色、概念化角色、数据角色、发现角色、教育和培训角色、形式分析角色、获取资助角色、资助来源角色、硬件角色、基础设施角色、仪器角色、调查角色、图书馆员角色、营销和沟通角色、方法论角色、修饰角色、患者招募角色、同行评审角色、政策制定角色、主持人角色、保存角色、项目管理角色、资源角色、软件角色、标准开发角色、提交者角色、监督角色、验证角色、可视化角色 RDF

Table 3

Contribution elements system for open research output"

贡献者角色 贡献要素
写作角色 提出研究问题；研究概念设计；文献检索及文献综述；图、表设计制作；研究结果集成；撰写稿件；审核修订稿件；稿件质量保证
数据角色 数据方案设计；数据收集；数据处理；数据建模；数据质量检查；数据标准开发；数据转化；数据验证；形式分析；数据发布；存储管理
实验角色 实验设计；实验调查；实验分析；技术支持
软件角色 需求分析；编写代码；软件架构设计；软件开发；软件项目管理；软件工程；软件测试；撰写技术文档
方法论角色 制定研究指南；创建协议；开发标准化操作程序；设计研究方法
研究管理角色 项目管理；研究协调；研究监督；团队管理；法律法规遵循审查
资源存档角色 纸质资料保存管理；数字化资源保存管理
资助角色 获取资助；资助使用过程管理
资源角色 提供各类资源

Fig.2

Semantic model for identifying academic contribution"

Table 4

Methods of representing academic contributions to research outputs"

项目 表达方式 适用对象 贡献揭示程度 集成能力

署名作者；

署名作者+致谢文本；

署名作者+作者贡献声明

 文字 期刊论文 一般 支持与ORCID等系统集成
贡献矩阵 可视化图形 期刊论文、科学数据集、科学软件 揭示所有贡献者、贡献内容和贡献分值 支持与作者信息系统和其他系统集成

Table 5

Example of contribution matrix representation"

贡献要素

贡献者

 CS MP NAS CBR MC KDH
研究概念设计 ☆ ☆ ☆ ☆ ☆
获取资助 △ ◇
实验设计 ◇ ◇ ◇ ◇
研究方法设计 △ ◇
提供资源 △ ◇
编写代码 △ ◇
撰写稿件 □ ◇ ◇
贡献分值 38% 23% 5% 2% 20% 12%

Table 6

Contributor's contribution elements in the example paper"

贡献者 贡献要素（依据CEediT贡献角色定义）
Anna Prokop-Dorner 概念化，数据管理，形式分析，资助获取，调查，方法，软件，可视化，撰写初稿，稿件审阅及修订
Aleksandra Piłat-Kobla 概念化，数据管理，形式分析，资助获取，调查，方法，软件，可视化，撰写初稿，稿件审阅及修订
Magdalena Ślusarczyk 概念化，数据管理，资助获取，稿件审阅及修订
Maria Świątkiewicz-Mośny 概念化，数据管理，资助获取，项目管理，资源，稿件审阅及修订
Natalia Ożegalska-Łukasik 概念化，数据管理，资助获取，稿件审阅及修订
Aleksandra Potysz-Rzyman 数据管理，稿件审阅及修订
Marianna Zarychta 数据管理，稿件审阅及修订
Albert Juszczyk 数据管理，稿件审阅及修订
Dominika Kondyjowska 数据管理，稿件审阅及修订
Agnieszka Magiera 数据管理，稿件审阅及修订
Małgorzata Maraj 数据管理，稿件审阅及修订
Dawid Storman 数据管理，稿件审阅及修订
Sylwia Warzecha 数据管理，稿件审阅及修订
Paulina Węglarz 数据管理，稿件审阅及修订
Magdalena Wojtaszek-Główka 数据管理，稿件审阅及修订
Wioletta Żabicka 数据管理，稿件审阅及修订
Małgorzata M Bała 概念化，数据管理，形式分析，资助获取，调查，方法，项目管理，资源，软件，监督，稿件审阅及修订

Table 7

Calculation index of contribution degree"

序号 贡献要素 贡献要素中的贡献者人数 贡献程度（Aij ） 贡献权重（Wj ）/%
1 概念化 5 1/5 18.89
2 数据管理 17 1/17 13.48
3 形式分析 3 1/3 6.60
4 资助获取 6 1/6 4.34
5 调查 3 1/3 10.56
6 方法 3 1/3 8.54
7 软件 3 1/3 5.56
8 可视化 2 1/2 4.60
9 资源 2 1/2 5.38
10 监督 1 1 1.11
11 项目管理 2 1/2 2.25
12 撰写初稿 2 1/2 14.49
13 稿件审阅及修订 16 1/16 4.20

Table 8

Contribution representation in the example paper"

序号 贡献者 贡献要素 贡献分值/%
1 Anna Prokop-Dorner 概念化，数据管理，形式分析，资助获取，调查，方法，软件，可视化，撰写初稿，稿件审阅及修订 25.52
2 Aleksandra Piłat-Kobla 概念化，数据管理，形式分析，资助获取，调查，方法，软件，可视化，撰写初稿，稿件审阅及修订 25.52
3 Małgorzata M Bała 概念化，数据管理，形式分析，资助获取，调查，方法，项目管理，资源，软件，监督，稿件审阅及修订 16.92
4 Maria Świątkiewicz-Mośny 概念化，数据管理，资助获取，项目管理，资源，稿件审阅及修订 9.37
5 Magdalena Ślusarczyk 概念化，数据管理，资助获取，稿件审阅及修订 5.56
6 Natalia Ożegalska-Łukasik 概念化，数据管理，资助获取，稿件审阅及修订 5.56
7 Aleksandra Potysz-Rzyman 数据管理，稿件审阅及修订 1.06
8 Marianna Zarychta 数据管理，稿件审阅及修订 1.05
9 Albert Juszczyk 数据管理，稿件审阅及修订 1.05
10 Dominika Kondyjowska 数据管理，稿件审阅及修订 1.05
11 Agnieszka Magiera 数据管理，稿件审阅及修订 1.05
12 Małgorzata Maraj 数据管理，稿件审阅及修订 1.05
13 Dawid Storman 数据管理，稿件审阅及修订 1.05
14 Sylwia Warzecha 数据管理，稿件审阅及修订 1.05
15 Paulina Węglarz 数据管理，稿件审阅及修订 1.05
16 Magdalena Wojtaszek-Główka 数据管理，稿件审阅及修订 1.05
17 Wioletta Żabicka 数据管理，稿件审阅及修订 1.05
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