Foundations of Data Science
Published by American Institute of Mathematical Sciences
eISSN : 2639-8001
Abbreviation : Found. Data Sci.
Aims & Scope
Foundations of Data Science (FoDS) invites submissions focusing on advances in mathematical, statistical, and computational methods for data science.
Results should significantly advance current understanding of data science, by algorithm development, analysis, and/or computational implementation which demonstrates behavior and applicability of the algorithm.
Fields covered by the journal include, but are not limited to Bayesian Statistics, High Performance Computing, Inverse Problems, Data Assimilation, Machine Learning, Optimization, Topological Data Analysis, Spatial Statistics, Nonparametric Statistics, Uncertainty Quantification, and Data Centric Engineering.
View Aims & ScopeMetrics & Ranking
Journal Rank
| Year | Value |
|---|---|
| 2024 | 12310 |
Journal Citation Indicator
| Year | Value |
|---|---|
| 2024 | 108 |
SJR (SCImago Journal Rank)
| Year | Value |
|---|---|
| 2024 | 0.464 |
Quartile
| Year | Value |
|---|---|
| 2024 | Q2 |
h-index
| Year | Value |
|---|---|
| 2024 | 13 |
Impact Factor
| Year | Value |
|---|---|
| 2024 | 1.70 |
Impact Factor Trend
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, designed to support cutting-edge academic discovery.