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.

Revista Brasileira de Computação Aplicada is a distinguished peer-reviewed journal dedicated to disseminating innovative research and advancements in the field of applied computing. Published by UNIV PASSO FUNDO, this open-access journal has been serving the global academic community since 2009, ensuring that high-quality research is accessible to all. With its ISSN 2176-6649, the journal aims to foster collaboration and dialogue among researchers, professionals, and students, bridging the gap between theory and practice in computing. Positioned as an essential resource for those interested in the latest trends and developments in applied computational technologies, the journal strives to contribute significantly to the scholarly discourse and enhance knowledge sharing within this dynamic field. For researchers looking to publish their findings or professionals seeking to stay updated on cutting-edge research, the Revista Brasileira de Computação Aplicada serves as an invaluable platform that empowers the evolution of applied computing in Brazil and beyond.

Data & Policy is a premier open-access journal published by Cambridge University Press, dedicated to advancing the fields of Artificial Intelligence, Computer Science, Public Administration, and the broader Social Sciences. With its inception in 2020, the journal has quickly gained recognition, reflected in its impressive 2023 Scopus rankings—placing it in the top quartiles across multiple categories. Emphasizing the intersection of data utilization and policy-making, Data & Policy provides an essential platform for researchers, policymakers, and professionals looking to navigate and enhance the impact of data-driven decisions in society. Accessible to a global audience without subscription barriers, this journal offers valuable insights and contemporary research that are vital for educators, practitioners, and emerging scholars alike. Located in the United Kingdom, Data & Policy continues to contribute to shaping the dialogue around the ethical use of data and its implications in shaping public policy and governance.

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.

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.

Cognitive Computation is a prominent journal published by Springer, focusing on interdisciplinary research at the intersection of cognitive sciences and computational methods. With an ISSN of 1866-9956 and an E-ISSN of 1866-9964, this journal has established itself as a leading resource for novel advancements and methodologies from 2009 through 2024. It is categorized in the top quartile (Q1) for 2023 in influential fields such as Cognitive Neuroscience, Computer Science Applications, and Computer Vision and Pattern Recognition. With impressive Scopus rankings including a 14th position in Cognitive Neuroscience and a percentile rank of 88th, the journal serves as a crucial platform for researchers and professionals eager to explore the cognitive processes underlying computational techniques. Although it does not operate under an open access model, the richness of research published within its pages contributes significantly to the academic discourse in these rapidly evolving domains, making it an essential read for scholars and practitioners alike.

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.

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.

Data & Knowledge Engineering is a prestigious, peer-reviewed journal dedicated to the fields of data management, information systems, and knowledge engineering. Published by Elsevier in the Netherlands, this journal serves as a critical resource for researchers, professionals, and students alike, offering a platform for high-quality, original research and innovative approaches in the realm of data-driven technologies and methodologies. With a considerable impact factor and classified in the Q2 quartile for Information Systems and Management, it ranks 47th out of 148 journals in its category, placing it in the esteemed 68th percentile according to Scopus metrics. Data & Knowledge Engineering covers a wide array of topics including database systems, data mining, and knowledge representation, ensuring that it remains at the forefront of advancing understanding and application in these dynamic fields. Engage with compelling articles and significant findings published since its inception in 1985, as the journal continues to shape the future of data-centric research up to 2024 and beyond.

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.