面向数据科学的情报学学科研究方法及学科教育内容设计

Research Methods and Discipline Education Content Design of Intelligence Studies Oriented for Data Science

大数据技术和数据科学为现代情报学的学科体系设计和学科特色回归提供了必要性和可能性。从人们对数据科学的认知和社会对数据科学类人才的需求角度来看,现代情报学也需要积极探索新时期的新发展方向。文章结合大量文献整理和理论分析,对比分析了情报学与数据科学的区别和联系,重点从学科研究方法和学科教育内容两个角度探索了相关的学科建设思路。数据科学在情报学教育目标的重定位、教育内容的重设计和人才培养的新要求等多个角度可以为现代情报学学科发展提供有益的改革方向参考,不仅有助于改变传统情报学学科固有的一些陈旧内容和方法,而且有助于情报学更好地适应新时期包括国家战略层面和社会应用层面的多方面现实需求。文章系统地从学科对比分析的角度,认为在明确情报学研究对象和研究目标的情况下,数据科学可以成为现代情报学学科发展的重要助力和研究方向。

The continuous development of big data technology and Data Science provides the necessity and possibility for the discipline system design and discipline characteristic regression of modern Intelligence Studies.From the perspective of cognition of Data Science and social requirement for Data Science occupation,modern Intelligence Studies needs to actively explore new development direction in the new era.Based on a large number of literature review and theoretical analysis,this paper compares and analyzes the differences and relations between Intelligence Studies and Data Science,and explores the related discipline construction ideas from two aspects of discipline research methods and discipline education.Data Science can provide beneficial reform direction reference for the development of modern Intelligence Studies,including the re-orientation of education goal,re-design of education content and new requirements of personnel training.It not only helps to change some old contents and methods inherent in traditional Intelligence Studies,but also helps Intelligence Studies better adapt to various practical needs in the new era,including national strategic level and social application level.From the perspective of comparative analysis of disciplines,this paper believes that Data Science can become an important basis and development direction of modern Intelligence Studies transformation under the condition of clear research object and research goal of Intelligence Studies.