Frontiers in Big Data, published by Frontiers Media SA in Switzerland, is a leading open access journal that has established itself as a vital resource for scholars and practitioners in the expanding realms of artificial intelligence, computer science, and information systems since its inception in 2018. With an impressive impact factor reflected in its Q2 rankings across multiple categories, including Artificial Intelligence, Computer Science (Miscellaneous), and Information Systems, this journal serves as a pivotal platform for disseminating groundbreaking research and promoting interdisciplinary collaboration. The journal's commitment to open access ensures that high-quality research is readily accessible to a global audience, fostering the exchange of innovative ideas and advancements in big data technologies. By creating an inclusive space for diverse perspectives, Frontiers in Big Data aims to bridge the gap between theoretical research and practical application, making it an essential read for anyone invested in the future of data science.

PeerJ Computer Science is a leading open access journal published by PEERJ INC, dedicated to the field of computer science. Since its inception in 2015, it has made significant strides in promoting scholarly communication and accessibility to cutting-edge research. With an impressive impact factor reflected by a Q1 ranking in the Computer Science (miscellaneous) category and a Scopus rank of 51 out of 232, this journal stands at the forefront of its field. The journal's open access model ensures that groundbreaking findings are readily available to researchers, professionals, and students alike, fostering collaboration and innovation in the ever-evolving landscape of computer science. As it continues to publish until 2024 and beyond, PeerJ Computer Science remains an essential resource for those seeking to stay ahead in their research and practice.

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.

International Journal of Data Science and Analytics, published by SpringerNature, is a leading peer-reviewed journal dedicated to advancing the fields of data science and analytics. Since its inception in 2016, the journal has become an essential platform for researchers, professionals, and students, promoting the exchange of innovative ideas and cutting-edge research. With an impressive categorization in Q2 across multiple domains including Applied Mathematics, Computational Theory and Mathematics, and Information Systems, it demonstrates a notable impact within the academic community, as reflected by its high rankings in various Scopus categories. The journal emphasizes rigorous methodologies and practical applications of data science, making it a valuable resource for those seeking to enhance their understanding and application of data-driven solutions. Although it currently does not operate as an open-access journal, it is committed to disseminating high-quality research that shapes the future of analytics and computation. The journal's headquarters in Switzerland further enriches its international scope, fostering a global dialogue among scholars and practitioners alike.

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.

Computational and Mathematical Methods is a dynamic peer-reviewed journal published by Wiley-Hindawi, focusing on innovative research in the fields of computational mathematics, mechanics, and theory. Since its transition to an Open Access format in 2022, the journal has enhanced its accessibility to researchers and practitioners globally, providing a platform for the dissemination of high-quality studies that contribute to emerging developments in mathematical modeling and computational techniques. Based in the United Kingdom, this journal is committed to fostering collaboration amongst scholars, evidenced by its rankings within Scopus: Q3 in computational mathematics, computational mechanics, and computational theory and mathematics, reflecting its relevance and influence within these critical fields. With an emphasis on interdisciplinary studies, Computational and Mathematical Methods is an essential resource for researchers, professionals, and students seeking to expand their knowledge and apply cutting-edge methodologies to practical challenges.

Statistical Analysis and Data Mining is a leading journal published by WILEY, dedicated to exploring the latest advancements in statistical methods and data mining techniques. With an ISSN of 1932-1864 and an E-ISSN of 1932-1872, this journal serves as a significant platform for researchers and professionals in statistical analysis, computer science applications, and information systems. Covering a wide range of topics from innovative analytical methodologies to emerging data mining algorithms, the journal aims to disseminate high-quality research that contributes to the evolving landscape of data science. Ranked in the Q2 category for the fields of Analysis, Computer Science Applications, and Information Systems in 2023, it emphasizes its relevance and impact within academia. While it offers limited Open Access options, the insights shared in this publication are integral for those wishing to stay ahead in fast-paced research and data-driven industries. Since its inception in 2008 and continuing through 2024, Statistical Analysis and Data Mining invites submissions that reflect rigorous empirical research coupled with practical implications, making it a vital resource for the academic community.

Studies in Informatics and Control is a distinguished academic journal published by the NATL INST R&D INFORMATICS-ICI, specializing in the interdisciplinary fields of Computer Science and Electrical and Electronic Engineering. With an ISSN of 1220-1766 and a recognized standing within its field, this journal aims to foster innovation and disseminate high-quality research findings from 2010 through 2024. It maintains a significant presence in the academic landscape, holding a Q3 ranking in both Computer Science (miscellaneous) and Electrical and Electronic Engineering categories for 2023, which underscores its commitment to advancing knowledge and technology in these areas. While the journal is not open access, it provides valuable insights and results that are essential for researchers, professionals, and students striving to develop their expertise in informatics and control systems. Based in Romania, its contributions traverse international boundaries, appealing to a global audience keen on the latest developments and trends within these rapidly evolving fields.

Japanese Journal of Statistics and Data Science, published by SPRINGERNATURE, is a leading academic journal dedicated to the advancement of statistical methodologies and data science applications, with a focus on fostering innovative research and discourse within the field. Since its inception in 2018, the journal has sought to bridge theory and practice, embracing emerging trends and interdisciplinary approaches that contribute to the ever-evolving landscape of statistics, probability, and computational theory. Hailing from Germany, the journal holds an impressive Q3 ranking in both Computational Theory and Mathematics and Statistics and Probability, reflecting its commitment to high-quality, impactful research. With an accessible ISSN of 2520-8756 and E-ISSN 2520-8764, the journal invites a global audience of researchers, professionals, and students to explore its rich array of articles and findings, all aimed at furthering knowledge and application in the realm of data science.

Big Data Mining and Analytics, published by TSINGHUA UNIVERSITY PRESS, stands at the forefront of interdisciplinary research in the fields of Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, and Information Systems. With an impressive Q1 ranking in multiple categories as of 2023, this journal serves as a critical platform for researchers and professionals eager to explore innovative techniques and methodologies related to big data analytics. Since its transition to Open Access in 2018, Big Data Mining and Analytics has aimed to increase the visibility and accessibility of its cutting-edge research, making permanent strides in the global academic landscape. Housed in Beijing, China, and actively embracing the converged years from 2018 to 2024, the journal aims to cultivate a rich discourse on emerging trends and applications, ensuring its relevance in a rapidly evolving technological environment. Join a vibrant community of scholars dedicated to advancing the frontiers of knowledge in big data.