地方公共数据政策量化评价研究——基于PMC指数模型

Quantitative Evaluation of Local Public Data Policy——Based on PMC Index Model

[目的/意义]旨在通过对现有地方公共数据政策的量化评价,为后续政策的制定提供参考和借鉴。[方法/过程]本文首先基于25项地方公共数据政策文本,通过ROSTCM6提取高频关键词,在已有评价指标体系的基础上,更细粒度地构建了地方公共数据政策的PMC指数模型。其次对10项政策样本进行量化评价,得出各样本的PMC指数值,并据此绘制PMC曲面图,以更直观地了解各政策样本的优劣情况。[结果/结论]结果显示,地方公共数据政策整体尚可,5项良好,5项可接受,在政策领域、性质、政策部门、内容方面表现较好,需要在政策工具、效力、评价等方面加以改进。

[Purpose/Significance]It aims to provide reference for the formulation of subsequent policies through the quantitative evaluation of existing local public data policies.[Method/Process]Based on 25 local public data policy texts,this paper extracted high-frequency keywords through ROSTCM6,and constructed a PMC index model of local public data policy at a more granular level on the basis of the existing evaluation index system.Secondly,the study obtained the PMC index value of ten policy sample by quantitative evaluation,and drew the PMC surface chart according to better understand the advantages and disadvantages of each policy sample.[Result/Conclusion]The results show that the overall local public data policy is acceptable,5 are good,5 are acceptable,and they perform well in policy areas,nature,policy departments,and content,and need to be improved in terms of policy tools,effectiveness,and evaluation.