| 邢文明,胡灵.科学数据开放共享中数据质量治理的演化博弈分析[J].数字图书馆论坛,2026,22(4):11~24 |
| 科学数据开放共享中数据质量治理的演化博弈分析 |
| Evolutionary Game Analysis of Data Quality Governance in the Open Sharing of Scientific Data |
| 投稿时间：2026-02-25 |
| DOI：10.3772/j.issn.1673–2286.2026.04.002 |
| 中文关键词: 科学数据；开放共享；数据质量治理；利益相关者；演化博弈 |
| 英文关键词: Scientific Data; Open and Shared; Data Quality Governance; Stakeholders; Evolutionary Game |
| 基金项目:本研究得到国家社会科学基金一般项目“我国科学数据中心国际影响力评价及提升研究”（编号：23BTQ061）资助。 |
| 作者 | 单位 | | 邢文明 | 湘潭大学公共管理学院 | | 胡灵 | 湘潭大学公共管理学院 |
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| 中文摘要: |
| 本研究针对科学数据开放共享中的数据质量问题，探究科学数据质量治理中多元主体行为策略选择及其演化规律，进而提出促进多方参与科学数据质量治理的优化策略。基于演化博弈理论，构建数据生产者、数据使用者、数据处理者和数据监管者四方博弈模型，分析各主体在不同情境中的策略选择及关键因素对系统演化的影响。研究结果表明：数据生产者的感知收益对数据生产者和数据处理者具有差异化影响；数据使用者的反馈成本存在最优区间；数据处理者对数据生产者与数据使用者的奖励效果存在阈值，超过一定限度反而抑制主体积极策略行为；数据监管者严格监管的初始意愿能加速系统收敛，但随着其他主体积极性提高，监管边际收益递减，系统最终向宽松监管方向演化。据此，本研究提出完善科研成果评价、健全科学数据管理机制、优化数据基础治理环境、打造多主体治理联盟等策略来提升科学数据质量。 |
| 英文摘要: |
| This study focus on the data quality problem in the open sharing of scientific data, investigating the strategic behavior choices and evolutionary dynamics of multiple stakeholders involved in scientific data quality governance, and subsequently proposes optimization strategies to enhance multi-party engagement. Based on the evolutionary game theory, this paper constructed a four-player game model of data producers, data users, data processors and data regulators, and analyzed the influence of strategy choices and key factors on system evolution in different scenarios. The findings indicate that：the perceived benefits of data producers have differentiated effects on data producers and data processors; there is an optimal range for the feedback costs of data users; the incentive effect of data processors on data producers and users has a threshold, and exceeding a certain limit instead suppresses proactive strategies; the initial willingness of data regulators to enforce strict supervision can accelerate system convergence, but as the activity of other stakeholders increases, the marginal benefit of supervision decreases, and the system ultimately evolves toward relaxed regulation. Accordingly, this paper proposes strategies such as refining the evaluation mechanism of scientific research outcomes, strengthening the scientific data management frameworks, optimizing the data foundational governance environment, and building a multi-stakeholder governance alliance to improve the quality of scientific data. |
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