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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.

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About the Journal

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.

Current Issue

Vol. 1 No. 5 (2026)

This issue presents a diverse collection of research addressing emerging challenges across artificial intelligence, information security, cloud computing, blockchain, healthcare, education, smart transportation, energy transition, and enterprise technologies. The featured studies explore blockchain-enabled research integrity, reputation quantification, neuroevolutionary autonomous systems, AI-driven medical diagnosis, privacy-preserving machine learning, immersive photovoltaic adoption, cloud performance, SaaS customization, supply-chain analytics, computational thinking assessment, wireless security, reproducible computing, configuration management, product authenticity, precision industrial synchronization, decentralized asset exchange, and bias-aware natural language processing. Together, these contributions highlight innovative computational approaches, practical deployment frameworks, and interdisciplinary solutions for advancing intelligent, secure, and scalable digital ecosystems.

Published: 2026-09-25

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