数据科学与管理(英文)(Data Science and Management)(可官网投稿)

《数据科学与管理(英文)》(Data Science and Management)(季刊),杂志于2021年创办,经新闻出版总署批准的正规刊物,2023年获批CN刊号,系教育部主管、西安交通大学主办,西安交通大学管理学院、数学学院与期刊中心共同承办的开放获取英文学术期刊。DSM旨在推动数据科学研究及其在商业、工程、社会管理等领域的应用,聚焦数据科学与管理科学交叉领域,突出运用数据科学理论方法,解决数字化、网络化、智能化发展中的管理难题和经济社会转型发展中的关键问题。

本刊特点:AMI入库国际刊(2022-2026版),外文期刊,

数据科学与管理(英文)(Data Science and Management)

期刊基本信息

出版周期:季刊 级别:国级期刊
主管部门:教育部
主办单位:西安交通大学
编辑部:《数据科学与管理(英文)》编辑部
中国国内刊号:CN61-1530/TN
国际标准刊号:ISSN 2666-7649

杂志社联系方式

地址:陕西西安中国西部科技创新港1号巨构2108《数据科学与管理(英文)》编辑部
邮编:710049
电话:029-88968307
官方微信公众号:数据科学与管理DSM
官网邮箱:dsm@xjtu.edu.cn
官方网站:http://www.keaipublishing.com/en/journals/data-science-and-management/

杂志征稿投稿要求

《数据科学与管理(英文)》期刊简介

【微信公众号信息】

Data Science and Management(《数据科学与管理(英文)》,DSM)是一本由西安交通大学主办,西安交通大学管理学院与期刊中心共同承办的开放获取英文学术期刊。期刊旨在推动数据科学研究及其在商业、工程、社会管理等领域的应用,聚焦数据科学与管理科学交叉领域,突出运用数据科学理论方法,解决数字化、网络化、智能化发展中的管理难题和经济社会转型发展中的关键问题。期刊由徐宗本院士担任主编,已入选FMS管理科学高质量国际期刊推荐列表,并已被Scopus、DOAJ数据库收录。

期刊主页:

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

投稿网址:

https://www.editorialmanager.com/dsm/default1.aspx

《数据科学与管理(英文)》作者指南

(Data Science and Management)

【杂志社官方网站信息】

Guide for Authors

INTRODUCTION

Types of paper

Contributions falling into the following categories will be considered for publication: full length articles, original research papers, review articles, short communications, technical notes, editorials, book reviews, case reports, feature articles.

Please ensure that you select the appropriate article type from the list of options when making your submission. Authors contributing to special issues should ensure that they select the special issue article type from this list. Types of article

The Journal publishes Research Papers, Short Communications and Graphical Reviews. We support the "Your Paper Your Way" Elsevier guideline which allows authors to submit their main manuscript file without any formatting requirements.

Research Papers are not limited in size. However, we do strongly recommend to authors to be as succinct as possible in the best interest of the readers and the dissemination of the work. Short Communications should not contain more than 2 Figures and no more than 4000 words, double-spaced, Arial font, size 11.

Graphical Reviews (GRs) are a short, structured article type, which primarily use illustrative schematic summaries to convey only key concepts and novel ideas on a major research interest in the lab. GRs present an opportunity to succinctly showcase your research contributions within a wider overview of recent developments within a field. GRs are designed to communicate information in a visually appealing representation of the current state of research on a specific topic. The overall message should be accessible to a broad scientific audience. GRs have a format of 3-5 (color) schemes/figures, ideally formatted as easily downloadable (PowerPoint) slides or the like, for use by readers for educational purposes. The text body should provide the reader with 'backbone' information and context, connecting the material presented in the figures. GRs cannot include unpublished data, new hypotheses, formal mathematical models, or meta-analysis. GR article structure:

Abstract: up to 250 words

Body (exclusive of figure legends): up to 2000 words, double-spaced, Arial font, size 11

3-5 color schemes/figures summarizing the state of the specific topic covered. Each figure needs to be self-explanatory, including sufficient annotations to allow the readers to quickly grasp the content of the figure.

Figure legends must be straight to the point, providing additional details which deepen the message of the figure itself. Please ensure that the reader, who may not be a direct expert in the field, can easily grasp the information provided.

References: no more than 25 key articles that exemplify the most significant recent advances in the field.

Illustrations: Authors are expected to use their own illustration resources. They may also make use of Elsevier's https://webshop.elsevier.com/illustration-servicesIllustration Services to ensure the best presentation of their images, in accordance with all technical requirements.

An example of a GR is available https://media.journals.elsevier.com/content/files/gr-example-final-31053420.pdfhere

BEFORE YOU BEGIN

Ethics in publishing

Please see our information on Ethics in publishing.

Declaration of interest

All authors must disclose any financial and personal relationships with other people or organizations that could inappropriately influence (bias) their work. Examples of potential competing interests include employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and grants or other funding. Authors must disclose any interests in two places: 1. A summary declaration of interest statement in the title page file (if double anonymized) or the manuscript file (if single anonymized). If there are no interests to declare then please state this: 'Declarations of interest: none'. 2. Detailed disclosures as part of a separate Declaration of Interest form, which forms part of the journal's official records. It is important for potential interests to be declared in both places and that the information matches. More information.

Submission declaration and verification

Submission of an article implies that the work described has not been published previously (except in the form of an abstract, a published lecture or academic thesis, see 'Multiple, redundant or concurrent publication' for more information), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder. To verify originality, your article may be checked by the originality detection service Crossref Similarity Check.

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更多详情:

http://www.keaipublishing.com/en/journals/data-science-and-management/guide-for-authors/

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