The scientific, technical, and medical (STM) journals in China are embracing unprecedented development opportunities. Many incentive policies have been introduced, accompanied by the initiation of a large number of funding projects. Under this supportive environment, STM journals in Chinese language try to adjust their publishing strategies, excavate topic selection, attract and invite high-quality manuscripts, and adopt diverse promotional methods, thus resulting in substantial development. Simultaneously, the rapid development of science and technologies brings about technological innovation. Particularly, the emergence and development of generative artificial intelligence (AI) technologies such as ChatGDP and DeepSeek have created new opportunities and challenges for the Chinese-language STM journals. Though, such innovative technologies significantly optimize academic writing processes and simplify editorial tasks of journal editors, they bring confusion to editorial normative operation and ethical integrity. To address these issues, several standards or guidance documents have been established, such as the “Academic Publishing Specification—Definition of Academic Misconduct for Journals (CY/T 174—2019)”. To systematically understand the development status of Chinese-language STM journals and explore the steady development pathways for these journals, the development of Chinese-language STM journals in 2024 is briefly reviewed in this paper, and the performance metrics of Chinese-language STM journals are analyzed using data from the Annual Report for Chinese Academic Journal Impact Factors (Natural Science) (2020—2024), World Journal Clout Index (WJCI) of Scientific and Technological Periodicals (2022—2024), and Annual Report for International Citation of Chinese Academic Journals (Natural Science) (2024). The results show notable improvements in the discipline impact of Chinese-language STM journals in 2024. Firstly, the average impact factor, average total citations, average annual downloads, and average number of annually-published articles in 2024 have all increased compared to 2023. Secondly, all average evaluation indicators from World Journal Clout Index (WJCI) in 2024 are larger than those in 2023, and the number of selected species increases year by year. Moreover, Chinese-language STM journals have also performed well in database inclusion. In 2024, more than 35 journals were included in the “Key Magazine of China Technology”, more than 124 journals were indexed by SCOPUS, and more than 64 journals were included by the Directory of Open Access Journals (DOAJ). Though the absolute values of impact indices of major Chinese-language STM journals in the Journal Citation Reports (JCR) for SCI in 2024 were reduced, most Chinese-language STM journals improved slightly in subject rankings. Based on the aforementioned findings, alongside the development policies for Chinese-language STM journals, this paper thoroughly explores the authoritative database inclusion status of Chinese-language STM journals, the status quo of Chinese-language STM journals selected in the “Excellence Action Plan for China STM Journals”, and the development trends of these journals in 2024. In light of the current development environment of STM journals at home and abroad, some suggestions are proposed to promote the sustainable and high-quality development of Chinese-language STM journals: leveraging policy support to solidify foundations; embracing open science to broaden perspectives; practicing credibility construction to ensure steady progress; and integrating the new AI technologies to lead the future intelligently.

This study presents a systematic evaluation of DeepSeek, a cutting-edge Chinese-developed large language model (LLM), focusing on its application in editing and refining Chinese-language abstracts for medical journals. It employed a comprehensive methodology, analyzing 60 medical research abstracts from the Journal of Jilin University (Medical Edition). These texts were processed using DeepSeek-R1, the latest version of the model released in January 2025, which was specifically integrated into Microsoft Word to simulate practical editorial workflows. To ensure methodological rigor, this study implemented a dual evaluation framework combining quantitative metrics with qualitative expert assessments conducted by three senior medical editors with extensive publishing experience. In terms of basic language refinement, the model demonstrated remarkable proficiency, accurately identifying and correcting grammatical errors in 95% of cases compared to benchmarks set by human editors. It performed particularly well in handling complex Chinese sentence structures, including resolving issues with subject-verb agreement, proper comma usage, and logical coherence. Moreover, the model exhibited strong performance in language simplification, reducing wordiness by 44.7% across the test corpus while preserving essential meaning, a capability that could substantially improve the clarity and accessibility of medical research reporting. However, the evaluation also revealed critical limitations that currently restrict DeepSeek's utility for comprehensive medical editing. Notably, the model struggled with domain-specific challenges, achieving only 22.4% accuracy in standardizing domain-specific medical terminology. Several technical factors underlying these limitations were identified. First, the model's training data appears insufficient to comprehensively cover the full spectrum of medical sub-specialties and their evolving terminologies. Second, DeepSeek exhibits constrained ability to contextualize information within the rigorous framework of medical research reporting, occasionally prioritizing linguistic fluency over scientific precision. Third, the analysis suggests that the model has difficulty keeping pace with rapid advancements in medical science, occasionally providing outdated terminology or conceptual frameworks. Despite these limitations, the model's processing speed, approximately 20 times faster than human editors, positions it as a transformative tool for revolutionizing manuscript turnaround times, particularly during periods of high submission volume. Its consistent performance in fundamental language polishing suggests valuable applications for initial manuscript screening and formatting standardization. A tiered editorial workflow is recommended, where DeepSeek handles initial language refinement and formatting, followed by specialized human editors focusing on content validation and scientific accuracy. To maximize future potential of the model, three key development directions are proposed: (1) expanding medical domain-specific training data, particularly for emerging specialties and technologies; (2) developing hybrid models that integrate linguistic analysis with medical knowledge graphs; and (3) creating customizable modules that journals can adapt to their specific stylistic and terminological requirements. These findings.

Nations worldwide are actively developing and leveraging data resources both domestically and internationally. These resources exhibit economic characteristics including externalities, non-rivalry, and non-excludability, alongside sociological attributes such as shareability, spatiotemporal relevance, and public accessibility. Data quality serves as a critical determinant of model performance in generative artificial intelligence (GenAI) systems, and the lack of high-quality training datasets remains a significant challenge across sectors. While previous research on data elements has focused on implementation aspects, this study examines the underlying rationale and methodologies. This paper establishes the connotation and extension of high-quality datasets, identifying four quality dimensions within a three-dimensional six-tier analytical framework; 1. Structural Dimension; 2. Spatiotemporal Dimension; 3. Security Dimension: The core requirements for constructing high-quality datasets are categorized into four dimensions; 1. Data Unit Level; 2. Dataset Level; 3. Social Benefit Perspective; 4. Economic Benefit Perspective: This framework integrates technical specifications with governance principles, addressing both operational efficiency and societal value creation. The analysis examines industry-specific characteristics and resource endowments to demonstrate why the publishing sector holds unique social responsibility in constructing high-quality datasets. Publishing data exhibits inherent advantages: 1. Quantity: Rich diversity of types and abundant reserves; 2. Quality: Rigorous supply mechanisms and strict review processes; 3. Externality: Traceable ownership and privacy clearance; 4. Standardization: Technical support and cross-referencing capabilities. At the data unit level, publishing data undergoes comprehensive peer review and expert verification, ensuring superior accuracy and reliability compared to alternative data sources. Publishing data achieves substantial completeness and richness through comprehensive industry coverage. At the dataset level, professional editorial teams facilitate secondary knowledge production during data aggregation. They integrate technology with publishing workflows in processes such as packaging, delivery, error correction, and iterative updates, establishing sustainable version control mechanisms. Regarding benefits, publishing data inherently features desensitization and alignment with mainstream ideological values, addressing the balance between data protection and public accessibility. Moreover, the publishing industry's established ownership tracing and benefit distribution mechanisms provide a foundation for business evolution, facilitating trust networks and incentive-compatible business models between data providers and users. From a meso-theoretical perspective, this study employs a best-practice approach, examining mature image databases in the digital copyright trading industry as case studies. It analyzes principles and methodologies for constructing high-quality datasets, proposes operational and training recommendations, and achieves alignment between theory and practice. The marginal contributions of this paper are threefold: first, clarifying the scope and definition of high-quality datasets; second, analyzing the publishing industry's characteristics and advantages to identify key stakeholders; and third, recommending standards, operational principles, and construction methods for high-quality datasets.

The development of internationally influential scientific, technical, and medical (STM) journals that align with China’s technological advancement depends fundamentally on establishing an editorial team with a “craftsmanship spirit.” An analysis of the contemporary connotations of craftsmanship spirit in the context of STM journals reveals its dual essence: A pursuit of values and professional competence. Social cognitive theory, particularly its triadic reciprocal determinism provides a valuable perspective for understanding the interactions between individual factors (such as self-efficacy and values), environmental factors (institutional frameworks, cultural context, and physical infrastructure), and behavioral outcomes (experience and practice). In the cognitive dimension (individual factors), value pursuit manifests through editors' role as scientific gatekeepers and their professional dedication, while professional competence requires self-efficacy-driven knowledge iteration and skill enhancement, forming a dynamic mechanism where value orientation and capability development mutually reinforce each other. The behavioral dimension demonstrates value pursuit through standardized operating systems and cultural construction, with professional competence reflected in lean practices such as technological integration and continuous learning, extending value through technical behaviors. In the environmental interaction dimension (environmental factors), value pursuit requires editors to uphold academic missions amid institutional reforms and integrate resources to build academic communities; meanwhile, professional competence necessitates addressing emerging challenges like open science and intelligent publishing. This involves constructing a "technology-content-service" system, deeply embedding emerging technologies like artificial intelligence and big data into the entire publishing process to achieve innovative breakthroughs. Based on social cognitive theory and combined with the key elements of building world-class scientific journals in China, this paper explores the new requirements of high-quality development for editors’ craftsmanship spirit. These are reflected mainly in three dimensions: Cognitive upgrading—redefining the editor’s role in alignment with national strategy; behavioral enhancement—acquiring and applying interdisciplinary knowledge; and environmental adaptation— publishing innovation in the context of technological evolution. Editors must closely integrate their work with national strategic priorities, ensuring that journal content supports both national objectives and guides the development of disciplinary research. It is essential for editors to construct a system for learning and applying cross-disciplinary knowledge, relying on an interactive “editing-learning-research” mechanism to enable continuous renewal of their knowledge structures. Taking the publishing practice of Science and Technology Review Pubblishing House as an example, this paper proposes that the main approaches for STM journal editors to practice craftsmanship spirit for high-quality development include: Deepening understanding of national strategies while building a quality assurance system; establishing a dynamic knowledge updating system to enhance academic services; and innovating publishing models to promote the transformation and upgrading of journals. In conclusion, the craftsmanship spirit, characterized by strong value commitment and professional excellence, remains fundamental to the high-quality development of China’s STM journals.

In 2024, the prosperity of open science and the progressive refinement of Artificial Intelligence (AI) technology have initiated a profound transformation in scientific research. Simultaneously, they have brought Scientific, Technological and Medical (STM) publishing and academic dissemination to a critical point of transition. This paper presents a comprehensive analysis of international trends in STM journal publishing at this crucial juncture. First, Open Access (OA) publishing has experienced new changes due to intense competition between commercialization and community-based forces. The number of Transformative Agreements (TAs) has decreased for the first time this year. High Article Processing Charges (APCs) have raised questions about whether OA development has diverged from its original purpose, prompting fundamental reflections of OA as the sole permitted publishing model. Preprints, despite their advantages and limitations, are emerging as a pathway toward researcher-led, academically autonomous OA, though issues such as quality control remain unresolved. Second, the Open Data movement continues to advance steadily progressing and gradually towards more responsible data sharing practices. However, the absence of standardized data sharing protocols may result in inconsistent formats, incomplete or missing metadata descriptions, broken access links, and uneven data quality, impeding effective discovery, access, interoperability, and reuse of data. Furthermore, although open data sharing represents an inevitable trend, certain data cannot be publicly accessible under all circumstances. Unrestricted sharing of specific data may potentially threaten national security, commercial confidentiality, personal privacy, and social stability. Consequently, governments, funding agencies, and publishers are developing or updating policies and implementing measures to promote standardized and secure data sharing, reflecting heightened demands for data quality, security, and normative usage in academia. Third, STM publishers are expediting their transformation through content and technology integration, pursuing new opportunities presented by advanced technologies such as AI. Beyond consolidating content resources through acquisitions, partnerships with academic societies, and launch of new journals, publishers like Taylor & Francis Group and John Wiley have achieved revenue growth through AI-enabled content. More publishers are recognizing the efficiency benefits of AI applications and actively developing related tools and services for the scientific research lifecycle or creating AI-based specialized solutions. As AI technology applications deepen, the possession and acquisition of high-quality, specialized content and data will reveal multiple roles and values. Finally, STM journal publishing in the digital era confronts an intensified trust crisis, with emerging AI technologies potentially exacerbating this challenge through biases and errors. To address integrity threats including paper mills, AI application issues, and peer review reform challenges, various stakeholders have proposed technical and non-technical solutions to maintain research quality. In conclusion, the revolution catalyzed by open science and AI in scientific research and STM publishing remains in its early stages. However, their potential has already generated significant interest among researchers, publishers, and other stakeholders. Realizing the vision of digitization will require collaborative efforts to ensure responsible AI utilization, foster a new open and healthy publishing ecosystem, and advance goals in open science, research integrity, and transparency.

The history of human civilization, in a sense, is the history of publishing. Publishing compiles the remarkable material and intellectual creations of mankind, and organizes, processes, and disseminates these achievements to the public in the form of textual content, images, charts, audio and video, facilitating their widespread dissemination. This process shapes the civilization’s evolution and human progress. Publishing not only participates in it with its social responsibility and professional style, but also plays an irreplaceable role and creates a cultural style that is unique to mankind. The academic community is accustomed to positioning publishing as "spreading knowledge, inheriting culture" or even merely "collecting and organizing information". However, such perspectives are obviously insufficient and do not conform to the historical achievements and actual development of publishing. In ancient societies, publishing served as a creator of traditional culture; while in modern times, it plays the role of a leader of modern culture. Publishing should re-examine its own history, and re-evaluate its historical achievements by engaging with realities and developing a deeper understanding of itself, that is, publishing creates culture in its own way. This article expounds on the publishing activities of ancient, modern and new eras, examines the unique cultural mission and responsibilities of publishing in each era, and proves that the role of publishing in creating culture has never diminished from ancient to contemporary times. Specifically, the study highlights three key dimensions. First, publishing is the creator of traditional culture. It created content culture through the arrangement, editing and publication of ancient classics; created graphic structure art culture through layout design and binding design; and created the unique material culture of books with Chinese binding form. Second, publishing is the leader of modern culture. It has brought modern scientific culture to China; created a new publishing material culture that combines Chinese and Western cultures; and created a new type of industrial and commercial social culture by opening up the modern enterprise system. Third, publishing is the initiator of the new culture of the new era. It firstly builds the cultural peak of Chinese modernization with new academic publishing creations; and then builds the new culture of publishing and media with new industrial technologies and new forms. Finally, it improves the "scientific" level of reading culture with the trend of popularization of knowledge. In short, each society has its own needs, and different needs form different waves of the times. The topics, challenges, and issues that reflect the needs of the country, the nation and the times are those to which the publishing industry should give the greatest consideration, attention, and response. In different historical eras, facing different responsibilities and missions, publishing has created its own unique cultural forms. Responding to the topics, challenges and issues of the new era in its own way constitutes cultural innovation aligned with the times, creating a new culture of the times, which plays an indispensable role in the development of human society and the evolution of civilization. In the new historical era, as China embarks on the path of building a socialist modern country with Chinese characteristics, publishers should shoulder their mission of the times, live up to the trust of the times, and create a new culture of the new era.