企业高质量数据集建构:内涵特征、逻辑框架与未来展望OACHSSCD

Analyzing the connotation,characteristics and logical framework of enterprise high-quality dataset con-struction is essential to unlocking data value and enabling firms'digital-intelligent transformation.This paper concep-tualises enterprise high-quality datasets,identifies six core attributes,establishes a three-dimensional framework(val-ue,scenario,technology)based on socio-technical systems theory to provide theoretical support for the construction of high-quality corporate datasets under the"AI Plus"background;subsequently,from the analytical perspectives of the data value chain and data life cycle theories,it constructs a five-dimensional model encompassing scenario demand perception,data resource weaving,knowledge resource extraction,data-knowledge integration and refinement,and a digital-intelligence service ecosystem;finally,in response to the practical dilemmas currently faced by enterprises,the study proposes targeted optimization strategies,suggesting that future efforts should focus synergistically on data sce-nario shaping,data aggregation and governance,data labeling optimization,and data security assurance to overcome the bottlenecks of high-quality dataset construction,enhance the value-enabling efficiency of data elements,and pro-vide robust support for the digital-intelligence transformation and high-quality development of enterprises.