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.

IADIS-International Journal on Computer Science and Information Systems is a prominent platform dedicated to advancing research and knowledge in the field of computer science and information systems. Published by IADIS, this journal aims to disseminate innovative findings and theoretical advancements that address contemporary challenges and trends in technology. The journal fosters a rigorous peer-review process, ensuring that only high-quality research is shared with its audience, which includes researchers, professionals, and students from around the globe. Although the journal is not currently open access, it serves as a vital resource for those looking to deepen their understanding of the evolving landscape of computer science. The ISSN of this journal is 1646-3692, and it boasts a strong commitment to promoting interdisciplinary communication and collaboration in the realm of information technology, making it an essential read for anyone looking to stay at the forefront of this fast-paced field.

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.

Information is a distinguished open-access journal published by MDPI since 2010, dedicated to advancing the field of Information Systems. With its E-ISSN 2078-2489, the journal serves as a crucial platform for researchers, professionals, and students to disseminate and access innovative research and methodologies in the domain of information science, data management, and technology. Based in Basel, Switzerland, the journal has established a commendable reputation in the academic community, currently holding a Q2 ranking in the prestigious Scopus category of Information Systems, and occupies the 74th percentile among its peers. The breadth of the journal's objectives is to promote and facilitate the open exchange of ideas, research findings, and emerging trends, fostering collaboration and knowledge growth in a rapidly evolving digital landscape. With an unwavering commitment to high-quality scholarship and accessible knowledge, Information plays an essential role in shaping the future of the information sciences.

INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS

Published by WORLD SCIENTIFIC PUBL CO PTE LTD, the INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS plays a pivotal role within the fields of Computer Science and Information Systems. With a focus on the development and application of cooperative information systems, this journal aims to foster innovation and collaborative research among scholars and professionals. Established in 1996, the journal has consistently published high-quality research that contributes to a better understanding of cooperative methodologies, enhancing system efficiencies across various applications. While its impact factor remains undisclosed, the journal is positioned in the Q4 category of the Scopus rankings, indicating a growing presence in the academic community. Although it does not offer open access, its rich repository of articles remains accessible to subscribers and relevant institutions. Located in Singapore, this journal will continue to serve as a critical resource for researchers, practitioners, and students keen on exploring the evolving dynamics of information systems in today's interconnected world.

Journal of Information Technology Research (ISSN: 1938-7857, E-ISSN: 1938-7865) is a prestigious academic journal published by IGI Global, dedicated to advancing the field of information technology through rigorous research and insightful analysis. This journal serves as a critical platform for scholars, professionals, and students alike, providing them with up-to-date knowledge and innovative solutions in the ever-evolving realm of computer science. Despite the coverage of the journal being discontinued in Scopus after 2020, it previously held a commendable rank of #145 out of 221 in the 'General Computer Science' category, placing it in the 34th percentile, which reflects its respectable standing among peers. Although currently not an Open Access journal, its contributions significantly shape the discourse surrounding emerging technologies, information systems, and IT management.

The Journal of Scientometric Research is a pivotal publication in the fields of Computer Science Applications, Information Systems, and Library and Information Sciences, published by PHCOG NET. This journal, with ISSN 2321-6654 and E-ISSN 2320-0057, serves as a vital platform for scholars and practitioners seeking to disseminate and engage with cutting-edge research from 2019 through 2024. It occupies a noteworthy position with its 2023 category quartiles, reflecting its growing influence—ranking in Q3 for Computer Science Applications and Information Systems, and Q2 in Library and Information Sciences. The journal's Scopus rankings further emphasize its relevance, performing particularly well within the social sciences domain. Researchers, professionals, and students are encouraged to take advantage of this open-access journal, contributing to the advancement of knowledge and collaboration within the diverse intersection of these fields.

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.

MEASUREMENT is a premier academic journal published by Elsevier Science Ltd, dedicated to advancing research in the fields of Applied Mathematics, Condensed Matter Physics, Electrical and Electronic Engineering, Statistics, and Instrumentation. With an impressive Q1 ranking in multiple categories as of 2023, MEASUREMENT stands out with its strong impact factor, indicative of its high-quality contributions to interdisciplinary research. Since its inception in 1983, the journal has maintained a commitment to publishing innovative methodologies, cutting-edge technologies, and significant advances in measurement science. Although currently not an Open Access publication, the journal provides vital access options through institutional subscriptions, ensuring that researchers, professionals, and students can delve into a wealth of knowledge throughout its pages, including both theoretical and practical applications. The journal’s rigorous peer-review process ensures that only the highest quality research is disseminated, making it an essential resource for anyone involved in quantitative analysis and measurement in diverse scientific domains.

The Journal of Informetrics, published by Elsevier, stands as a leading platform for interdisciplinary research in the realms of Applied Mathematics, Computer Science Applications, Library and Information Sciences, Management Science, Operations Research, Modeling and Simulation, and Statistics. Boasting an impressive 2023 impact factor that ranks it in the Q1 category across multiple disciplines, the journal features a robust Scopus ranking of 38/280 in Library and Information Sciences, placing it in the 86th percentile. This esteemed journal, headquartered in the Netherlands, operates without open access, ensuring a curated selection of high-impact research. Since its inception in 2007, the Journal of Informetrics has been pivotal in advancing knowledge and fostering academic discourse, making significant contributions to the study of information metrics and analytics, thereby appealing to researchers, professionals, and students eager to stay at the forefront of this dynamic field.