DATA MINING AND KNOWLEDGE DISCOVERY, published by Springer, stands as a premier journal within the realms of Computer Networks and Communications, Computer Science Applications, and Information Systems. With an impressive impact factor and a notable presence in various rankings—achieving the Q1 category in 2023—we invite researchers, professionals, and students alike to explore cutting-edge methodologies and innovative applications in data mining. Established in 1997 and continuing its journey through to 2024, the journal not only contributes significantly to the advancement of knowledge in computational techniques but also fosters an understanding of the complex interrelations in data systems. Though not an open access publication, it offers a wealth of insights crucial for driving advancements in technology and analytics. Based in Dordrecht, Netherlands, the journal remains dedicated to disseminating high-quality research and is essential reading for anyone engaged in the ever-evolving field of data science.

ACM Transactions on Intelligent Systems and Technology, published by the Association for Computing Machinery (ACM), is a leading peer-reviewed journal dedicated to the rapid dissemination of innovative research in the fields of Artificial Intelligence and Theoretical Computer Science. With an impressive Impact Factor and a strong H-Index, it boasts a premier standing in the academic community, being ranked Q1 in both AI and Theoretical Computer Science categories as of 2023. This journal serves as a critical platform for researchers, professionals, and students aiming to contribute to and stay informed about the latest developments in intelligent systems and technology. While there are currently no open-access options, readers can explore invaluable insights into current trends and methodologies from 2010 to 2024, making it an essential resource for anyone passionate about advancing their knowledge in these rapidly evolving domains. The journal continues to foster collaboration and innovation, reflecting the forefront of research where technology intersects with intelligent systems.

Data Technologies and Applications is a leading academic journal published by Emerald Group Publishing Ltd, captivating the interest of researchers, professionals, and students alike within the dynamic fields of Information Systems and Library and Information Sciences. With its ISSN 2514-9288 and E-ISSN 2514-9318, this journal holds a commendable Q2 ranking in Library and Information Sciences and a Q3 ranking in Information Systems as of 2023, reflecting its impact and contribution to ongoing discourse in these disciplines. Operating with an open access model, it provides a platform for accessing high-quality research that encompasses innovative methodologies and applications of data technologies. The journal's scope includes interdisciplinary studies that leverage data to enhance decision-making, improve information retrieval, and foster technological convergence. Housed in the United Kingdom, the journal facilitated its first publication in 2018, with a commitment to fostering valuable academic conversations through to 2024 and beyond. Engage with insightful research that shapes the future of data technologies and applications, making this journal an essential resource for anyone invested in the advancement of knowledge in these pivotal fields.

Intelligent Data Analysis is a highly regarded journal published by IOS Press, specializing in the fields of Artificial Intelligence, Computer Vision, and Pattern Recognition. With its ISSN 1088-467X and E-ISSN 1571-4128, the journal has been a cornerstone of scholarly communication since its inception in 1997, serving as a vital resource for researchers, professionals, and students engaged in advancing methodologies and applications in intelligent data analysis. The journal maintains its significance with impressive Scopus ranks, indicating its notable position within the academic community. Although currently not an Open Access journal, Intelligent Data Analysis offers a wealth of insights and findings, encouraging collaboration and knowledge exchange among its readership. With an impact factor reflective of its rigorous selection processes, the journal traverses a broad range of topics, contributing to ongoing discussions and innovations in its field. As the journal looks toward shaping future research until 2024 and beyond, it remains a pivotal platform for disseminating cutting-edge research and fostering academic inquiry.

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, published by Springer Singapore Pte Ltd, is a pivotal platform in the rapidly evolving realms of computer science and technology. With an ISSN of 1000-9000 and an E-ISSN of 1860-4749, this journal encompasses a diverse array of topics including computational theory, hardware and architecture, software engineering, and applications of computer science. Spanning over three decades from 1986 to 2024, it boasts an impressive standing within academic circles, ranking in the Q2 quartile across several key categories and achieving notable placement in Scopus metrics. Although this journal operates under a subscription-based model, it remains a crucial resource for researchers, professionals, and students seeking to advance their knowledge and contribute to discussions in computer science. The JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY is committed to fostering innovation and scholarly communication in the field, encouraging submissions that contribute substantive advancements in theory and application.

Journal of Big Data, published by SPRINGERNATURE, is a leading academic journal dedicated to advancing the understanding and application of big data technologies and methodologies across various domains. Since its inception in 2014, this Open Access journal has gained recognition for its rigorous peer-reviewed research, boasting impressive rankings in multiple categories in Scopus, including Q1 in Computer Networks and Communications and Q1 in Information Systems. With its impactful contributions, the journal is positioned at the forefront of scholarly work on big data, addressing critical topics such as data analytics, storage, visualization, and applied data science. Its global reach and commitment to disseminating knowledge ensure that researchers, professionals, and students have equitable access to groundbreaking findings that empower advancements in technology and information systems. The Journal of Big Data continues to foster collaboration and inspire new research avenues leading to tangible impacts in the field.

International Journal of Data Warehousing and Mining, published by IGI Global, is a vital resource in the field of data management and analytics, catering to researchers, professionals, and students alike. With ISSN 1548-3924 and E-ISSN 1548-3932, this journal has been at the forefront of disseminating pioneering research since its inception in 2005 and will continue to do so through 2024. Despite its current categorization in the Q4 quartile for Hardware and Architecture as well as Software, and its Scopus rankings, the journal aims to foster innovation within the domains of data warehousing, data mining, and their applications across various sectors. The absence of an open access option does not diminish its significance; rather, it ensures that the journal maintains rigorous peer-review standards, providing high-quality research outputs that contribute to ongoing discussions and advancements within the field. Researchers and practitioners looking to stay updated on the latest trends and methodologies will find the International Journal of Data Warehousing and Mining an indispensable tool in their academic and professional endeavors.

Big Data Research, published by Elsevier, is a leading academic journal dedicated to the exploration and advancement of Big Data methodologies and technologies. With an ISSN of 2214-5796, and a commendable impact reflected in its Scopus rankings—ranking Q2 in Computer Science Applications and Q1 in Information Systems—this journal offers a prominent platform for researchers and practitioners to share innovative findings in the realm of data science, analytics, and management. Since its inception in 2014, Big Data Research has fostered a multidisciplinary approach, addressing cutting-edge topics crucial for both academic inquiry and real-world applications. The journal's objectives include advancing the understanding of data-intensive systems, promoting essential methodologies for big data analytics, and enhancing data-driven decision-making processes across various industries. As an open access journal, Big Data Research is committed to disseminating knowledge widely, allowing researchers, professionals, and students to stay at the forefront of developments in this fast-evolving field. Its influence in the academic community is further underscored by a strong commitment to quality and relevance, making it an essential resource for anyone interested in the transformative power of big data.

The Journal of Experimental & Theoretical Artificial Intelligence, published by Taylor & Francis Ltd, serves as a premier platform for researchers and professionals interested in advancing the fields of artificial intelligence, software engineering, and theoretical computer science. Established in 1989, this peer-reviewed journal features original research and comprehensive reviews that explore innovative methodologies and emerging trends within these dynamic domains. With an impact factor that reflects its relevance, the journal currently ranks in Q3 across its categories, affirming its contributions to the scholarly community. The journal's commitment to quality and rigor invites submissions that bridge experimental and theoretical frameworks, thus fostering a deeper understanding of AI's applications and implications. Researchers and students can access insightful articles that drive critical discussions and inspire future work, making this journal an essential resource for anyone looking to delve into the complexities of artificial intelligence and its surrounding disciplines.

Data Science and Engineering is a premier open access journal published by SPRINGERNATURE, dedicated to advancing the fields of data science, artificial intelligence, computational mechanics, and information systems. Since its inception in 2016, this journal has rapidly established itself as a leader in the academic community, boasting an impressive Q1 ranking in multiple computer science categories, including Artificial Intelligence, Software, and Information Systems. With a commitment to disseminating high-quality research, it caters to a diverse audience of researchers, professionals, and students eager to explore the intersection of data and technology. The journal's robust global reach, combined with its respected reputation, empowers authors to share their findings widely, facilitating breakthroughs and innovations across the digital landscape. Join the vibrant community of scholars contributing to this integral field of study, and stay informed with the latest research by accessing the journal freely online.