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Academic Journal

International Journal of Intelligent Systems and Data Science

ISSN: 3143-2328 Building robust, ethical, and scalable data-driven and intelligent systems requires an integrated approach that recognizes the close interdependence between data, analytics, computing infrastructure, and decision-making processes. Advances in data science, machine learning, and information systems increasingly influence decision-making across science, industry, governance, and society, making it essential to address not only technical performance but also reliability, transparency, and long-term sustainability. This includes developing methods that are resilient to data uncertainty, bias, and distributional shifts, as well as designing systems that can adapt to evolving real-world conditions. Achieving meaningful progress in data science and intelligent systems demands attention to foundational challenges such as data quality, model interpretability, computational efficiency, system scalability, and responsible deployment. Equally important are broader structural considerations, including access to data and computational resources, skills development, data governance, privacy, and the societal implications of data-driven technologies. Addressing these challenges requires collaboration across disciplines, combining theoretical advances with applied research and empirical validation. The International Journal of Intelligent Systems and Data Science (IJISDS) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from data science, analytics, information systems, machine learning, decision support systems, cloud and distributed computing, and allied domains to deepen understanding of how data-driven and intelligent systems can be designed, evaluated, optimized, and applied responsibly. IJISDS supports research that bridges theory and practice, encouraging contributions that demonstrate both methodological rigor and real-world relevance. Through its editorial standards and publishing practices, IJISDS actively promotes reproducibility, ethical responsibility, and transparent peer review. The journal also seeks to contribute to broader global priorities by supporting research aligned with sustainable development, digital innovation, responsible data practices, and trustworthy analytics, recognizing the critical role that data science and intelligent systems play in shaping resilient and equitable futures.

ISSN2589-0042
Publishing modelOpen Access
Latest IssueAug 26, Vol. 1, Issue 4
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Journal Updates

Call for Papers – International Journal of Intelligent Systems and Data Science (IJISDS)

The International Journal of Intelligent Systems and Data Science (IJISDS) invites submissions for its inaugural issues from researchers and practitioners working across data science, intelligent information systems, analytics, and data-driven computing.

IJISDS welcomes original research articles, comprehensive review papers, case studies, and applied or practice-oriented studies that present substantive contributions to theory, methodology, systems, or real-world implementation. Submissions may include, but are not limited to:

  • Novel methods, frameworks, or systems for data science, analytics, and intelligent information systems
  • Methodological advances in statistical learning, predictive modeling, data mining, and knowledge discovery
  • Research on decision support systems, recommender systems, expert systems, and information systems
  • Empirical studies supported by rigorous experimentation, observational data, or real-world datasets
  • Applied machine learning research addressing practical analytical or decision-making challenges
  • Research on cloud computing, distributed computing, edge computing, big data technologies, and system optimization
  • Internet of Things (IoT), cyber-physical systems, and data-intensive computing applications
  • Research addressing data governance, data privacy, explainable analytics, and responsible data-driven systems
  • Applied studies demonstrating the deployment, evaluation, or impact of data-driven systems in practical settings
  • Interdisciplinary work where data, analytics, or computational systems play a central analytical or decision-support role
  • Critical reviews, systematic reviews, and meta-analyses that synthesize and evaluate developments within the journal's scope

The journal encourages submissions that emphasize technical soundness, methodological clarity, reproducibility, and real-world relevance, while clearly articulating their contribution to existing knowledge, systems, or practice.

Contributions from both academic and industry contexts are welcome, provided they meet scholarly standards and offer verifiable insights.

Submission Status: Open
Review Model: Double-blind peer review
Publication Model: Open Access