Annals of Data Science is a scholarly journal focusing on Big Data analytics and applications. Publishes a broad range of research findings, experimental results, and case studies in data science. Promotes interdisciplinary techniques, including statistics, artificial intelligence, and optimization for Big Data processing and data mining. Encourages application of knowledge derived from Big Data in real-life scenarios such as finance, healthcare, climate changes, etc. Focuses on heterogeneous data analysis, data modeling, and data mining
⚡ Speed vs Prestige
How does this journal balance review speed with impact level?
Springer Science and Business Media Deutschland GmbH
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Does the journal have a website?
✓ Linked
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Is the ISSN verified?
2198-5812
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Indexed in a trusted database?
Scopus
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Peer review process documented?
N/A
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Follows ethical publishing standards (COPE)?
N/A
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APC fees clearly disclosed?
N/A
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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?
N/A
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Listed in DOAJ (verified OA)?
N/A
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Primary language documented?
N/A
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.
Business, Management and Accounting (miscellaneous)Q1
Artificial IntelligenceQ2
Computer Science ApplicationsQ2
Statistics, Probability and UncertaintyQ2
Subject Classification
Scopus Categories
Statistics, Probability and UncertaintyComputer Science ApplicationsArtificial IntelligenceBusiness, Management and Accounting (miscellaneous)
Research Topics (OpenAlex)
Statistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignStatistical Methods and Bayesian InferenceAdvanced Statistical Methods and ModelsFinancial Risk and Volatility ModelingHydrology and Drought AnalysisBayesian Methods and Mixture ModelsStatistical Methods and InferenceReliability and Maintenance OptimizationStock Market Forecasting Methods