The field of data science is advancing at an incredible pace. New scientific articles are published daily. As a student, I try to stay up-to-date with the scientific literature that is published. In this blog post, I created a list of scientific journals that I believe every data scientist should follow. The journals are presented in no particular order.

数据科学 吨 他现场以惊人的速度在前进。 每天都会发表新的科学文章。 作为一名学生，我尝试与最新的科学文献保持同步。 在此博客文章中，我创建了一份科学期刊列表，我相信每位数据科学家都应遵循。 期刊的排列顺序不分先后。

国际数据科学与分析杂志 (International Journal of Data Science and Analytics)

The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations.

该期刊欢迎有关数据科学和高级分析的实验和理论发现，以及它们在现实生活中的应用。

The first scientific journal on the list is the International Journal of Data Science and Analytics (JDSA). This is no surprise since this was the first scientific journal in data science and analytics. The editor-in-chief is Longbing Cao from the University of Technology in Sydney, Australia.

名单上的第一本科学期刊是《国际数据科学与分析期刊(JDSA)》。 这并不奇怪，因为这是第一本数据科学和分析科学期刊。 主编是澳大利亚悉尼科技大学的 曹龙兵 。

The journal contains articles from many subdomains in data science mostly focussing on machine learning and big data. It brings together thought leaders, researchers, industry practitioners, and potential users of data science and analytics, to develop the field, discuss new trends and opportunities, exchange ideas and practices, and promote transdisciplinary and cross-domain collaborations [1].

该期刊包含来自数据科学许多子领域的文章，主要侧重于机器学习和大数据。 它汇集了思想领袖，研究人员，行业从业人员以及数据科学和分析的潜在用户，以开发该领域，讨论新趋势和机遇，交流思想和实践并促进跨学科和跨领域的合作[ 1 ]。

Link to a recent edition: Volume 10, issue 4, October 2020

链接到最新版本： 2020年10月，第10卷，第4期

数据挖掘与知识发现 (Data Mining and Knowledge Discovery)

The premier technical publication in the field, Data Mining and Knowledge Discovery is a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities.

该领域的主要技术出版物“数据挖掘和知识发现”是收集相关通用方法和技术的资源，也是统一各种组成研究社区的论坛。

The Data Mining and Knowledge Discovery journal was founded in 1997 and has grown to one of the most influential journals in the field [2]. The current editor-in-chief is Johannes Fürnkranz from the Technical University of Darmstadt.

数据挖掘和知识发现期刊创建于1997年，现已发展成为该领域最具影响力的期刊之一[ 2 ]。 目前的主编是达姆施塔特技术大学的 JohannesFürnkranz 。

The journal publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications [3].

该期刊发表有关数据挖掘和知识发现的研究与实践，重要领域和技术的调查和教程以及重要应用的详细说明[ 3 ]的原始技术论文。

Link to a recent edition: Issue 4, July 2020

链接到最新版本： 2020年7月第4期

IEEE知识与数据工程学报 (IEEE Transactions on Knowledge and Data Engineering)

TKDE is an archival journal published monthly designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area.

TKDE是每月出版的一份归档期刊，旨在为研究人员，开发人员，管理人员，战略规划人员，用户以及对知识和数据工程领域的最新活动和实践活动感兴趣的其他人员提供信息。

The Institute of Electrical and Electronics Engineers (IEEE) produces over 30% of the world’s literature in the electrical and electronics engineering and computer science fields, publishing well over 100 peer-reviewed journals and magazines; it also sponsors over 1800 conferences and events [4]. The IEEE Transactions on Knowledge and Engineering (TKDE) focusses on knowledge and data engineering [5]. The editor-in-chief of the journal is Xuemin Lin from the University of New South Wales.

电气和电子工程师协会(IEEE)在电气和电子工程和计算机科学领域的著作占全球的30％以上，出版了100多种经过同行评审的期刊和杂志； 它还赞助了1800多个会议和活动[ 4 ]。 IEEE知识与工程事务(TKDE)专注于知识与数据工程[ 5 ]。 编辑总司令该杂志是学敏林来自新南威尔士大学 。

To reflect the current trends in knowledge and data engineering research and development practice, TKDE gives priority to submissions on emerging topics, including but not limited to big data and applications, and new frontiers of knowledge and data engineering, such as social networks, social media, and crowdsourcing [6].

为了反映知识和数据工程研究和开发实践的当前趋势， TKDE优先考虑新兴主题的提交，包括但不限于大数据和应用以及知识和数据工程的新领域，例如社交网络，社交媒体，以及众包[ 6 ]。

Link to a recent publication: Volume 32, Issue 9, September 2020

链接到最新出版物： 2020年9月，第32卷，第9期

人工智能 (Artificial Intelligence)

The journal of Artificial Intelligence (AIJ) welcomes papers on broad aspects of AI that constitute advances in the overall field including, but not limited to, cognition and AI, automated reasoning and inference, case-based reasoning, commonsense reasoning, computer vision, constraint processing, ethical…

人工智能杂志(AIJ) 欢迎有关AI广泛方面的论文，这些方面构成了整个领域的进步，包括但不限于认知和AI，自动推理和推理，基于案例的推理，常识性推理，计算机视觉，约束处理，道德...

Artificial Intelligence, which commenced publication in 1970, is now the generally accepted premier international forum for the publication of results of current research in this field [7]. The editors-in-chief are Patrick Doherty from the Linköping University and Sylvie Thiébaux from the Australian National University.

人工智能始于1970年，现已成为该领域当前研究成果发表的公认的主要国际论坛[ 7 ]。 主编是林雪平大学的 Patrick Doherty和澳大利亚国立大学的 SylvieThiébaux 。

Apart from regular papers, the journal also accepts research notes, research field reviews, position papers, and book reviews. Occasionally, the journal also publishes special editions that are focused on a particular topic.

除常规论文外，该期刊还接受研究笔记，研究领域评论，立场论文和书评。 有时，该杂志还会发布针对特定主题的特别版本。

Link to a recent publication: Volume 287, October 2020

链接到最新出版物： 2020年第287卷

大数据 (Big Data)

The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research.

《大数据杂志》发表了高质量的学术研究论文，方法论和案例研究，涵盖了从大数据分析到数据密集型计算以及大数据研究的所有应用的广泛主题。

The Journal of Big Data is an open-access journal whose papers van be accessed for free on their website. The journal occasionally publishes highly innovative articles [8]. The editors-in-chief of the journal are Borko Furth and Taghi Khoshgoftaar from the Florida Atlantic University.

《大数据杂志》是一种开放式期刊 ，可以在其网站上免费获取论文。 该期刊偶尔会发表高度创新的文章[ 8 ]。 该杂志的主编是佛罗里达大西洋大学的 Borko Furth和Taghi Khoshgoftaar 。

The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems [8].

该期刊探讨了当今和未来大数据所面临的挑战，包括但不限于：数据捕获和存储； 搜索，共享和分析； 大数据技术； 数据可视化； 大规模并行处理的架构； 数据挖掘工具和技术； 大数据的机器学习算法； 云计算平台； 分布式文件系统和数据库； 和可扩展的存储系统[ 8 ]。

Link to articles: website

链接到文章： 网站

These are the five journals that I would recommend to follow. There are many more journals in the field of data science. I never intended this list to be a comprehensive overview of scientific data science publications. This blog post only discusses journals, but there are more ways to stay up-to-date with the scientific community. If you know other great sources for scientific studies, feel free to post them in the comments.

这些是我建议遵循的五种期刊。 数据科学领域还有许多期刊。 我从未希望此列表成为科学数据科学出版物的全面概述。 该博客文章仅讨论期刊，但是有更多方法可以与科学界保持同步。 如果您知道其他重要的科学研究资源，请随时在评论中发布它们。