Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery is a premier journal published by WILEY PERIODICALS, INC, dedicated to the rapidly evolving fields of data mining and knowledge discovery. Since its inception in 2011, this journal has emerged as a vital resource for researchers and practitioners alike, boasting an impressive Q1 ranking in the field of Computer Science (miscellaneous) as of 2023, and is recognized for achieving a remarkable 98th percentile in Scopus rankings. The journal aims to disseminate high-quality, interdisciplinary research that addresses the theoretical and practical implications of data mining techniques, innovative algorithms, and knowledge discovery paradigms. With a commitment to fostering knowledge exchange among academia and industry, Wiley Interdisciplinary Reviews is essential for those looking to remain at the forefront of data science advancements. Researchers and professionals will find relevant discussions, cutting-edge methodologies, and comprehensive reviews that contribute significantly to the field's development.

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.

The Journal of Intelligent Systems, published by DE GRUYTER POLAND SP Z O O, is a premier open access journal that has been at the forefront of advancements in the fields of Artificial Intelligence, Information Systems, and Software Engineering since its inception in 1991. With a commitment to disseminating high-quality research, the journal has been recognized in the 2023 category quartiles as Q3 in these critical areas, reflecting its relevance and impact in the academic community. The journal serves as a vital platform for researchers, professionals, and students interested in the evolving landscape of intelligent systems, offering insights into innovative methodologies and applications. As an open access publication since 2020, it ensures that research is readily available to a global audience, fostering collaboration and engagement within the scientific community. With a Scopus rank in the 65th to 69th percentiles across its categories, The Journal of Intelligent Systems continues to contribute significantly to the discourse on intelligent technologies and their implications for the future.

Social Network Analysis and Mining, published by SPRINGER WIEN, is a premier journal dedicated to the advanced study and application of social network analysis and data mining methodologies within the fields of communication, computer science, and media technology. With rigorous peer-review standards and a 2023 category ranking within the Q1 quartile for Communication and various Q2 rankings across Computer Science and Human-Computer Interaction, this journal not only highlights cutting-edge research but also influences current trends and methodologies in the discipline. The journal's articles are accessible through subscription, ensuring a broad reach among academic institutions and professionals. Covering converged years from 2011 to 2024, Social Network Analysis and Mining serves as an essential resource for researchers, practitioners, and students seeking to deepen their understanding of social networks’ roles in information systems and digital communication, reflecting significant insights from its Scopus rankings that position it at a high percentile among related fields.

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.

The Journal of Intelligent Information Systems, published by Springer since 1992, is a premier academic journal that offers a multidisciplinary platform in the fields of Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Information Systems, and Software. With an impressive impact reflected in its 2023 Q2 category rankings across multiple domains and a commendable standing in the Scopus Rankings—ranking #84 in Computer Networks and Communications and #101 in Artificial Intelligence—the journal is recognized for its contribution to advancing knowledge and innovation. Although it is not an open-access journal, its accessibility through institutional subscriptions ensures that a wide range of researchers, professionals, and students can engage with high-quality, peer-reviewed research that addresses the latest advancements and trends in intelligent systems. For over three decades, this journal has effectively bridged gaps between academia and industry, making it a vital resource for those aiming to push boundaries in intelligent information systems.

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.

Econometrics and Statistics is a premier journal published by Elsevier, dedicated to advancing the fields of Econometrics and Statistics. Since its inception in 2017, this journal has provided a platform for cutting-edge research, bridging theoretical foundations with practical applications to inform data-driven decision-making. With an impressive impact factor and positioned in the Q2 category across Economics, Econometrics, and Statistics in 2023, it ranks among the top-tier journals in its field, ensuring that the published works are recognized for their quality and relevance. The journal encompasses a broad scope that includes statistical methodologies, econometric analysis, and their interconnectedness, making it valuable for a diverse audience of researchers, professionals, and students. Although it operates under a traditional access model, ongoing efforts are being made to explore open-access publishing options to enhance the dissemination of knowledge. The journal's commitment to rigor and innovation solidifies its role in shaping the future of quantitative analysis.

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.

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.