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.

EXPERT SYSTEMS is a prestigious journal published by WILEY, dedicated to advancing the fields of Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering, and Theoretical Computer Science. Established in 1984, this journal has consistently provided a platform for rigorous research, showcasing innovative methodologies and applications that drive the future of intelligent systems. With an impressive impact factor and Scopus rankings placing it among the top quartiles within its categories, EXPERT SYSTEMS is a vital resource for researchers, professionals, and students seeking to deepen their understanding of complex systems and their applications. The journal is not currently an Open Access publication, emphasizing its commitment to high-quality, peer-reviewed research that impacts the global academic community. With a convergence year extending to 2024, it prepares to continue its legacy as a cornerstone of knowledge in these dynamic fields.

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.

SIAM Journal on Mathematics of Data Science is an esteemed publication within the fields of applied mathematics and data science, published by SIAM PUBLICATIONS. This journal serves as a vital platform for researchers and practitioners, dedicated to disseminating high-quality research that addresses complex mathematical problems arising in the context of data science. The journal aims to bridge the gap between rigorous mathematical theory and practical applications, fostering interdisciplinary collaboration among mathematicians, data scientists, and statisticians. With its commitment to excellence, the SIAM Journal on Mathematics of Data Science contributes significantly to advancing the understanding and development of mathematical methodologies that analyze and interpret large datasets effectively. Researchers and professionals will find it an invaluable resource with its comprehensive articles, insightful reviews, and original research papers, which represent the forefront of innovative mathematical approaches in the evolving landscape of data science. For those interested in contributing to this dynamic field, the journal provides an array of access options tailored to diverse audiences.

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.

Data is an innovative open-access journal published by MDPI, dedicated to advancing research and knowledge in the fields of Computer Science and Information Systems. Since its inception in 2016, Data has positioned itself as a prominent platform for disseminating high-quality research, currently boasting an impact factor reflective of its rigorous peer-review process and academic standards. Situated in Switzerland, the journal encompasses a broad scope of topics, making it an essential resource for researchers, professionals, and students alike. With a notable standing in multiple categories—including Q2 rankings in Information Systems and Information Systems and Management—the journal facilitates access to cutting-edge findings and methodologies that drive innovation in data management and analysis. Scholars are encouraged to utilize this open-access platform to share their findings and contribute to the collective understanding in these rapidly evolving fields.

Wiley Interdisciplinary Reviews: Computational Statistics is a leading journal published by WILEY, renowned for its influential contributions to the field of statistics and its application in computational studies. With an impressive impact factor reflected in its 2023 categorization as Q1 in Statistics and Probability, this journal ranks among the top in its category, positioned at 20 out of 278 in Scopus, placing it in the 92nd percentile for its discipline. The journal spans from 2009 to 2024 and offers a rich repository of interdisciplinary insights that encompass both theoretical advancements and practical applications of computational statistics, making it an invaluable resource for researchers, professionals, and students alike. While it does not currently offer open access, the journal's commitment to high-quality, peer-reviewed content ensures that it remains a trusted source for cutting-edge developments and methodologies in the rapidly evolving realm of computational statistics.

3c Tecnologia is a premier open-access journal dedicated to the dynamic fields of technology and engineering, published by 3CIENCIAS. With its ISSN 2254-4143, the journal serves as an essential platform for researchers, professionals, and students to disseminate innovative findings and advancements in technologic applications and methodologies. Since its inception in 2012, 3c Tecnologia has fostered a collaborative environment for knowledge exchange, aiming to bridge gaps between theoretical concepts and practical implementations. The journal is accessible to a global audience, ensuring that groundbreaking research is readily available to all. With a commitment to quality and relevance, 3c Tecnologia is positioned as a vital resource within the technological landscape, encouraging contributions that push the boundaries of current understanding and inspire future developments.

Big Data, an esteemed journal published by MARY ANN LIEBERT, INC, serves as a leading platform within the realms of computer science and information systems. Launched in 2013, this journal has made significant strides in shaping the discourse around the management, analysis, and applications of large-scale data. With a commendable impact factor reflected in its 2023 quartile rankings—Q1 in Information Systems and Management, and Q2 in both Computer Science Applications and Information Systems—Big Data is recognized for its quality and influence, holding a notable position in Scopus rankings. Renowned for its rigorous peer-review process, the journal welcomes original research, reviews, and discussions that address the challenges and innovations associated with big data technologies. Researchers, professionals, and students alike will find Big Data an indispensable resource that not only highlights emerging trends but also fosters collaboration and knowledge sharing within the data science community. Access options are available through institutional subscriptions and individual access, ensuring a broad dissemination of critical research findings.

Advances in Data Analysis and Classification is a premier journal published by SPRINGER HEIDELBERG, focusing on the dynamic intersections of applied mathematics, computer science applications, and statistics. Established in 2007, this journal has rapidly gained recognition in the academic community, evidenced by its placement in the Q2 quartile across multiple categories in 2023, including Applied Mathematics and Statistics and Probability. With a strong Scopus ranking, where it stands 68th among 278 in Statistics and Probability, and 190th among 635 in Applied Mathematics, the journal serves as a platform for interdisciplinary research and innovation in data analysis techniques. This journal not only offers a rich repository of scholarly articles but also fosters the dissemination of cutting-edge methodologies and their practical applications. Researchers, professionals, and students alike will find invaluable insights relevant to their work and studies, reinforcing the journal's critical role in advancing knowledge and practices in data science and analysis.