1、该刊只有国际刊号。

2、投稿方式：在线投稿。

3、官网网址：

https://www.keaipublishing.com/en/journals/data-science-and-informetrics/

https://www.sciencedirect.com/journal/data-science-and-informetrics

4、投稿系统：https://www.editorialmanager.com/dsim

5、主办单位官网：https://casee.hdu.edu.cn/main.htm

（杭州电子科技大学）

6、官网邮箱：dsi@hdu.edu.cn

7、官网电话：0571-86873823

8、出刊日期：季刊，逢季末月出版。

2026年1月29日星期四

《数据科学与信息计量学（英文）》期刊简介

（Data Science and Informetrics）

《数据科学与信息计量学》(DSI)是由中国科学与科学政策科学学会、杭州电子科技大学和清华大学互联网产业研究院联合主办的旗舰期刊，其刊载的文章促进了对数据科学与信息计量学的实证、理论和方法论理解。期刊致力于发表原创的同行评审的研究，跨越数据科学和信息计量领域的所有子领域和学科以及所有层次的分析。我们努力把期刊打造成为数据科学和信息度量领域的专家和学者交流的学术社区。DSI欢迎高质量的作品，反映广泛的视角、主题、背景和方法，包括跨学科和多学科的研究。

Online ISSN: 2694-6106

Print ISSN: 2694-6114

《数据科学与信息计量学（英文）》投稿指南

【官网信息】

Guide for Authors

About the journal

Aims and scope

The contents of Volume 1 to Volume 3 can be found here ( https://dsi.hdu.edu.cn/issues.aspx?ClassID=3)

Data Science and Informetrics (DSI) covers the trends, scientific foundations, techniques and applications of the field. The journal publishes research papers, technical reports subject reviews, short comments and book reviews, providing a platform for data scientists, computer scientists, industry practitioners, and potential users of data science and analytics.

Topics covered include but are not limited to:

• Theory and mathematical foundations for data science and informetrics.

• Data analytics, knowledge discovery, machine learning, and deep learning, and intelligent processing of various data (including text, image, video, graph and network).

• Big data architecture, infrastructure, computing, matching, indexing, query processing, mapping, search, retrieval, interopera­bility, exchange and recommendation.

• Data science applications, intelligent services in scientific, business, governmental, cultural, behavioral, social and economic, health and medical, human, natural and artificial (including online/Web, cloud, IoT, mobile and social media) domains.

• Ethics, quality, privacy, safety and security, trust and risk on data science and big data.

• The convergence of bibliometrics, scientometrics, webometrics, altmetrics, informetrics and data science.

• Informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, network science and data science.

……

更多详情：

https://www.keaipublishing.com/en/journals/data-science-and-informetrics/guide-for-authors/