Information Systems

Aims & Scope

Information systems are the software and hardware systems that support data-intensive applications.

The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems.

Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science.

Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome.

Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome.

All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.4

SJR (SCImago Journal Rank)

Year	Value
2024	0.885

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	100

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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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 rise of “big data” on cloud computing: Review and open research issues

  Citation: 1894

  Authors: Ibrahim Abaker Targio, Ibrar, Nor Badrul, Salimah, Abdullah, Samee

• Time-series clustering – A decade review

  Citation: 1402

  Authors: Saeed, Ali, Teh

• Automated analysis of feature models 20 years later: A literature review

  Citation: 887

  Authors: David, Sergio, Antonio

• YAWL: yet another workflow language

  Citation: 881

  Authors: W.M.P., A.H.M.

• Conformance checking of processes based on monitoring real behavior

  Citation: 776

  Authors: A., W.M.P.

• Rock: A robust clustering algorithm for categorical attributes

  Citation: 612

  Authors: Sudipto, Rajeev, Kyuseok

• Cure: an efficient clustering algorithm for large databases

  Citation: 536

  Authors: Sudipto, Rajeev, Kyuseok

• Business process mining: An industrial application

  Citation: 528

  Authors: W.M.P., H.A., A.J.M.M., B.F., A.K., M., H.M.W.

• Efficient mining of association rules using closed itemset lattices

  Citation: 497

  Authors: Nicolas, Yves, Rafik, Lotfi

• A review of topic modeling methods

  Citation: 495

  Authors: Ike, Sathish A.P.

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