Article Processing Timeline
2–6 Days
Typical initial quality and plagiarism check
21–30 Days
Typical peer-review period
45–60 Days
Typical overall processing time
Processing times are indicative and may vary depending on manuscript
type, editorial assessment, reviewer availability, revision requirements,
ethical or technical checks, author response times, and production
requirements.
About the Journal
Overview
The Journal of AI, Data Science, and Cyber Systems is an international, peer-reviewed, open-access journal covering research at the intersection of artificial intelligence, data science, computing, cybersecurity, and cyber-enabled systems. The journal provides a platform for researchers, academics, engineers, and industry professionals to communicate research findings in intelligent computing, data-driven methodologies, and secure digital systems.
The journal welcomes theoretical, methodological, computational, and application-oriented research involving artificial intelligence, machine learning, data analytics, cloud and edge computing, cyber-physical systems, cybersecurity, privacy, distributed systems, and related computing technologies.
The journal also welcomes interdisciplinary research applying AI, data science, and cyber technologies across healthcare, finance, manufacturing, transportation, smart infrastructure, environmental systems, agriculture, social sciences, business, and other relevant domains. Research addressing security, privacy, ethics, explainability, robustness, trustworthiness, and responsible deployment of intelligent systems is also within the journal's scope.
The Journal of AI, Data Science, and Cyber Systems welcomes original research articles, review articles, short communications, technical perspectives, case studies, methodological contributions, and other scholarly submissions appropriate to its scope. Manuscripts are considered in accordance with the journal's editorial policies, ethical requirements, author guidelines, and peer-review procedures.
The journal is committed to responsible scholarly communication, research integrity, transparent editorial practices, accurate publication metadata, and responsible dissemination of research in artificial intelligence, data science, cybersecurity, and related computing fields.
Aim and Scope
The Journal of AI, Data Science, and Cyber Systems is an international, peer-reviewed, open-access journal covering research in artificial intelligence, data science, computing infrastructures, cybersecurity, and cyber-enabled systems. The journal welcomes theoretical, methodological, computational, and application-oriented research involving intelligent algorithms, data-driven methods, secure computing, and interdisciplinary applications.
The journal encourages research that integrates computer science, engineering, information systems, mathematics, and relevant application domains, including studies addressing ethical, explainable, privacy-aware, secure, and trustworthy use of intelligent technologies.
Submissions are welcomed across a broad range of areas, including but not limited to:
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
- Interdisciplinary science, technology, and knowledge systems
- Technology-driven research addressing societal and industrial challenges
The journal welcomes research that combines methods, theories, datasets, technologies, or perspectives from multiple disciplines where such integration is relevant to the research question.
Editorial and Peer-Review Policy
Journal of AI, Data Science and Cyber Systems
follows the editorial and peer-review procedures described in the
journal's policies and author guidelines. Manuscripts are assessed
for relevance to the journal's scope, originality, scientific merit,
methodological considerations, ethical compliance, and suitability
for publication.
Key features include:
-
Manuscripts are evaluated by appropriate reviewers and/or editors
with relevant subject expertise, according to the journal's
stated peer-review model.
-
The applicable peer-review model and reviewer confidentiality
arrangements are described in the journal's policies.
-
Editorial assessment considers scientific relevance, originality,
methodological quality, ethical compliance, and alignment with
the journal's scope.
-
Manuscripts undergo appropriate originality, plagiarism, and
research-integrity checks before or during the editorial process.
-
Final publication decisions are made by the responsible editor
in accordance with the journal's editorial policies and the
outcome of the applicable review process.
Publication Frequency & Format
The journal's publication frequency is
Annual (One issue per year).
Accepted articles are made available online in HTML and PDF formats
following completion of the applicable editorial and production processes,
supporting accessible and timely dissemination of published research.
Open Access Policy
Journal of AI, Data Science and Cyber Systems
operates under an open-access publishing model. Published content is
freely accessible to readers without subscription or paywall
restrictions, subject to the applicable journal policies and licensing
terms.
Copyright, licensing, and reuse rights are governed by the terms
specified for the journal and individual published content.
Indexing & Archiving
The Journal of AI, Data Science and Cyber Systems
seeks to make its published research discoverable through appropriate
scholarly indexing, abstracting, and discovery services. Inclusion in
any external indexing or abstracting service is subject to the
eligibility requirements, evaluation procedures, and acceptance
decisions of the respective service.
The journal is committed to maintaining accurate article metadata,
persistent identifiers, accessible article landing pages, and the
continued availability of published scholarly content.
Information about indexing, abstracting, discovery, and preservation
services is provided on a service-specific basis and is updated when
the relevant status has been established and verified.
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 that informed consent is obtained where required and protect the confidentiality and privacy of participants and research subjects.
- 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.
Abstract
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