About the Journal
Overview
The Journal of AI, Data Science, and Cyber Systems is an international, peer-reviewed journal that serves as a comprehensive platform for research at the intersection of artificial intelligence, data science, and cyber-enabled systems. It addresses the increasing demand for intelligent, secure, and scalable computing solutions in modern data-driven and interconnected environments.
Rapid advancements in artificial intelligence, big data technologies, cloud and edge computing, and cyber-physical systems are transforming sectors such as healthcare, finance, manufacturing, transportation, and smart infrastructure. These developments create significant opportunities for innovation while also introducing critical challenges related to security, privacy, ethics, trustworthiness, and system control.
The journal welcomes both theoretical and application-oriented research contributions, including the development of novel algorithms, models, architectures, and frameworks, as well as real-world implementations of AI and data science techniques in cyber systems. It promotes interdisciplinary research that integrates computer science, engineering, information systems, and diverse application domains, with a focus on intelligent automation, digital transformation, and cyber resilience.
Particular emphasis is placed on responsible and trustworthy AI, encouraging research that advances fairness, transparency, robustness, and ethical deployment of intelligent systems. The journal aims to attract high-quality contributions from academia, industry, and research institutions, publishing original research articles, reviews, and perspectives that contribute to the advancement of next-generation intelligent and secure systems.
Aim and Scope
The Journal of AI, Data Science, and Cyber Systems is an international, peer-reviewed, open-access journal that publishes high-quality research on intelligent algorithms, data-driven methodologies, and secure cyber-enabled systems. It focuses on the integration of artificial intelligence, machine learning, data analytics, computing infrastructures, and cybersecurity, covering both theoretical advancements and practical implementations aimed at building scalable, reliable, and resilient digital systems. The journal encourages interdisciplinary research across computer science, engineering, and application domains, with a strong emphasis on ethical, explainable, and trustworthy AI.
Artificial Intelligence & Intelligent Systems
- Artificial intelligence, machine learning, and deep learning methodologies
- Generative AI, foundation models, and large-scale intelligent systems
- Natural language processing and human-computer interaction
- Computer vision and multimedia intelligence systems
- Knowledge representation, reasoning, and decision-making systems
- Explainable, ethical, and trustworthy AI
Data Science & Advanced Analytics
- Data science, big data analytics, and data mining techniques
- Predictive analytics and intelligent decision support systems
- Statistical modeling and probabilistic computing methods
- Data engineering, integration, and data management systems
- Data visualization and high-dimensional data interpretation
Cyber Systems & Security
- Cybersecurity, privacy, and secure communication technologies
- Cyber-physical systems and intelligent networked environments
- Blockchain technologies and decentralized systems
- Adversarial machine learning and secure AI systems
- Distributed, resilient, and fault-tolerant cyber infrastructures
Computing Technologies & Digital Infrastructure
- Cloud computing, edge computing, and fog computing paradigms
- High-performance, parallel, and distributed computing systems
- Internet of Things (IoT) and smart interconnected systems
- Real-time systems and embedded intelligent technologies
- Computational modeling, simulation, and optimization techniques
Engineering & Applied Scientific Systems
- Interdisciplinary engineering and advanced technological systems
- Civil, mechanical, electrical, and chemical engineering applications
- Mathematics and algorithmic foundations of intelligent systems
- Applied sciences integrated with AI and computational methods
- Physics, chemistry, and material sciences in computational contexts
- Earth sciences, environmental systems, and sustainability studies
- Agriculture and ecological systems supported by intelligent technologies
- Astronomy, astrophysics, and space-related computational research
Life Sciences & Healthcare Technologies
- Medical sciences and AI-enabled healthcare systems
- Bioinformatics, biotechnology, and computational biology
- Clinical data analysis and intelligent diagnostic systems
- Public health analytics and epidemiological modeling
- Digital health systems and precision medicine
Social Sciences, Humanities & Knowledge Systems
- Economics, finance, and business analytics
- Business management, public relations, and organizational systems
- Management science and decision-making frameworks
- Social sciences and interdisciplinary societal studies
- Psychology and behavioral data analysis
- Political science, governance, and policy systems
- Education and intelligent learning technologies
- History and archaeological research
- Philosophy and knowledge systems
- Language, linguistics, and communication studies
- Literature and cultural analysis
- Library and information science
Creative Systems & Human-Centered Technologies
- Architecture and smart built environments
- Arts, music, and creative digital systems
- Painting, photography, and visual communication
- Recreation, entertainment, and sports analytics
- Human-centered computing and user experience design
Multidisciplinary & Integrative Research
- Multidisciplinary and cross-domain research contributions
- Integration of AI, data science, and cyber systems across domains
- Science and knowledge systems in general
- Technology-driven solutions for societal and industrial challenges
Editorial and Peer-Review Policy
Journal of AI, Data Science and Cyber Systems adheres to a strict single-blind peer-review process to maintain the quality, integrity,
and scientific validity of all published work.
Key features include:
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Each manuscript is reviewed by independent experts in the relevant field, along with oversight from an academic editor.
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Reviewers can see author details, but the identities of the reviewers remain hidden from the authors.
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The evaluations emphasize scientific merit, originality, methodological rigor, ethical
compliance, and how well the work fits within the journal's scope.
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Every submission goes through plagiarism checks and ethical compliance assessments
before the review process begins.
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The final decision on publication is based on the reviewer's recommendations and the
editor's evaluation.
Publication Frequency & Format
This journal comes out Bi-Annual (Two issues per year). Accepted articles are
made available online in both HTML and PDF formats, ensuring that scholarly work is accessible
and disseminated promptly.
Open Access Policy
Journal of AI, Data Science and Cyber Systems operates under a fully open access model. This means all published content is freely
accessible to readers around the globe, without any subscription or paywall. Authors maintain
the copyright to their work, and the content is shared under an appropriate open-access license.
Indexing & Archiving
Journal of AI, Data Science and Cyber Systems is dedicated to upholding high standards with the goal of being included in reputable
scientific indexing and abstracting services. The journal also ensures long-term digital
preservation through recognized archives and repositories, guaranteeing permanent access and
discoverability.
Manuscript Submission
Authors are encouraged to submit their manuscripts through the journal's Online Submission
System (Submit Manuscript).
Manuscripts must adhere to the journal's author guidelines regarding structure, formatting,
referencing style, ethical approvals, and necessary disclosures (such as conflicts of interest
and funding).
Publication Ethics & Integrity
Journal of AI, Data Science and Cyber Systems follows internationally recognized standards for publication ethics and research integrity,
which include (but are not limited to):
- Make sure you have ethical approval.
- Ensure informed consent and guarantee confidentiality.
- Declare any conflicts of interest.
- Be transparent about data availability.
- Clarify authorship criteria and the roles of contributors.
- Conduct anti-plagiarism checks.
- Have a clear policy for retraction and correction.
