The Journal of Data Science is an official journal of the Center for Applied Statistics, School of Statistics, Renmin University of China. It aims to publish high-quality research papers on data science, including statistical learning, machine learning, data mining, and their applications in various fields. The journal encourages submissions that address current hot spots in data science research and promotes reproducibility by requiring authors to provide data and code for their work.
⚡ Speed vs Prestige
How does this journal balance review speed with impact level?
Center for Applied Statistics, School of Statistics, Renmin University of China
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Does the journal have a website?
✓ Linked
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Is the ISSN verified?
1683-8602
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Indexed in a trusted database?
Scopus, DOAJ
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Peer review process documented?
Single-blind
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Follows ethical publishing standards (COPE)?
N/A
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APC fees clearly disclosed?
No APC (Free)
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Not on predatory/blacklists?
✓ Clean
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Long-term digital preservation?
N/A
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Plagiarism detection in place?
No
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Listed in DOAJ (verified OA)?
DOAJ verified
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Primary language documented?
English
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Publication & Citation Trend
Articles published
Times cited
2019
2020
2021
2022
2023
2024
2025
2026
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Computer Science ApplicationsQ3
Statistics and ProbabilityQ3
Subject Classification
Scopus Categories
Computer Science ApplicationsStatistics and Probability
Research Topics (OpenAlex)
Statistical Distribution Estimation and ApplicationsStatistical Methods and InferenceStatistical Methods and Bayesian InferenceAdvanced Statistical Methods and ModelsBayesian Methods and Mixture ModelsProbabilistic and Robust Engineering DesignStatistical Methods in Clinical TrialsFinancial Risk and Volatility ModelingCOVID-19 epidemiological studiesHydrology and Drought Analysis