期刊档案 · Mathematics-Computational Mathematics
Data Science in Science
ISSN 2694-1899 · Taylor & Francis Group · United Kingdom
Data Science in Science 完全开放获取，APC 约 1,500 美元，近 24 个月 56 篇文章投稿到接收中位 227 天，官网公布录用率 21%，2025 年发文 26 篇，Scopus 收录。
研究范围
研究范围与定位
Data Science in Science 由 Taylor & Francis Group 出版。按 OpenAlex 近年发文统计，该刊主要发表 Statistical Methods and Inference、Gaussian Processes and Bayesian Inference、Statistical Methods and Bayesian Inference 等主题的论文，这 3 个主题约占 22.9%，主导子领域为 Statistics and Probability。（根据 OpenAlex 主题统计与中科院分区数据生成）
Data Science in Science is an open access, international journal publishing original research and reviews at the intersection of Science and Data Science. Its aim is to advance: new ideas for experimental and observational data-driven learning and discovery that help address fundamental questions at the frontiers of Science and scientific inference; quantification and summarization of uncertainty from data-driven theories and complex Data Science models, algorithms, and workflows; and new practices for scientific reproducibility and replicability enabled through Data Science. It promotes the intrinsically multidisciplinary nature of the field of Data Science and seeks explicitly science-driven advances in Data Science, and their novel, significant, or transformative applications to Science. It fosters dedicated collaboration and convergence between the broadly defined fields of Science and Data Science through: (i) deep domain, (ii) broader inter-domain, and (iii) trans-domain collaborative research. It encourages collective scientific learning through new collaborative and scientific methods and theories that have the potential to inform the knowledge among and strengthen the data practices of domain and data scientists. Original research articles should encompass scientific and Data Science concepts, techniques, or computational methods and tools for addressing scientific problems in a way that is novel or beyond that of traditional disciplinary research. Review articles should highlight important and timely applications of Data Science within a scientific discipline or insightful applications across disciplines, with comprehensive discussion of any application, specific considerations, or assumptions. Special issues dedicated to relevant and timely special topics will also be of interest. Proposals should be emailed to the Editor-in-Chief for consideration in the first instance. Peer Review Policy All submitted manuscripts are subject to initial appraisal by the Editors. If found suitable for further consideration, papers are subject to peer review by independent, anonymous expert referees. All peer review is double anonymized and submissions can be made online on Submission Portal. Publishing Ethics The Journal adheres to the highest standards of publishing ethics, with rigorous processes in place to ensure this is achieved. Taylor & Francis is a member of the Committee of Publications Ethics (COPE) and utilizes CrossCheck for all Journals. More inform
摘自期刊官网 Aims & Scope
研究方向（LetPub）：Mathematics-Computational Mathematics
主要研究主题 OpenAlex 近年发文统计，占比为近似值
- Statistical Methods and InferenceMathematics9.2%
- Gaussian Processes and Bayesian InferenceComputer Science7.3%
- Statistical Methods and Bayesian InferenceMathematics6.4%
- Neural Networks and ApplicationsComputer Science6.4%
- Financial Risk and Volatility ModelingEconomics, Econometrics and Finance5.5%
- Advanced Causal Inference TechniquesMathematics4.6%
- Complex Systems and Time Series AnalysisEconomics, Econometrics and Finance4.6%
- Forecasting Techniques and ApplicationsDecision Sciences4.6%
分区与收录
学科分区与数据库收录
中科院期刊分区表
期刊分区表（ 2025年3月升级版）未收录
该期刊未被此版本分区表收录。
《新锐期刊分区表》（ 2026年3月发布）未收录
该期刊未被此版本分区表收录。
期刊分区表（ 2023年12月旧的升级版）未收录
该期刊未被此版本分区表收录。
CiteScore 分区（Scopus，2026 年 6 月版）
| 学科 | 分区 | 排名 | 百分位 |
|---|---|---|---|
| Computational Mathematics | Q4 | 161/212 | — |
| Statistics and Probability | Q4 | 243/303 | — |
Scopus 按 CiteScore 在每个学科内为期刊排名，百分位 75 及以上为 Q1，每 25 为一档；与中科院分区是不同体系。LetPub
数据库收录
ScopusDOAJLetPub
国际期刊预警名单：各版本均未列入LetPub
期刊官网自述收录
Portico出版商官网
期刊官网列出的收录清单，未与各数据库逐一核对；Web of Science 各子库以上方记录为准。
不同版本、大类与小类分别展示，不将不同评价口径合并为一个分区值；投稿与考核前请确认所在机构采用的版本。
指标
影响力指标与发文规模
影响力指标
- CiteScore 2026-06
- 1.1LetPub ·
- CiteScore（出版商公布） 2025
- 1.1出版商官网 ·
- SJR 2026-06
- 0.22LetPub ·
- SJR（出版商公布） 2025
- 0.22出版商官网 ·
- SNIP 2026-06
- 0.36LetPub ·
- SNIP（出版商公布） 2025
- 0.36出版商官网 ·
- h-index
- 7OpenAlex ·
- i10-index
- 3OpenAlex ·
- 两年平均被引
- 1.18OpenAlex ·
- Gold OA 文章占比
- 0%LetPub ·
发文规模
- 年发文量（出版商公布）
- 2,023出版商官网 ·
- 年下载量（出版商公布）
- 32,000出版商官网 ·
逐年发文量 OpenAlex 统计 · 累计 87 篇 · 当年数据不完整
| 年份 | 发文量 | 其中 OA | 被引 |
|---|---|---|---|
| 2026 | 27 | 27 | 70 |
| 2025 | 26 | 26 | 40 |
| 2024 | 14 | 14 | 36 |
| 2023 | 14 | 14 | 16 |
| 2022 | 6 | 6 | 4 |
| 2021 | 0 | 0 | 1 |
不同来源的统计口径与观测时间不同，页面保留各来源原值；“出版商公布”为期刊官网自述数据。
审稿与录用
审稿周期与录用情况
文章统计的审稿周期 Crossref 登记的稿件日期 · 至
227 天投稿到接收中位数 · P25–P75 180 天 – 313 天
- 接收到上线
- 中位数 27 天（56 篇）
- 投稿到上线
- 中位数 259 天
- 样本
- 56 篇有投稿与接收日期的文章（窗口内共 59 篇），最近一篇接收于
只统计最终被录用并发表的文章，不含被拒稿件的处理时间，因此通常长于出版商公布的"首次决定时间"。
其他来源
- 平均审稿速度（社区反馈）
- 10 WeeksLetPub ·
- 录用率（出版商公布）
- 21%出版商官网 ·
- 投稿到首次决定
- 85 天出版商官网 ·
- 外审后首次决定
- 124 天出版商官网 ·
- 接收到发表
- 31 天出版商官网 ·
- 投稿到发表（期刊自报）
- 约 10 周DOAJ ·
- 评审方式
- 单盲同行评审DOAJ
社区反馈来自投稿者样本，置信度 0.5，不代表期刊承诺；“出版商公布”的时间节点定义以官网为准。
费用与开放获取
版面费与开放获取政策
完全开放获取DOAJ
所有文章开放获取，通常向作者收取文章处理费（APC）。
| 来源 | 文章处理费 | 费用减免 | 许可证 | 观测时间 |
|---|---|---|---|---|
| DOAJ | USD 1,500 | 有 | CC BY、CC BY-NC | |
| LetPub | USD 1,500 | 有 | — | |
| 出版商官网 | USD 1,680 / GBP 1,344 / EUR 1,615 / AUD 2,340 | — | — |
- APC 费用说明 ↗DOAJ
- 费用减免政策 ↗DOAJ
- 开放获取声明 ↗DOAJ
- 许可与版权 ↗DOAJ
费用以期刊官网为准；不同来源的观测时间可能不同，页面保留各来源原值，不做平均。
投稿要求
文章类型与投稿政策（官网）
投稿准备要点1 项，摘自作者指南
- 摘要
- ≤ 200 词
接收的文章类型4 种，含篇幅限制
- book reviewResearch Article Should be written with the following elements in the following order: title page; abstract; keywords; main text introduction, materials and met…正文 ≤ 200 词 · 摘要 ≤ 200 词
- data noteResearch Article Should be written with the following elements in the following order: title page; abstract; keywords; main text introduction, materials and met…正文 ≤ 200 词 · 摘要 ≤ 200 词
- research articleResearch Article Should be written with the following elements in the following order: title page; abstract; keywords; main text introduction, materials and met…未说明篇幅
- reviewResearch Article Should be written with the following elements in the following order: title page; abstract; keywords; main text introduction, materials and met…正文 ≤ 200 词 · 摘要 ≤ 200 词
官网政策摘录数据可用性、出版伦理、许可与版权、开放获取、同行评审
- 数据可用性 Data Sharing Policy
Taylor & Francis Basic Data Sharing Policy 模型摘要
This journal applies the Taylor & Francis Basic Data Sharing Policy. Authors are encouraged to share or make open the data supporting the results or analyses presented in their paper where this does not violate the protection of human subjects or other valid privacy or security concerns. Authors are encouraged to deposit the dataset(s) in a recognized data repository that can mint a persistent dig…
原文 ↗出版商官网 ·- 出版伦理
Publishing Ethics: adheres to highest standards; Taylor & Francis is COPE member and uses CrossCheck. 模型摘要
The Journal adheres to the highest standards of publishing ethics, with rigorous processes in place to ensure this is achieved. Taylor & Francis is a member of the Committee of Publications Ethics (COPE) and utilizes CrossCheck for all Journals.
原文 ↗出版商官网 ·- 许可与版权 Copyright Options
Copyright allows you to protect your original material, and stop others from using your work without your permission. Taylor & Francis offers a number of different license and reuse options, including Creative Commons licenses when publishing open access. Read more on publishing agreements.
原文 ↗出版商官网 ·- 开放获取 Open access
Overview Open journals Open Select Dove Medical Press F1000Research
原文 ↗出版商官网 ·- 同行评审 Peer Review and Ethics
Double anonymous peer review 模型摘要
Taylor & Francis is committed to peer-review integrity and upholding the highest standards of review. Once your paper has been assessed for suitability by the editor, it will then be double anonymous peer reviewed by two independent, anonymous expert. If you have shared an earlier version of your Author’s Original Manuscript on a preprint server, please be aware that anonymity cannot be guaranteed…
原文 ↗出版商官网 ·
摘录来自期刊官网页面，仅保留原文片段；“模型摘要”由 Workers AI 生成并经原文校验，以官网为准。
基本信息
出版信息与官方入口
- 出版商
- Taylor & Francis Group
- 出版国家或地区
- United Kingdom
- 出版语言
- English
- ISSN
- 2694-1899
- 学会 / 主办单位
- American Statistical Association
- 官网最新一期
- Volume 5, Issue 1（2026 年）
- 官方链接
- 期刊主页 ↗LetPub
- 投稿系统 ↗出版商官网
- 作者指南 ↗LetPub
- Aims & Scope ↗LetPub
- 专刊 / 特刊征稿 ↗出版商官网
- APC 费用说明 ↗DOAJ
- 费用减免政策 ↗DOAJ
- 开放获取声明 ↗DOAJ
- 许可与版权 ↗DOAJ
- 评审流程 ↗LetPub
- 编委会 ↗LetPub
- 查重政策 ↗DOAJ
常见问题
关于 Data Science in Science 的常见问题
Data Science in Science 的审稿周期多长？
按 2024年10月至2026年10月（近 24 个月）56 篇已发表文章登记的日期，投稿到接收的中位数为 227 天（四分位 180–313 天）；投稿社区反馈的平均审稿速度为约 10 周；期刊官网公布的录用率为 21%。文章统计只含被录用的稿件，出版商数据口径以官网为准，社区反馈来自投稿者样本，均不代表期刊承诺。
Data Science in Science 被哪些数据库收录？
据 LetPub 与 DOAJ 记录，Data Science in Science 被 Scopus、DOAJ 收录。
Data Science in Science 是开放获取期刊吗？版面费多少？
Data Science in Science 为完全开放获取。APC 约 1,500 美元。
来源与更新
本页事实来自 LetPub、出版商官网、DOAJ、OpenAlex；每个数字旁标注来源与观测日期，冲突数据保留各来源原值。LetPub 原始详情页：查看 ↗（2026-08-25 归档）。最近更新：。