Communications for Statistical Applications and Methods is a vital academic journal dedicated to advancing the field of statistics, with a particular focus on practical applications and methodologies. Published by the Korean Statistical Society, this journal has become a significant resource for researchers, practitioners, and students engaged in statistical sciences and its diverse applications in various fields including finance and modeling. Operating without an Open Access format, the journal is accessible through institutional subscriptions, allowing a broad audience to benefit from its insights. The journal covers works from its inception in 2017 to 2024, and although it currently ranks in the Q4 and Q3 quartiles across various mathematical and statistical categories, its commitment to quality research makes it a noteworthy platform for emerging trends and innovations. The journal not only serves to disseminate knowledge but also fosters collaboration among statisticians, ensuring that crucial advancements in statistical applications are communicated effectively.

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.

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.

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.

International Journal of Data Mining Modelling and Management, published by InderScience Enterprises Ltd, is a prominent academic platform dedicated to the exploration and advancement of data mining techniques and their applications across various domains. Located in the picturesque environment of Geneva, Switzerland, this journal serves as a crucial resource for researchers, professionals, and students engaged in the fields of Computer Science, Management Information Systems, and Modeling and Simulation. With an ISSN of 1759-1163 and an E-ISSN of 1759-1171, the journal has steadily converged its scope from 2008 to 2024, emphasizing innovative methodologies and dynamic developments in data analytics. Although currently categorized in Q4 for several relevant fields according to 2023 quartiles, the journal is committed to elevating its impact and outreach through rigorous peer-reviewed research, making it an essential read for those aiming to stay at the forefront of data-driven decision-making and management practices. Whether you are a seasoned researcher or an eager student, the International Journal of Data Mining Modelling and Management offers invaluable insights and contributions to the evolving conversation in data science.

Big Data and Cognitive Computing is a premier open-access journal published by MDPI, dedicated to advancing research in the dynamic fields of artificial intelligence, computer science, information systems, and management information systems. Since its inception in 2017, the journal has established a significant presence, reflected in its impressive categorization within the Q2 quartiles for multiple disciplines in the 2023 rankings. Situated in Switzerland, the journal provides a vital platform for researchers, professionals, and students to publish groundbreaking work and access high-quality articles, enhancing the exploration of big data applications powered by cognitive computing. With an increasing global emphasis on data-driven decision-making, Big Data and Cognitive Computing offers unrestricted access to innovative research findings, addressing both theoretical and practical aspects. The journal's contributions are integral for those looking to stay at the forefront of technological advancements and their implications across various sectors.

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.

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.

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.