梳理国内高校科技评价研究现状，针对传统做法普遍存在需耗费大量人力物力进行数据收集和管理效率低等问题，从数据采集和评价方法两个方面分析信息化和数字化转型带来的新机遇，提出基于数据仓库的高校科技活动数据采集概念模型和基于数据挖掘的高校科技评价概念模型，并基于模型的应用需求，从数据的来源和结构多样性、属性间相关性和安全性以及模型选择重要性等方面分析高校科技评价数字化转型面临的挑战，其中数据多样性和安全性以及模型选择是目前面临的主要挑战，以期为高校科技评价提供新的思路和方法。

By sorting out the current situation of domestic university science and technology evaluation research, and aiming at the common problems of traditional methods that require a lot of manpower and material resources for data collection and low management efficiency, it analyzes the new opportunities brought by informatization and digital transformation from two aspects of data collection and evaluation methods. Propose a conceptual model for collecting scientific and technological activity data in colleges and universities based on data warehouse and a conceptual model for scientific and technological evaluation of colleges and universities based on data mining, and based on the model of application requirements, from the data sources and structural diversity, correlation and security as well as the model selection of attribute importance aspects of analysis of university of science and technology evaluation of the challenges facing digital transformation, Among them, data diversity and security as well as model selection are the main challenges we are facing at present, in order to provide new ideas and methods for university science and technology evaluation.

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