Core Viewpoint - Springer Nature offers a comprehensive portfolio of open access (OA) journals, providing authors with high-impact publishing options and increased citation opportunities for their research [3]. Group 1: OA Journal Portfolio - Springer Nature has approximately 700 pure OA journals, with 2023 OA articles averaging 6.3 citations each, surpassing industry peers [3]. - Over 500 pure OA journals have an impact factor (IF), with 62% of these journals showing growth in their IF [4]. - 309 pure OA journals are ranked in Q1 across various disciplines, representing 57% of the total [4]. - 450 pure OA journals are in the top 50 of their respective fields, accounting for 83% [4]. - 106 pure OA journals are in the top 10 of their fields, including notable journals like Signal Transduction and Targeted Therapy [4]. Group 2: Historical Context and Development - Springer, founded in 1842, is a renowned publishing brand in science, technology, medicine, humanities, and social sciences, with over 2000 mixed and OA journals [5]. - BMC, a pioneer in OA publishing, has around 300 peer-reviewed OA journals focused on advancing biological, health, and medical sciences [7][8]. Group 3: Specific Journal Highlights - The Discover journal series aims to support rapid publication of research across various scientific fields, targeting a publication timeline of 7-10 weeks [14]. - Nature Partner Journals (npj) collaborate with global scientists and institutions to publish high-quality OA research in diverse scientific areas [19]. - The Communications series under Nature Portfolio emphasizes diverse community engagement and aims to publish research that brings new insights to its fields [23]. - Nature Communications, a highly selective multidisciplinary OA journal, has an impact factor of 15.7 and a total citation count of 911,428 for 2024 [30]. - Scientific Reports, another multidisciplinary OA journal, has an impact factor of 3.9 and a total citation count of 834,622 for 2024 [34]. - Humanities and Social Sciences Communications provides a rigorous platform for research in the humanities and social sciences, with an impact factor of 3.6 for 2024 [35].

Core Viewpoint - The article discusses the launch of a new global scientific literature data platform, dbdata.com, created by Chinese institutions, aimed at providing high-quality research support and reducing reliance on Western-dominated databases [2][3]. Group 1: Platform Overview - The dbdata.com platform includes nearly 90 million high-quality scientific literature metadata and incorporates AI functionalities to enhance research efficiency [2]. - The platform's basic features will be available for free to global users, facilitating literature retrieval, citation analysis, and data tracking [2]. Group 2: Issues with Existing Databases - The most widely used scientific literature database globally is Web of Science, which has over 100 million entries but suffers from issues such as manipulation of citation metrics, affecting the objectivity and accuracy of research evaluations [3]. - The existing citation evaluation system has not seen substantial improvements in 70 years, leading to the inclusion of many low-quality papers, which diminishes the academic value of the database [3]. Group 3: Dongbi Index - The platform is based on the Dongbi Index, a new evaluation standard developed by a team of young scientists, which aims to provide a more objective and accurate reflection of journal authority and impact [4]. - The Dongbi Index incorporates a quality grading system and a citation tracing method, moving beyond the traditional reliance on citation counts [4]. Group 4: Classification System - The platform has developed a classification system aligned with the habits of Chinese researchers, using the classification codes from the National Natural Science Foundation and the Ministry of Education, which are not represented in Web of Science [4]. - This classification system helps researchers understand their academic boundaries and provides precise decision-making support for management departments [4]. Group 5: AI Integration - The platform has integrated AI capabilities, including "scholar achievement interpretation" and "automatic review generation," effectively providing users with an "AI assistant" for research inquiries [5]. - Users can interact with the AI to obtain insights into scholars' research directions, characteristics, and contributions [5].

Core Viewpoint - The launch of the global technology literature data platform dbdata.com aims to provide a self-controlled, high-quality resource for scientific research, addressing the monopolization of scientific literature databases by Western companies and enhancing China's technological infrastructure [1][2]. Group 1: Platform Overview - The dbdata.com platform includes nearly 90 million high-quality scientific literature metadata and incorporates AI functionalities to assist in high-quality scientific research [1]. - The platform's basic features will be available for free to global users, offering efficient literature retrieval, citation analysis, and data tracking services [1]. Group 2: Issues with Existing Databases - The most widely used scientific literature database globally is Web of Science, which has over 100 million entries but suffers from flaws in its citation metrics, leading to potential manipulation and misallocation of research resources [2]. - The existing evaluation metrics have not seen substantial improvements in 70 years, which has hindered the academic community and reduced the reference value of many included papers [2]. Group 3: Dongbi Index and Classification - The platform is based on the Dongbi Index, a new evaluation standard developed by a team of young scientists, which aims to provide a more objective and accurate reflection of journal authority and impact [3]. - The Dongbi Index incorporates a quality grading system and is designed to align with the classification habits of Chinese researchers, offering a more relevant categorization of journals [3]. Group 4: AI Integration - The platform has integrated AI capabilities, including "scholar achievement interpretation" and "automatic review generation," effectively providing users with an AI assistant for inquiries about researchers and their contributions [4].