基于声誉理论的开放科学数据质量提升激励机制研究

Research on Incentive Mechanism of Open Science Data Quality Improvement Based on Reputation Theory

[目的/意义]针对科学数据开放中的数据质量问题,设计开放科学数据质量提升激励机制,以促进科研人员开放高质量科学数据并积极参与科学数据开放共享活动。[方法/过程]借鉴声誉理论构建博弈模型,提出科学数据质量提升激励机制,利用百度文库对激励机制进行验证。[结果/结论]基于声誉理论建立科学数据质量提升激励机制需满足4个条件,即博弈是多次重复的、良好的声誉可为科研人员带来利益、科学数据主管机构能及时发现开放低质量科学数据的行为并予以惩罚、完备的声誉传播渠道,并提出相应措施。

[Purpose/Significance] Aiming at the data quality problem in the opening of scientific data, an incentive mechanism for improving the quality of open scientific data is designed to encourage researchers to open up high-quality scientific data and actively participate in the open sharing of scientific data. [Method/Process] Drawing on reputation theory to build a game model, it proposed an incentive mechanism to improve the quality of scientific data, and introduced Baidu Wenku as a verification of the incentive mechanism. [Result/Conclusion] The establishment of an incentive mechanism for scientific data quality improvement based on reputation theory needs to meet four conditions, namely, the game is repeated many times, a good reputation can bring benefits to researchers, scientific data authorities can timely discover and punish open low-quality scientific data and complete reputation dissemination channels, and it puts forward corresponding measures on this basis.