计算知识管理科学:数智化时代的知识管理研究路径

Computational Knowledge Management Science:The Research Path of Knowledge Management in the Era of Digital Intelligence

[目的/意义]数字化数据激增要求建立新的以复杂性数据和方法为基础的研究范式,构建可计算的研究范式是适应数智化时代知识管理研究的新路径,通过系统性地数字表示和执行可计算知识对象,对于促进知识向实践的应用模式探索意义非凡。[方法/过程]借鉴计算社会科学的发展规律和研究成果,提出构建计算知识管理科学的概念和核心内容。对比计算社会科学研究范式的三大研究方法,提出计算知识管理科学可发展的三大研究方法。[结果/结论]计算知识管理科学是数智化时代知识管理发展的新路径,核心是融合计算机科学技术嫁接“数据—知识—实践—数据”间的桥梁。计算知识管理科学发展依赖数据、算法与算力三位一体驱动,构建可计算的知识管理体系和解释能力是适应未来复杂知识环境的必经之路。计算知识管理科学的研究方法具有融合性、自适性和时效性,动态演变和多维验证是可计算知识管理体系的核心要求。

[Purpose/significance]The proliferation of digital data calls for new research paradigms based on complex data and methodologies.Constructing a new computable research paradigm is a new path for knowledge management research in the era of digital intelligence.The systematic numerical representation and execution of computable knowledge objects is of great significance for facilitating the exploration of patterns of application of knowledge to practice.[Method/process]Drawing on the development law and research results of computational social science,the concept and core content of building computational knowledge management science are proposed.Comparing the three research methods of the computational social science research paradigm,three research methods for the development of computational knowledge management science are proposed.[Result/conclusion]Computational knowledge management science is a new path for the development of knowledge management in the era of digital intelligence.Its core is the bridge between“data-knowledge-practice-data”grafting with computer science and technology.The scientific development of computational knowledge management is driven by the trinity of data,algorithms and computing power.Building a computable knowledge management system and interpretation capability is the only way to adapt to the complex knowledge environment in the future.The research methods of computational knowledge management science are integrated,adaptive and time-sensitive.Dynamic evolution and multi-dimensional verification are the core requirements of computational knowledge management systems.