Aims & Scope
Information Sciences will publish original, innovative and creative research results.
A smaller number of timely tutorial and surveying contributions will be published from time to time.
The journal is designed to serve researchers, developers, managers, strategic planners, graduate students and others interested in state-of-the art research activities in information, knowledge engineering and intelligent systems.
Readers are assumed to have a common interest in information science, but with diverse backgrounds in fields such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioural sciences and biochemistry.
The journal publishes high-quality, refereed articles.
It emphasizes a balanced coverage of both theory and practice.
It fully acknowledges and vividly promotes a breadth of the discipline of Informations Sciences.
View Aims & ScopeMetrics & Ranking
Impact Factor
| Year | Value |
|---|---|
| 2025 | 6.8 |
SJR (SCImago Journal Rank)
| Year | Value |
|---|---|
| 2024 | 1.803 |
Quartile
| Year | Value |
|---|---|
| 2024 | Q1 |
h-index
| Year | Value |
|---|---|
| 2024 | 243 |
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, Decision Sciences, Engineering and Mathematics, designed to support cutting-edge academic discovery.
Most Cited Articles
The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.
-
The concept of a linguistic variable and its application to approximate reasoning—I
Citation: 11119
Authors: L.A.
-
The concept of a linguistic variable and its application to approximate reasoning-III
Citation: 2462
Authors: L.A.
-
The concept of a linguistic variable and its application to approximate reasoning—II
Citation: 2355
Authors: L.A.
-
Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
Citation: 2194
Authors: C.L., Chun-Yang
-
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
Citation: 1855
Authors: Salvador, Alberto, Julián, Francisco
-
Teaching–Learning-Based Optimization: An optimization method for continuous non-linear large scale problems
Citation: 1506
Authors: R.V., V.J., D.P.