[目的/意义] 在大数据浪潮和“新文科”背景下，中国图情档学科的人才培养范式亟需改革。与此同时，大数据相关专业的建设方兴未艾，对于图情档学科的人才培养新范式建设具有借鉴意义。[方法/过程] 采用一种时序主题网络模型及计算方法；通过搜集、处理、统计、分析259所高等院校的大数据专业培养方案文本，在时间维度上进行主题挖掘，总结归纳数据科学课程的层次；分析图情档学科主干知识与大数据专业的联系，并给出适合图情档学科的数据科学课程建议。[结果/结论] 结果表明，所采用的时序主题网络模型方法能够较好地契合大数据专业的人才培养范式发展分析，可以成为研究学科主题的一种方法。此外，还给出面向图情档学科的数据科学类课程建议，可供图情档学科的人才培养参考。
[Purpose/significance] Under the background of the big data tide and the new liberal arts, there is an urgent need to reform and innovate the talent training mode of library and information science in China. The construction of the big data subjects is in the ascendant, which has a strong reference significance for the construction of a new paradigm of talent cultivation in library and information science. [Method/process] This paper innovatively proposed a new sequential topic network model and the calculation method. By collecting, processing, counting and analyzing the talent cultivation policies of the big data subjects in 259 universities, this paper conducted topic mining in the time dimension and summarized the levels of data science courses. Additionally, this paper analyzed the relevance between the subjects of the big data and the main knowledge of library and information science, and put forward suggestions for data science courses suitable for library and information science. [Result/conclusion] The sequential topic network model can better fit the analysis of talent cultivation paradigm development in the big data subjects, and it may also be a way to research the topic of a subject. Finally, this paper puts forward some suggestions for the courses of data science which is oriented to library and information science, and there is certain reference value for the development of talent cultivation in library and information science.
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