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.

數據科學 噸 他現場以驚人的速度在前進。 每天都會發表新的科學文章。 作為一名學生，我嘗試與最新的科學文獻保持同步。 在此博客文章中，我創建了一份科學期刊列表，我相信每位數據科學家都應遵循。 期刊的排列順序不分先后。

國際數據科學與分析雜志 (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.

該期刊歡迎有關數據科學和高級分析的實驗和理論發現，以及它們在現實生活中的應用。

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.

名單上的第一本科學期刊是《國際數據科學與分析期刊(JDSA)》。 這并不奇怪，因為這是第一本數據科學和分析科學期刊。 主編是澳大利亞悉尼科技大學的 曹龍兵 。

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].

該期刊包含來自數據科學許多子領域的文章，主要側重于機器學習和大數據。 它匯集了思想領袖，研究人員，行業從業人員以及數據科學和分析的潛在用戶，以開發該領域，討論新趨勢和機遇，交流思想和實踐并促進跨學科和跨領域的合作[ 1 ]。

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

鏈接到最新版本： 2020年10月，第10卷，第4期

數據挖掘與知識發現 (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.

該領域的主要技術出版物“數據挖掘和知識發現”是收集相關通用方法和技術的資源，也是統一各種組成研究社區的論壇。

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.

數據挖掘和知識發現期刊創建于1997年，現已發展成為該領域最具影響力的期刊之一[ 2 ]。 目前的主編是達姆施塔特技術大學的 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].

該期刊發表有關數據挖掘和知識發現的研究與實踐，重要領域和技術的調查和教程以及重要應用的詳細說明[ 3 ]的原始技術論文。

Link to a recent edition: Issue 4, July 2020

鏈接到最新版本： 2020年7月第4期

IEEE知識與數據工程學報 (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是每月出版的一份歸檔期刊，旨在為研究人員，開發人員，管理人員，戰略規劃人員，用戶以及對知識和數據工程領域的最新活動和實踐活動感興趣的其他人員提供信息。

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.

電氣和電子工程師協會(IEEE)在電氣和電子工程和計算機科學領域的著作占全球的30％以上，出版了100多種經過同行評審的期刊和雜志； 它還贊助了1800多個會議和活動[ 4 ]。 IEEE知識與工程事務(TKDE)專注于知識與數據工程[ 5 ]。 編輯總司令該雜志是學敏林來自新南威爾士大學 。

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].

為了反映知識和數據工程研究和開發實踐的當前趨勢， TKDE優先考慮新興主題的提交，包括但不限于大數據和應用以及知識和數據工程的新領域，例如社交網絡，社交媒體，以及眾包[ 6 ]。

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

鏈接到最新出版物： 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…

人工智能雜志(AIJ) 歡迎有關AI廣泛方面的論文，這些方面構成了整個領域的進步，包括但不限于認知和AI，自動推理和推理，基于案例的推理，常識性推理，計算機視覺，約束處理，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 Link?ping University and Sylvie Thiébaux from the Australian National University.

人工智能始于1970年，現已成為該領域當前研究成果發表的公認的主要國際論壇[ 7 ]。 主編是林雪平大學的 Patrick Doherty和澳大利亞國立大學的 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.

除常規論文外，該期刊還接受研究筆記，研究領域評論，立場論文和書評。 有時，該雜志還會發布針對特定主題的特別版本。

Link to a recent publication: Volume 287, October 2020

鏈接到最新出版物： 2020年第287卷

大數據 (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.

《大數據雜志》發表了高質量的學術研究論文，方法論和案例研究，涵蓋了從大數據分析到數據密集型計算以及大數據研究的所有應用的廣泛主題。

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.

《大數據雜志》是一種開放式期刊 ，可以在其網站上免費獲取論文。 該期刊偶爾會發表高度創新的文章[ 8 ]。 該雜志的主編是佛羅里達大西洋大學的 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].

該期刊探討了當今和未來大數據所面臨的挑戰，包括但不限于：數據捕獲和存儲； 搜索，共享和分析； 大數據技術； 數據可視化； 大規模并行處理的架構； 數據挖掘工具和技術； 大數據的機器學習算法； 云計算平臺； 分布式文件系統和數據庫； 和可擴展的存儲系統[ 8 ]。

Link to articles: website

鏈接到文章： 網站

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.

這些是我建議遵循的五種期刊。 數據科學領域還有許多期刊。 我從未希望此列表成為科學數據科學出版物的全面概述。 該博客文章僅討論期刊，但是有更多方法可以與科學界保持同步。 如果您知道其他重要的科學研究資源，請隨時在評論中發布它們。