Study on Interdisciplinary Research Behaviors in the Biosafety

Study on Interdisciplinary Research Behaviors in the Biosafety | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Study on Interdisciplinary Research Behaviors in the Biosafety Xi Wang, Dongqiao Li, Xiwen Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8390102/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The deployment of scientific research projects through interdisciplinary models has become a consensus and is increasingly seen as an important approach to addressing major scientific and societal issues. The process of interdisciplinarity involves combining research materials, methods, themes, theories, and tools to achieve the integration of knowledge across disciplines. However, only a limited number of works have conducted bibliometric analyses of interdisciplinarity from the perspective of the interdisciplinary process itself. This paper defines the interdisciplinary research process as Interdisciplinary Behaviors. By analyzing those behaviors, it seeks to reveal the characteristics of interdisciplinarity. A fine-tuned large language model (LLM) is employed to construct a disciplinary knowledge graph, supporting research on interdisciplinary behaviors. Focusing on the field of Biosafety, the study quantitatively analyzes interdisciplinary behaviors from three perspectives: research materials, research methods, and research themes. It uncovers the internal behavioral processes and pathways of interdisciplinarity, aiming to provide a theoretical foundation and research tools for dissecting interdisciplinary phenomena, as well as a reference for describing interdisciplinary behaviors in the biosafety domain. Biosafety Research Behaviors Interdisciplinary Research Large Language Model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Looking back at the history of scientific development, the resolution of major problems and challenges in science and society, as well as disruptive scientific breakthroughs, often require crossing disciplinary boundaries and integrating knowledge from multiple fields. Interdisciplinary research has thus gradually become an indispensable model for tackling grand challenges and achieving innovative breakthroughs (Lu Y X, 2005 ; Zhang Lin et al., 2020). Interdisciplinarity is a research model undertaken by teams or individuals that integrates information, data, methods, tools, perspectives, concepts, and theories from two or more disciplines or professional knowledge communities. Its aim is to fundamentally deepen understanding or to solve problems that transcend the scope of a single discipline or field of practice (National Academy of Sciences et al., 2005). Scholars in China and abroad have analyzed the characteristics of interdisciplinarity from the perspectives of research materials/objects, research methods, and research themes. Zhang Lin (Zhang Lin et al., 2020) argue that when research approaches, methods, and tools from different disciplines are combined, the research object acquires characteristics of disciplinary diversity, and that this process represents the essence of interdisciplinarity. George (George J B, 2011 ) points out that interdisciplinary research establishes a framework of "Concepts-Theories-Empirical Findings" through the integration of different disciplinary perspectives, ultimately enabling the study of a given theme. Suo (Suo C J & Xiao Y, 2023) distinguish between formal interdisciplinarity and substantive interdisciplinarity, suggesting that substantive interdisciplinarity—formed through the integration of research content, sharing of methods, and the exchange and collision of perspectives across disciplines—tends to be more structurally cohesive. Yan Bing (Yan B & Song Z L, 1996), based on the "quadripartite classification" and qualitative and quantitative differences in interdisciplinarity, identify three types: unitary interdisciplinarity, binary interdisciplinarity, and multiple interdisciplinarity. They further explain these types from the perspectives of research materials, research methods, and research content. Lu Yongxiang (Liu Z L, 1993 ) proposes that interdisciplinary science uses theories and methods from multiple disciplines to study complex objects, ultimately achieving scientific holism. Liu Zhonglin (Liu Z L, 1993 ) regards interdisciplinarity as the organic integration of theories or methods from different disciplines. Lawrence (Lawrence et al., 2022 ) provide a review of definitions of interdisciplinarity, suggesting that it involves the transfer and interaction of disciplinary methods, theories, and knowledge across different fields. Existing research on the characteristics of interdisciplinarity mainly adopts perspectives such as citations, co-authorship, keywords, or subject terms. However, these approaches have low correspondence with the actual interdisciplinary process and thus struggle to reveal the internal mechanisms and patterns of interdisciplinarity. Only a limited number of scholars have analyzed the degree and development of interdisciplinarity from the perspectives of research methods and research objects. For example, Rafols (Rafols & Meyer, 2007 ) argue that the number of disciplines associated with the instruments mentioned in research methods can influence the level of interdisciplinarity. Chen (Y. Chen, 2020 ) points out that the mutual support among research methods such as the Internet of Things, cloud computing, big data processing, and artificial intelligence has created many interdisciplinary fields and promoted interdisciplinary development. Yang (Y. Yang, Zhang, et al., 2023 ) classify paradigms of interdisciplinarity driven by information processing and management technologies based on data objects, information objects, and computational methods. Wang Yuefen (Wang Y F et al., 2017 ), using data from the field of library and information science, studied themes such as "Information" and "Big Data," finding that these research objects intersect with multiple disciplines including higher education, business economics, computer software and applications, as well as journalism and communication. Overall, however, there has been relatively little integrative research directly analyzing the interdisciplinary process from the perspectives of methods, objects, or themes. There is also a lack of fine-grained studies that jointly analyze interdisciplinarity characteristics, as well as studies that examine the correlations between methods, objects, and themes in interdisciplinary research. This paper defines the concept of Interdisciplinary Behavior, which encompasses research objects, methods, and themes (specifically the classification of biosafety issues) in the context of interdisciplinarity. By integrating commonly used data on interdisciplinary features—such as publication time and disciplinary classifications—a dataset for studying interdisciplinarity characteristics was constructed. Using DeepSeek-V2 combined with manual annotation, a training dataset was rapidly built. The LoRA (Low-Rank Adaptation) method, together with prompt learning strategies, was applied to fine-tune LLaMA3.1-8-Chat, enabling fast identification and extraction of interdisciplinary features. A Neo4j-based interdisciplinary knowledge graph was created, along with methods for interpreting this graph. The study analyzed the characteristics of interdisciplinary behaviors in the biosafety field, describing how interdisciplinarity manifests in research objects, research methods, and research themes. The findings demonstrate that interdisciplinarity exists across all three dimensions in biosafety research. This work provides a theoretical reference for retrieving and discerning interdisciplinarity studies, and offers a practical pathway for the rapid identification of interdisciplinary features and the efficient construction of interdisciplinary knowledge graphs. Concept and Definition of Interdisciplinary Behaviors Interdisciplinary Behaviors refers to the manner in which relevant elements are adopted during the process of interdisciplinary research, including themes, objects, methods, and tools from different disciplines. "Behavior" is generally defined as observable and measurable activities or responses exhibited by individuals within an external environment, characterized by objectivity and diversity. The elements of interdisciplinarity include research objects, methods, themes, approaches, and tools. Interdisciplinary research may be achieved by incorporating a single element from another discipline (e.g., a research method) and combining it with its own theories, concepts, or research themes. Alternatively, it may involve integrating multiple elements—such as research methods and concepts—from other disciplines alongside knowledge from the home discipline to achieve interdisciplinarity. Measuring and describing interdisciplinary behaviors help clarify the pathways by which interdisciplinarity is implemented and further reveals its underlying behavioral mechanisms and interdisciplinary patterns. Interdisciplinary behaviors use research themes, objects, methods, tools, and theories as entry points to explore the characteristics of interdisciplinary processes at each stage. By identifying how a given field incorporates interdisciplinarity in terms of research methods, themes, and objects, one can obtain the interdisciplinary behavioral characteristics of that field. The concept of interdisciplinary behavior provides a clear pathway for carrying out future interdisciplinary research, offering references for the organization of studies, selection of methods, and determination of research objects. Ultimately, it aids the orderly integration and collaborative development of knowledge across disciplines within the research process. Method Our study first constructs an interdisciplinary dataset, combining DeepSeek-V2 (DeepSeek-AI et al., 2024) with manual annotation to rapidly build a training dataset. The LoRA (Hu et al., 2021) (Low-Rank Adaptation) method, together with prompt learning strategies, is then applied to fine-tune a large language model (LLaMA3.1-8-Chat) (Hugging Face, n.d.) in order to enable the fast identification and extraction of process elements of interdisciplinarity. Using Neo4j, the extracted information—including research objects, research methods, biosafety classifications, keywords, publication years, and WOSIDs—was organized into a knowledge graph. Techniques including clustering were further applied to develop a knowledge graph-based method for analyzing interdisciplinarity, thereby providing methodological support for uncovering interdisciplinary behaviors. Figure 1 shows the technical roadmap. 1. Data Collection This study emplyed the Web of Science Core Collection - All as the data source. Biosafety-related keywords such as " biological safety, bio-safety, biosecurity, biological security, biology safety, bio safety, bio-security, biosaf* " were applied in Boolean search queries. A total of 19,191 research papers published between January 1900 and January 2024 were retrieved. To facilitate the analysis of the interdisciplinary knowledge graph, the classification of each paper was carried out using the disciplinary knowledge contribution role system proposed by Wang (Wang et al., 2025). After removing papers that were difficult to classify, a final set of 16,805 original papers was obtained. Subsequently, abstracts, keywords, and other metadata of each paper were extracted in batches as the data source. Details of data screening and classification are provided in the supplementary file. Using a large language model, information such as abstracts, keywords, titles, publication dates, document types, JCR disciplines, and WOSID numbers was extracted from each paper. The complete information of one paper was recorded as one data entry. 2. Fine tuning of the large language model Due to computational resource limitations, this study adopted the LLaMA3.1-8B-Chat (Hugging Face, n.d.) model combined with the LoRA (Hu et al., 2021) method for model fine-tuning. LoRA (Hu et al., 2021) is an efficient and flexible fine-tuning technique designed for pretrained models. Integrating LoRA (Hu et al., 2021) with prompt learning strategies allows for better handling of domain-specific complexity and specificity. Details regarding the model training dataset, testing dataset, validation methods, and fine-tuning results are provided in the supplementary file. 3. Construction of the interdisciplinary knowledge graph This study designed a quintuple structure for the interdisciplinary knowledge graph, consisting of: head entity, head entity category, relation, tail entity, and tail entity category, which were stored in Neo4j to construct the knowledge graph. The entities in the knowledge graph are classified into seven categories: JCR subject information, WOSID number, keyword information, publication year information, research object, research method, research theme classification. The research theme classification is based on the Biosafety Law of the People’s Republic of China and includes: Human infectious diseases and illnesses, Animal infectious diseases and illnesses, Plant infectious diseases and illnesses, Biotechnology safety, Clinical biosafety, Laboratory biosafety, Genetic resource security, Biological resource security, Biodiversity, Species invasion, Antimicrobial resistance, Bioterrorism, Biological weapons threats, and Others. It is possible for a single article to involve multiple biosafety categories. Since document type is mainly used to help extract research methods, it is not stored in the knowledge graph. For all entities included in the knowledge graph, if multiple entities of the same category appear in a single paper, they are linked by a "co-occurrence" relation. For entities of different categories within the same paper, relations are defined as shown in Fig. 2. "Discipline" concerns "Biosafety Issue"; "Discipline" applies "Research Method"; "Discipline" focuses on "Research Object"; "Research Object" belongs to "Biosafety Issue"; and "Research Method" investigates "Biosafety Issue" and "Research Object." To facilitate subsequent data management, links are also established between WOSID and "Year," "Discipline," and "Keywords." The interdisciplinary knowledge graph provides a more intuitive perspective for describing the process of interdisciplinarity and helps improve the understanding of interdisciplinary behaviors. In Fig. 3, only 200 entities and relationships are displayed. Different colored nodes represent different types of entities, while the edges between nodes represent the relationships among them. Unlike traditional knowledge graphs, this graph incorporates a large volume of domain-specific knowledge from diverse fields, making it difficult to directly analyze using only the disciplinary categories of the literature. Therefore, this study develops a knowledge graph analysis method tailored for interdisciplinarity, and applies it to interpret the interdisciplinary knowledge graph. The detailed methodology is provided in the supplementary file. Interdisciplinary Activities in the Field of Biosafety Analysis of research objects in the field of biosafety Biosafety research encompasses a wide range of objects, yet scholarly attention to these objects is uneven. Clarifying their categories and the extent to which they are studied is essential for understanding the interdisciplinary dynamics of the field. To this end, this study examines disciplinary engagement with different research objects, highlighting variations in emphasis across domains (Fig. 4). As shown in Fig. 4, knowledge-contributing disciplines are classified into five categories: core (type_1), emerging (type_2), substitute (type_3), marginal (type_4), and hybrid (mix_type), the latter integrating at least two types of contributing knowledge. The analysis reveals that core disciplines address the broadest range of research objects across multiple disciplines, with particular emphasis on pests and diseases, followed by materials, biosafety itself, agriculture, and technology. Food, ecology, and related objects attract comparatively less attention. Within the core group, fields such as Biotechnology & Applied Microbiology, Materials Science, Biomaterials, and Engineering, Biomedical advance research on materials, technologies, equipment, and tools, while Cell Biology, Immunology, Oncology, and Microbiology provide methodological and analytical frameworks for exploring pathogenic mechanisms and the theoretical foundations of life processes. Pharmacology & Pharmacy supports the development of therapeutic strategies, and Chemistry, Physical together with Chemistry, Multidisciplinary underpins work on chemical drug development, laboratory reagents, and the biosafety of chemistry-related products. Emerging disciplines also engage broadly with nearly all categories of research objects, with the greatest emphasis on pests and diseases. They devote comparable attention to materials, biosafety itself, agriculture, and ecology, but show relatively limited interest in technology-related objects. Notably, emerging disciplines constitute the principal contributors to research on aquaculture-related objects. Substitute disciplines likewise address a wide spectrum of research objects, but unlike core and emerging disciplines, they place greater emphasis on biosafety itself, including protocols, legislation, and ethical considerations. According to the disciplinary knowledge-contribution classification, this category includes fields such as library and information science, history and philosophy of science, medical ethics, social issues, and agricultural economics and policy. These disciplines focus less on the mechanisms of disease or the creation of biological materials, and more on the social phenomena that shape the biosafety landscape. Consequently, substitute disciplines are more inclined toward research objects directly associated with biosafety as a conceptual and regulatory domain. Marginal disciplines, by contrast, engage with only seven categories of research objects. Given the limited data, no clear tendencies can be observed. Hybrid disciplines demonstrate a broad scope similar to the core and emerging groups, covering all research object types. Their attention is distributed relatively evenly between pests and diseases and materials, with comparatively less focus on food, aquaculture, and pharmaceutical-related objects. Taken together, these findings underscore the diversity and interdisciplinarity of research objects within the biosafety domain. Viewing research objects as a key lens through which to interpret interdisciplinary interactions offers a valuable approach to anticipating future hotspots and identifying the disciplines most likely to lead them. For instance, disciplines within the emerging category that advance aquaculture research, and those within the hybrid category that contribute to ecological studies, are well positioned to expand knowledge production, transcend their current classification, and ultimately establish themselves as core disciplines in the biosafety field. 2. Analysis of Research Methods in the Field of Biosafety The preceding results indicate that different disciplines direct varying levels of attention to specific research objects. To further examine whether research methods exhibit similar patterns, this study visualizes the relationship between disciplinary categories and research methods (Fig. 5). In the figure, the second column on the left represents knowledge-contributing discipline categories: type_1 denotes core disciplines, type_2 emerging disciplines, type_3 substitute disciplines, type_4 marginal disciplines, and mix_type hybrid disciplines comprising at least two distinct knowledge-contributing categories. The first column on the left indicates the level of methodological innovativeness. The third column, together with the fourth, represents the disciplinary domains to which methods belong, whereas third-column categories not linked to the fourth represent general and unknown categories. The results show that biosafety research employs methodologies from a broad array of disciplinary domains. Subsequently, this study examined the similarities and differences among disciplinary categories in their choice of research methods. The results reveal several commonalities: across core, emerging, substitute, marginal, and hybrid disciplines, domain-specific methods attract greater attention than general methods, and traditional approaches are favored over the development of new ones. Core disciplines employ the widest range of traditional methods while also contributing the largest number of methodological innovations. Hybrid disciplines rank second in terms of new method development, whereas emerging, substitute, and marginal disciplines have introduced relatively few novel approaches. The visualization of the relationship between disciplinary categories and research methods shows that core disciplines dominate across all methodological categories. This finding is consistent both with the original rationale for the disciplinary classification and with patterns of knowledge flow: core disciplines constitute the central actors in interdisciplinary biosafety research, contributing and citing the largest volume of knowledge. Hybrid disciplines, while drawing heavily on methodologies from the life sciences and medicine, also employ a comparatively higher proportion of natural science methods than other categories. Analysis further suggests that core and emerging disciplines serve as the two dominant contributors within the hybrid group. Combined with the observed focus of hybrid disciplines on material-related research objects, this indicates that they may frequently apply natural science methods to the study of materials. In addition, the linkages between the third and fourth columns reveal that, despite biosafety being an inherently interdisciplinary field encompassing a wide range of disciplines, the majority of studies rely primarily on specialized methodologies from the life sciences and medicine. This underscores that the field’s research focus remains firmly anchored in the life and medical sciences—a finding consistent with the actual state of the field (Renault et al., 2021). Overall, these analyses indicate that research methods in the biosafety field are highly diverse, spanning five major domains: life sciences and medicine, material sciences, social sciences, applied sciences, and the humanities and arts. In addition, widely applicable approaches such as reviews and systematic analyses are extensively employed. While traditional methods remain predominant, the field has also pursued methodological innovation, reflecting both the diversity of approaches and the strong interdisciplinarity characteristic of biosafety research. 3. Analysis of research themes in the field of biosafety In the biosafety domain, biosafety issues can be conceptualized as research themes. In this study, these issues were classified in accordance with the Biosafety Law of the People’s Republic of China (see supplement A, Table A1). Linking disciplinary categories with biosafety issue categories allows for the identification of thematic preferences across disciplines and the primary disciplines addressing each biosafety problem. Accordingly, this section examines the associations between disciplinary categories and biosafety issue categories, as illustrated in Fig. 6. In the figure, the first column on the left represents knowledge-contributing disciplinary categories: type_1 = core disciplines, type_2 = emerging disciplines, type_3 = substitute disciplines, type_4 = marginal disciplines, and mix_type = hybrid disciplines comprising at least two distinct knowledge-contributing categories. The results indicate that research themes in biosafety span multiple disciplinary domains. All disciplines exhibit heightened attention to biotechnology-related themes, likely due to the wide range of applications—including gene editing, nanomedicine, and cell technologies—that support studies on life processes, disease mechanisms, production of biological materials, and drug development. Consequently, biosafety in biotechnology has been extensively studied across all disciplines. Core and emerging disciplines show secondary emphasis on animal infectious diseases, whereas substitute disciplines focus primarily on human infectious diseases. Data for marginal disciplines are limited, making their thematic focus less apparent. Hybrid disciplines, while emphasizing animal infectious diseases, also demonstrate substantial attention to issues related to invasive species. Overall, with the exception of marginal disciplines, all categories exhibit broad engagement with diverse biosafety issues, reflecting the thematic diversity characteristic of research in the biosafety field. 4. Comprehensive analysis of interdisciplinary behavior in the field of biosafety In a single biosafety publication, research objects, research methods, and biosafety categories coexist. To explore the relationships among these three dimensions, this study visualized their associations (Fig. 7). The figure comprises five columns representing three types of categories: the first column (from the left) denotes biosafety categories, columns two through four represent a three-level classification of research methods in the biosafety field, and the fifth column corresponds to research object categories. Data from the first and second columns indicate that all types of research methods employ both field-specific and general methodologies, with a clear preference for field-specific methods in biosafety research. Notably, biosafety categories that currently attract considerable attention—such as biotechnology safety, human infectious diseases, animal infectious diseases, hybrid categories, and laboratory biosafety—show a relatively higher proportion of general method usage. This may be attributed to the abundant research accumulated in these areas and the availability of extensive data resources, enabling more comprehensive reviews, meta-analyses, and other integrative approaches. Consequently, these areas of biosafety research lend themselves to more multidimensional reviews and meta-analyses, which ultimately results in a greater application of general methods. The results further reveal that, for each type of research object, scholars employ both domain-specific and general methods, although domain-specific methods are generally preferred. However, when investigating biosafety itself, researchers are equally likely to adopt general or domain-specific methods. This pattern likely reflects the nature of biosafety research, which often focuses on non-material aspects such as principles, concepts, developmental trends, legislation, and protocols. Non-material research objects are typically composed of knowledge, concepts, or text, which increases the likelihood of applying general methods such as systematic reviews, meta-analyses, classification approaches, surveys, and other evaluative techniques. Additionally, the analysis shows that new methodological developments predominantly appear in the natural sciences and are applied to material-related research objects. This observation aligns with actual research practices in the field (Renault et al., 2021), further confirming the reliability of the methodology employed in this study. However, the above Sankey diagram cannot reveal which areas of research methods are applied to specific biosafety issues, nor can it clarify the distinctions among research objects across different biosafety domains. To further illuminate these details, this study constructed a Sankey diagram linking second-level research methods, biosafety categories, and biosafety research objects (Fig. 8). The results show that biosafety in biotechnology primarily focuses on research objects related to materials science, followed by technology, pests and pathogens, and life mechanisms. The dominant methods applied in this area derive from the life sciences and medicine as well as the physical sciences. Research on animal infectious diseases and related conditions primarily targets pest- and pathogen-related research objects, with secondary attention to agricultural research objects. These studies mainly employ methods from the life sciences and medicine. For example, parasitic infections on farms can cause significant economic losses in livestock production and may even infect humans. Addressing such issues requires life sciences and medical approaches to obtain species-level information on parasites, including biological characteristics and behavioral traits, which are essential for drug development and disease prevention. In addition, the treatment of animal infectious diseases also draws on methods from the social sciences. This likely reflects work by scholars who investigate farm biosafety issues and collect data through surveys of livestock farmers. Research on mixed biosafety issues tends to focus on pest- and pathogen-related objects but does not display clear methodological preferences. This is likely because pests and pathogens can involve humans, animals, and plants—for instance, zoonotic diseases—which encompass multiple types of biosafety problems. Such challenges often remain difficult to resolve or treat, thereby requiring collaborative application of diverse research methods. The remaining biosafety categories exhibit no distinctive features, instead comprising a mixture of diverse research objects and methods. This finding also illustrates that biosafety is inherently a complex, multidisciplinary, and integrative field, characterized by interdisciplinary interactions in research objects, methodologies, and research themes. The visualization provides an intuitive depiction of these interdisciplinary dynamics. The results further indicate that the principal research themes (issues) in biosafety include human infectious diseases, animal infectious diseases, plant infectious diseases, biotechnology safety, clinical biosafety, laboratory biosafety, genetic resource security, biological resource security, biodiversity, species invasion, antimicrobial resistance, bioterrorism, and biological weapons threats. Across these themes, scholars widely employ both general methods and domain-specific methods drawn from the life sciences and medicine, natural sciences, applied sciences, and social sciences. These methods are applied to investigate a broad spectrum of research objects, including agriculture, animals, plants, materials, biosafety, ethics, food, laboratories, medicine, aquatic products, reagents, pests, humans, cells, measures, technologies, biomolecules, and ecosystems. This study also visualized the research methods and research objects associated with the Others biosafety category (Fig. 9). The results indicate that this category employs both domain-specific and general research methods. The domain-specific approaches are concentrated in sociology and the life sciences and medicine, and are typically traditional in nature. Moreover, the Others category primarily addresses biosafety, agriculture, and pests. Research on biosafety and agriculture-related objects predominantly utilizes sociological methods, whereas studies on pest-related objects mainly rely on life sciences and medical methods. Agricultural biosafety has attracted not only broad scholarly attention but also increasing concern from national policymakers. As an integral component of agricultural development, agricultural biosafety deserves corresponding emphasis. 5. Fine-grained analysis of the interdisciplinary knowledge graph in the biosafety field Existing analyses of knowledge graphs remain relatively coarse, as current classification schemes are broad in scope and unable to capture interdisciplinary research at a finer level of granularity. To address this limitation, this study further excavates the biosafety interdisciplinary knowledge graph, with the aim of revealing research dynamics within specific subdomains. In practical contexts, the primary goal of biosafety is to prevent risks posed by diseases and biological agents (Renault et al., 2021). However, during the analysis of interdisciplinary patterns in the biosafety field, a small portion of research related to "physicochemical processes and products" was identified. To explore the reasons for the presence of such research objects in the biosafety domain, as well as the specific components included in "physicochemical processes and products," this study separately extracts the data corresponding to this category, in order to further investigate the interdisciplinary knowledge graph of the biosafety field. Based on the research object analysis method, a total of 710 articles related to research objects in the "physicochemical processes and products" category were collected. After applying DeepSeek-V3 for the interpretation and annotation of technical terms, it was found that the research objects in this category were primarily associated with chemistry and biochemistry, though a small number of physics-related terms were also present. Because these research objects contained a large number of interdisciplinary technical terms with highly similar annotated meanings, it was not feasible to classify them using word-vector-based methods such as k-means clustering or cosine similarity. Therefore, this study classified the research objects according to the annotation results generated by DeepSeek-V3. Ultimately, the "physicochemical processes and products" category was divided into six subcategories: chemical and biochemical reagents, chemical and biochemical products, chemical and biochemical processes, chemical and biochemical hazards, and physics-related research objects. To provide a more fine-grained perspective, further analysis was conducted on these six subcategories. The category of chemical and biochemical reagents encompasses a wide range of research objects used for diverse purposes, including contrast agents (Li et al., 2024), antimicrobials (X. Yang et al., 2022), pH indicators (Fathi et al., 2022), photosensitizers (Gu et al., 2022), disinfectants (Hasan et al., 2022), catalysts (Xu et al., 2022), and radioprotective agents (Zhou et al., 2023). These reagents are often closely associated with the prevention, diagnosis, and treatment of diseases. To examine the biosafety issues to which these reagents are related, as well as the research methods employed in relevant studies, this study conducted a visualization analysis of the biosafety categories and research methods associated with chemical and biochemical reagents within the "physicochemical processes and products" category (Fig. 10). In Fig. 10, the leftmost column represents biosafety categories, while the remaining columns denote categories of research methods. The results show that chemical and biochemical reagents are most strongly associated with biotechnology safety, followed by clinical biosafety, laboratory biosafety, animal infectious diseases, antimicrobial resistance, mixed biosafety types, human infectious diseases, and other biosafety categories. In contrast, their relevance to issues such as invasive species, biological resource security, bioweapons threats, biodiversity, and plant infectious diseases is relatively limited. This may be due to the broad application scope of chemical and biochemical reagents, which extends to biotechnology development, pharmaceutical research, clinical studies, and disease treatment, thereby linking them to biotechnology safety, clinical biosafety, animal and human infectious diseases, antimicrobial resistance, and other biosafety types. Furthermore, characteristics such as toxicity and volatility also connect these reagents to laboratory biosafety. With regard to choosing research methods, studies on chemical and biochemical reagents show a preference for domain-specific approaches, particularly methods from the natural sciences and the life sciences and medicine. Concurrently, many novel methods have been developed in this context, primarily new techniques for synthesizing or creating reagents. The domain-specific methods also included sociological approaches, which appear inconsistent with the field. Upon closer examination, however, five articles were identified that applied methods from the social sciences—such as qualitative pilot studies and expert evaluation—to investigate antimicrobial resistance in livestock and farming contexts. This finding further highlights the interdisciplinary nature of biosafety research and validates the fine-grained analytical capacity of the method employed in this study, demonstrating its ability to uncover otherwise overlooked knowledge in interdisciplinary research. Chemical and biochemical products encompass a wide range of substances, including chemical elements, chemical by-products, biochemical products, chemical metabolites, and compounds—non-reagent chemical materials generated in chemical or biological processes. These substances serve diverse purposes and are associated with a broad range of research themes. To investigate which biosafety issues these products are linked to and which research methods are employed, this study visualizes the associations between biosafety categories and research methods for chemical and biochemical products (Fig. 11). The results are largely consistent with those for chemical and biochemical reagents. Research on chemical and biochemical products shows the strongest association with biotechnology safety, followed by clinical biosafety, hybrid biosafety, human infectious diseases, laboratory biosafety, antimicrobial resistance, and other biosafety categories. In contrast, links to other biosafety issues are relatively limited. In terms of methodological choices, research on chemical and biochemical products—similar to that on chemical and biochemical reagents—tends to favor domain-specific methods, with substantial reliance on approaches from the natural sciences and the life sciences and medicine. Moreover, alongside the application of established natural science methods, numerous new methods have been developed, primarily focused on the synthesis or creation of new chemical or biochemical products. The category of chemical and biochemical hazards encompasses studies addressing the harmful properties of chemical or biochemical products, including issues such as chemical pollutants (X. Chen et al., 2022), chemical toxicity (El-Sherbiny et al., 2022), and chemical exposure (S.R. et al., 2023). Research in this area primarily focuses on laboratory biosafety and biotechnology safety, and typically employs traditional methods from the life sciences and medicine or the natural sciences. The category of chemical and biochemical processes includes investigations into various chemical and biochemical reactions, such as chemical immunotherapy based on Zn²⁺ chelation reactions (Y. Yang, Zhu, et al., 2023), removal of nitrogenous waste from water through nitrification/denitrification reactions (Preena et al., 2021), and studies on the toxicity generated by ozonation (Wei et al., 2021). These reactions are highly diverse and serve complex purposes: some contribute therapeutic benefits, while others produce by-products that may cause environmental pollution. The category of physics-related research objects examines the effects of physical factors, such as magnetic fields and near-infrared lasers, on biological systems. This research is largely situated within biotechnology safety, for example, demonstrating that extremely low-frequency electromagnetic fields may promote wound healing with favorable biosafety profiles (Saliev et al., 2014), and that near-infrared lasers show biosafety potential as a modality for photobiomodulation therapy (Khan et al., 2015). Overall, the field of biosafety encompasses numerous distinct disciplines, employs a variety of research methods, and addresses existing biosafety issues from multiple perspectives. Although the core focus of biosafety research is typically disease prevention and biological risk management, studies within the "physicochemical processes and products" category also constitute a notable proportion, reflecting the complexity of this field within the biosafety domain. To characterize the features of interdisciplinary research, this study classifies interdisciplinary studies based on research methods, research objects, and research themes, as illustrated in Fig. 12. In the figure, different colors represent different disciplinary themes, while the same color indicates the same disciplinary theme. The categories of interdisciplinary research are defined as follows: non-interdisciplinary, weakly interdisciplinary, moderately interdisciplinary, and highly interdisciplinary. Non-interdisciplinary research refers to studies in which the research objects, methods, and themes all belong to the same discipline; weakly interdisciplinary research refers to studies in which any two of the three components—research objects, methods, or themes—belong to the same discipline, while the third belongs to a different discipline; moderately interdisciplinary research refers to studies in which any one component belongs to a discipline, while the other two belong to other disciplines; and highly interdisciplinary research refers to studies in which research objects, methods, and themes all belong to different disciplines. It should be noted that distinguishing between weakly and moderately interdisciplinary research requires focusing on a specific discipline. Based on the analysis of interdisciplinary behavior in the biosafety field, this domain can be classified as a highly interdisciplinary area. Conclusion and future directions Interdisciplinary research behaviors help to clarify both the concrete pathways through which interdisciplinarity is implemented and the critical nodes at which it occurs. In this study, an interdisciplinary dataset was constructed based on the dimensions of research process, by integrating research objects, research methods, and research themes (categorized according to biosafety issues), together with commonly used metadata such as publication year and discipline. Using DeepSeek-V2 in combination with manual validation and annotation, a training dataset was rapidly developed. The LLaMA3.1-8-Chat model was then fine-tuned through the LoRA approach and prompt-based learning strategies to enable efficient identification and extraction of interdisciplinary research behaviors. Furthermore, a knowledge graph of interdisciplinary research in biosafety was constructed using Neo4j, accompanied by an interpretive analytical framework for its examination. By constructing an interdisciplinary knowledge graph with a fine-tuned large language model and developing an associated analytical framework, this study examines the characteristics of interdisciplinary research behaviors in the field of biosafety from the perspectives of research objects, research methods, and research themes (problems). The results demonstrate that interdisciplinarity is present across all three dimensions. Through a joint analysis of research materials (objects), methods, and themes (biosafety issue categories), the study further uncovers patterns of interdisciplinary research behaviors, tests their defining characteristics, and verifies both the effectiveness and applicability of the proposed analytical approach. These findings underscore the broad utility of this method for characterizing interdisciplinary behaviors. However, this paper also has certain limitations. First, in the method of characterizing interdisciplinary behaviors, the extraction of interdisciplinary data still requires improvement. Interdisciplinary research involves complex professional knowledge, and the writing styles of papers differ across disciplines and journals. Moreover, some studies do not mention research methods in their abstracts, titles, or keywords. Therefore, accurately extracting research methods and research objects is still challenging. In addition, accurately determining biosafety categories is also difficult, since such judgments require substantial expertise in biosafety. Although this paper has already provided training data for the large language model, some papers treat biosafety only as a research theme without actually studying or discussing specific biosafety issues, and under the condition of large-scale data, rapidly identifying such literature remains a challenge. Future studies may incorporate algorithms to model and analyze the transient states in the process of knowledge formation, and combine them with techniques such as theme recognition, semantic mining, in order to reveal the underlying evolution mechanisms of ideas and knowledge in further depth. Declarations Declaration of interests The authors declared that they have no conflicts of interest to this work. Author Contribution Conceptualization, Wang Xi, Li Dongqiao and Liu Xiwen; methodology, Wang Xi; Data collection and processing, Wang Xi; investigation, Wang Xi, Li Dongqiao and Liu Xiwen; visualization, Wang Xi; writing - original draft, Wang Xi and Li Dongqiao; writing-review & editing, Wang Xi, Li Dongqiao and Liu Xiwen; funding acquisition, resources, supervision, Li Dongqiao and Liu Xiwen. All authors contributed to the manuscript and approved the final version. Acknowledgements The authors want to thank Xinrui Wang for her efforts in the article modification. 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Interdisciplinary research: Connotation, measurement and impact. Science Research Management, 41(07), 279–288. Zhou, Y., Wang, Z., Pei, Y., Liu, L., Liu, C., Wang, C., & Hua, D. (2023). One-pot synthesis of ultra-stable polyvinylpyrrolidone-modified MnO2 nanoparticles for efficient radiation protection. Colloids and Surfaces B: Biointerfaces, 232, 113614. https://doi.org/10.1016/j.colsurfb.2023.113614 Additional Declarations No competing interests reported. Supplementary Files SupplementAtable.xlsx SupplementB.xlsx SupplementA.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8390102","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585506715,"identity":"0fce1f81-641a-4c6b-8505-f76fff11e7a6","order_by":0,"name":"Xi Wang","email":"","orcid":"","institution":"University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Wang","suffix":""},{"id":585506716,"identity":"049f2f83-1a50-4a13-afda-1e65890d2b18","order_by":1,"name":"Dongqiao 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4","display":"","copyAsset":false,"role":"figure","size":283265,"visible":true,"origin":"","legend":"\u003cp\u003eDisciplinary attention to different categories of research objects.\u003c/p\u003e\n\u003cp\u003eNote: type_1 = core disciplines; type_2 = emerging disciplines; type_3 = substitute disciplines; type_4 = marginal disciplines;mix_type = hybrid disciplines comprising at least two distinct categories of knowledge-contributing disciplines.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8390102/v1/06361e96031a18b31ac013c1.png"},{"id":102295873,"identity":"aba3e8f6-fd41-4c33-95c7-2f949484a41e","added_by":"auto","created_at":"2026-02-10 10:15:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":298617,"visible":true,"origin":"","legend":"\u003cp\u003eDisciplinary attention to different categories of research methods\u003c/p\u003e\n\u003cp\u003eNote: type_1 = core 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associations among research objects, research methods, and biosafety categories in the field of biosafety\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8390102/v1/20e51d5538384f3590ddd627.png"},{"id":102295961,"identity":"764a65dd-faf5-4a77-95b5-72e5c680380e","added_by":"auto","created_at":"2026-02-10 10:16:26","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":353548,"visible":true,"origin":"","legend":"\u003cp\u003eDetailed associations between research objects and research methods within the \"Other\" biosafety category\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8390102/v1/c4799aef57507406234510ee.png"},{"id":102296192,"identity":"cf2ac618-6f34-4980-a772-5e92b382260d","added_by":"auto","created_at":"2026-02-10 10:18:01","extension":"png","order_by":10,"title":"Figure 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challenges in science and society, as well as disruptive scientific breakthroughs, often require crossing disciplinary boundaries and integrating knowledge from multiple fields. Interdisciplinary research has thus gradually become an indispensable model for tackling grand challenges and achieving innovative breakthroughs (Lu Y X, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Zhang Lin et al., 2020). Interdisciplinarity is a research model undertaken by teams or individuals that integrates information, data, methods, tools, perspectives, concepts, and theories from two or more disciplines or professional knowledge communities. Its aim is to fundamentally deepen understanding or to solve problems that transcend the scope of a single discipline or field of practice (National Academy of Sciences et al., 2005). Scholars in China and abroad have analyzed the characteristics of interdisciplinarity from the perspectives of research materials/objects, research methods, and research themes. Zhang Lin (Zhang Lin et al., 2020) argue that when research approaches, methods, and tools from different disciplines are combined, the research object acquires characteristics of disciplinary diversity, and that this process represents the essence of interdisciplinarity. George (George J B, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) points out that interdisciplinary research establishes a framework of \"Concepts-Theories-Empirical Findings\" through the integration of different disciplinary perspectives, ultimately enabling the study of a given theme.\u003c/p\u003e \u003cp\u003eSuo (Suo C J \u0026amp; Xiao Y, 2023) distinguish between formal interdisciplinarity and substantive interdisciplinarity, suggesting that substantive interdisciplinarity\u0026mdash;formed through the integration of research content, sharing of methods, and the exchange and collision of perspectives across disciplines\u0026mdash;tends to be more structurally cohesive. Yan Bing (Yan B \u0026amp; Song Z L, 1996), based on the \"quadripartite classification\" and qualitative and quantitative differences in interdisciplinarity, identify three types: unitary interdisciplinarity, binary interdisciplinarity, and multiple interdisciplinarity. They further explain these types from the perspectives of research materials, research methods, and research content. Lu Yongxiang (Liu Z L, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) proposes that interdisciplinary science uses theories and methods from multiple disciplines to study complex objects, ultimately achieving scientific holism. Liu Zhonglin (Liu Z L, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) regards interdisciplinarity as the organic integration of theories or methods from different disciplines. Lawrence (Lawrence et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) provide a review of definitions of interdisciplinarity, suggesting that it involves the transfer and interaction of disciplinary methods, theories, and knowledge across different fields.\u003c/p\u003e \u003cp\u003eExisting research on the characteristics of interdisciplinarity mainly adopts perspectives such as citations, co-authorship, keywords, or subject terms. However, these approaches have low correspondence with the actual interdisciplinary process and thus struggle to reveal the internal mechanisms and patterns of interdisciplinarity. Only a limited number of scholars have analyzed the degree and development of interdisciplinarity from the perspectives of research methods and research objects. For example, Rafols (Rafols \u0026amp; Meyer, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) argue that the number of disciplines associated with the instruments mentioned in research methods can influence the level of interdisciplinarity. Chen (Y. Chen, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) points out that the mutual support among research methods such as the Internet of Things, cloud computing, big data processing, and artificial intelligence has created many interdisciplinary fields and promoted interdisciplinary development. Yang (Y. Yang, Zhang, et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) classify paradigms of interdisciplinarity driven by information processing and management technologies based on data objects, information objects, and computational methods. Wang Yuefen (Wang Y F et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), using data from the field of library and information science, studied themes such as \"Information\" and \"Big Data,\" finding that these research objects intersect with multiple disciplines including higher education, business economics, computer software and applications, as well as journalism and communication. Overall, however, there has been relatively little integrative research directly analyzing the interdisciplinary process from the perspectives of methods, objects, or themes. There is also a lack of fine-grained studies that jointly analyze interdisciplinarity characteristics, as well as studies that examine the correlations between methods, objects, and themes in interdisciplinary research.\u003c/p\u003e \u003cp\u003eThis paper defines the concept of Interdisciplinary Behavior, which encompasses research objects, methods, and themes (specifically the classification of biosafety issues) in the context of interdisciplinarity. By integrating commonly used data on interdisciplinary features\u0026mdash;such as publication time and disciplinary classifications\u0026mdash;a dataset for studying interdisciplinarity characteristics was constructed. Using DeepSeek-V2 combined with manual annotation, a training dataset was rapidly built. The LoRA (Low-Rank Adaptation) method, together with prompt learning strategies, was applied to fine-tune LLaMA3.1-8-Chat, enabling fast identification and extraction of interdisciplinary features. A Neo4j-based interdisciplinary knowledge graph was created, along with methods for interpreting this graph. The study analyzed the characteristics of interdisciplinary behaviors in the biosafety field, describing how interdisciplinarity manifests in research objects, research methods, and research themes. The findings demonstrate that interdisciplinarity exists across all three dimensions in biosafety research. This work provides a theoretical reference for retrieving and discerning interdisciplinarity studies, and offers a practical pathway for the rapid identification of interdisciplinary features and the efficient construction of interdisciplinary knowledge graphs.\u003c/p\u003e\n\u003ch3\u003eConcept and Definition of Interdisciplinary Behaviors\u003c/h3\u003e\n\u003cp\u003eInterdisciplinary Behaviors refers to the manner in which relevant elements are adopted during the process of interdisciplinary research, including themes, objects, methods, and tools from different disciplines. \"Behavior\" is generally defined as observable and measurable activities or responses exhibited by individuals within an external environment, characterized by objectivity and diversity. The elements of interdisciplinarity include research objects, methods, themes, approaches, and tools. Interdisciplinary research may be achieved by incorporating a single element from another discipline (e.g., a research method) and combining it with its own theories, concepts, or research themes. Alternatively, it may involve integrating multiple elements\u0026mdash;such as research methods and concepts\u0026mdash;from other disciplines alongside knowledge from the home discipline to achieve interdisciplinarity.\u003c/p\u003e \u003cp\u003eMeasuring and describing interdisciplinary behaviors help clarify the pathways by which interdisciplinarity is implemented and further reveals its underlying behavioral mechanisms and interdisciplinary patterns. Interdisciplinary behaviors use research themes, objects, methods, tools, and theories as entry points to explore the characteristics of interdisciplinary processes at each stage. By identifying how a given field incorporates interdisciplinarity in terms of research methods, themes, and objects, one can obtain the interdisciplinary behavioral characteristics of that field. The concept of interdisciplinary behavior provides a clear pathway for carrying out future interdisciplinary research, offering references for the organization of studies, selection of methods, and determination of research objects. Ultimately, it aids the orderly integration and collaborative development of knowledge across disciplines within the research process.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eOur study first constructs an interdisciplinary dataset, combining DeepSeek-V2 (DeepSeek-AI et al., 2024) with manual annotation to rapidly build a training dataset. The LoRA (Hu et al., 2021) (Low-Rank Adaptation) method, together with prompt learning strategies, is then applied to fine-tune a large language model (LLaMA3.1-8-Chat) (Hugging Face, n.d.) in order to enable the fast identification and extraction of process elements of interdisciplinarity. Using Neo4j, the extracted information\u0026mdash;including research objects, research methods, biosafety classifications, keywords, publication years, and WOSIDs\u0026mdash;was organized into a knowledge graph. Techniques including clustering were further applied to develop a knowledge graph-based method for analyzing interdisciplinarity, thereby providing methodological support for uncovering interdisciplinary behaviors. Figure\u0026nbsp;1 shows the technical roadmap.\u003c/p\u003e\n\u003ch3\u003e1. Data Collection\u003c/h3\u003e\n\u003cp\u003eThis study emplyed the Web of Science Core Collection - All as the data source. Biosafety-related keywords such as \u0026quot;\u003cem\u003ebiological safety, bio-safety, biosecurity, biological security, biology safety, bio safety, bio-security, biosaf*\u003c/em\u003e\u0026quot; were applied in Boolean search queries. A total of 19,191 research papers published between January 1900 and January 2024 were retrieved. To facilitate the analysis of the interdisciplinary knowledge graph, the classification of each paper was carried out using the disciplinary knowledge contribution role system proposed by Wang (Wang et al., 2025). After removing papers that were difficult to classify, a final set of 16,805 original papers was obtained.\u003c/p\u003e\n\u003cp\u003eSubsequently, abstracts, keywords, and other metadata of each paper were extracted in batches as the data source. Details of data screening and classification are provided in the supplementary file. Using a large language model, information such as abstracts, keywords, titles, publication dates, document types, JCR disciplines, and WOSID numbers was extracted from each paper. The complete information of one paper was recorded as one data entry.\u003c/p\u003e\n\u003ch3\u003e2. Fine tuning of the large language model\u003c/h3\u003e\n\u003cp\u003eDue to computational resource limitations, this study adopted the LLaMA3.1-8B-Chat (Hugging Face, n.d.) model combined with the LoRA (Hu et al., 2021) method for model fine-tuning. LoRA (Hu et al., 2021) is an efficient and flexible fine-tuning technique designed for pretrained models. Integrating LoRA (Hu et al., 2021) with prompt learning strategies allows for better handling of domain-specific complexity and specificity. Details regarding the model training dataset, testing dataset, validation methods, and fine-tuning results are provided in the supplementary file.\u003c/p\u003e\n\u003ch3\u003e3. Construction of the interdisciplinary knowledge graph\u003c/h3\u003e\n\u003cp\u003eThis study designed a quintuple structure for the interdisciplinary knowledge graph, consisting of: head entity, head entity category, relation, tail entity, and tail entity category, which were stored in Neo4j to construct the knowledge graph. The entities in the knowledge graph are classified into seven categories: JCR subject information, WOSID number, keyword information, publication year information, research object, research method, research theme classification. The research theme classification is based on the \u003cem\u003eBiosafety Law of the People\u0026rsquo;s Republic of China\u003c/em\u003e and includes:\u003c/p\u003e\n\u003cp\u003eHuman infectious diseases and illnesses, Animal infectious diseases and illnesses, Plant infectious diseases and illnesses, Biotechnology safety, Clinical biosafety, Laboratory biosafety, Genetic resource security, Biological resource security, Biodiversity, Species invasion, Antimicrobial resistance, Bioterrorism, Biological weapons threats, and Others. It is possible for a single article to involve multiple biosafety categories. Since document type is mainly used to help extract research methods, it is not stored in the knowledge graph.\u003c/p\u003e\n\u003cp\u003eFor all entities included in the knowledge graph, if multiple entities of the same category appear in a single paper, they are linked by a \u0026quot;co-occurrence\u0026quot; relation. For entities of different categories within the same paper, relations are defined as shown in Fig.\u0026nbsp;2. \u0026quot;Discipline\u0026quot; concerns \u0026quot;Biosafety Issue\u0026quot;; \u0026quot;Discipline\u0026quot; applies \u0026quot;Research Method\u0026quot;; \u0026quot;Discipline\u0026quot; focuses on \u0026quot;Research Object\u0026quot;; \u0026quot;Research Object\u0026quot; belongs to \u0026quot;Biosafety Issue\u0026quot;; and \u0026quot;Research Method\u0026quot; investigates \u0026quot;Biosafety Issue\u0026quot; and \u0026quot;Research Object.\u0026quot; To facilitate subsequent data management, links are also established between WOSID and \u0026quot;Year,\u0026quot; \u0026quot;Discipline,\u0026quot; and \u0026quot;Keywords.\u0026quot;\u003c/p\u003e\n\u003cp\u003eThe interdisciplinary knowledge graph provides a more intuitive perspective for describing the process of interdisciplinarity and helps improve the understanding of interdisciplinary behaviors.\u003c/p\u003e\n\u003cp\u003eIn Fig.\u0026nbsp;3, only 200 entities and relationships are displayed. Different colored nodes represent different types of entities, while the edges between nodes represent the relationships among them. Unlike traditional knowledge graphs, this graph incorporates a large volume of domain-specific knowledge from diverse fields, making it difficult to directly analyze using only the disciplinary categories of the literature. Therefore, this study develops a knowledge graph analysis method tailored for interdisciplinarity, and applies it to interpret the interdisciplinary knowledge graph. The detailed methodology is provided in the supplementary file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterdisciplinary Activities in the Field of Biosafety\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis of research objects in the field of biosafety\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eBiosafety research encompasses a wide range of objects, yet scholarly attention to these objects is uneven. Clarifying their categories and the extent to which they are studied is essential for understanding the interdisciplinary dynamics of the field. To this end, this study examines disciplinary engagement with different research objects, highlighting variations in emphasis across domains (Fig. 4). As shown in Fig. 4, knowledge-contributing disciplines are classified into five categories: core (type_1), emerging (type_2), substitute (type_3), marginal (type_4), and hybrid (mix_type), the latter integrating at least two types of contributing knowledge.\u003c/p\u003e\n\u003cp\u003eThe analysis reveals that core disciplines address the broadest range of research objects across multiple disciplines, with particular emphasis on pests and diseases, followed by materials, biosafety itself, agriculture, and technology. Food, ecology, and related objects attract comparatively less attention. Within the core group, fields such as Biotechnology \u0026amp; Applied Microbiology, Materials Science, Biomaterials, and Engineering, Biomedical advance research on materials, technologies, equipment, and tools, while Cell Biology, Immunology, Oncology, and Microbiology provide methodological and analytical frameworks for exploring pathogenic mechanisms and the theoretical foundations of life processes. Pharmacology \u0026amp; Pharmacy supports the development of therapeutic strategies, and Chemistry, Physical together with Chemistry, Multidisciplinary underpins work on chemical drug development, laboratory reagents, and the biosafety of chemistry-related products.\u003c/p\u003e\n\u003cp\u003eEmerging disciplines also engage broadly with nearly all categories of research objects, with the greatest emphasis on pests and diseases. They devote comparable attention to materials, biosafety itself, agriculture, and ecology, but show relatively limited interest in technology-related objects. Notably, emerging disciplines constitute the principal contributors to research on aquaculture-related objects. Substitute disciplines likewise address a wide spectrum of research objects, but unlike core and emerging disciplines, they place greater emphasis on biosafety itself, including protocols, legislation, and ethical considerations. According to the disciplinary knowledge-contribution classification, this category includes fields such as library and information science, history and philosophy of science, medical ethics, social issues, and agricultural economics and policy. These disciplines focus less on the mechanisms of disease or the creation of biological materials, and more on the social phenomena that shape the biosafety landscape. Consequently, substitute disciplines are more inclined toward research objects directly associated with biosafety as a conceptual and regulatory domain.\u003c/p\u003e\n\u003cp\u003eMarginal disciplines, by contrast, engage with only seven categories of research objects. Given the limited data, no clear tendencies can be observed. Hybrid disciplines demonstrate a broad scope similar to the core and emerging groups, covering all research object types. Their attention is distributed relatively evenly between pests and diseases and materials, with comparatively less focus on food, aquaculture, and pharmaceutical-related objects.\u003c/p\u003e\n\u003cp\u003eTaken together, these findings underscore the diversity and interdisciplinarity of research objects within the biosafety domain. Viewing research objects as a key lens through which to interpret interdisciplinary interactions offers a valuable approach to anticipating future hotspots and identifying the disciplines most likely to lead them. For instance, disciplines within the emerging category that advance aquaculture research, and those within the hybrid category that contribute to ecological studies, are well positioned to expand knowledge production, transcend their current classification, and ultimately establish themselves as core disciplines in the biosafety field.\u003c/p\u003e\n\u003ch3\u003e2. Analysis of Research Methods in the Field of Biosafety\u003c/h3\u003e\n\u003cp\u003eThe preceding results indicate that different disciplines direct varying levels of attention to specific research objects. To further examine whether research methods exhibit similar patterns, this study visualizes the relationship between disciplinary categories and research methods (Fig. 5). In the figure, the second column on the left represents knowledge-contributing discipline categories: type_1 denotes core disciplines, type_2 emerging disciplines, type_3 substitute disciplines, type_4 marginal disciplines, and mix_type hybrid disciplines comprising at least two distinct knowledge-contributing categories. The first column on the left indicates the level of methodological innovativeness. The third column, together with the fourth, represents the disciplinary domains to which methods belong, whereas third-column categories not linked to the fourth represent general and unknown categories. The results show that biosafety research employs methodologies from a broad array of disciplinary domains.\u003c/p\u003e\n\u003cp\u003eSubsequently, this study examined the similarities and differences among disciplinary categories in their choice of research methods. The results reveal several commonalities: across core, emerging, substitute, marginal, and hybrid disciplines, domain-specific methods attract greater attention than general methods, and traditional approaches are favored over the development of new ones. Core disciplines employ the widest range of traditional methods while also contributing the largest number of methodological innovations. Hybrid disciplines rank second in terms of new method development, whereas emerging, substitute, and marginal disciplines have introduced relatively few novel approaches.\u003c/p\u003e\n\u003cp\u003eThe visualization of the relationship between disciplinary categories and research methods shows that core disciplines dominate across all methodological categories. This finding is consistent both with the original rationale for the disciplinary classification and with patterns of knowledge flow: core disciplines constitute the central actors in interdisciplinary biosafety research, contributing and citing the largest volume of knowledge. Hybrid disciplines, while drawing heavily on methodologies from the life sciences and medicine, also employ a comparatively higher proportion of natural science methods than other categories. Analysis further suggests that core and emerging disciplines serve as the two dominant contributors within the hybrid group. Combined with the observed focus of hybrid disciplines on material-related research objects, this indicates that they may frequently apply natural science methods to the study of materials. In addition, the linkages between the third and fourth columns reveal that, despite biosafety being an inherently interdisciplinary field encompassing a wide range of disciplines, the majority of studies rely primarily on specialized methodologies from the life sciences and medicine. This underscores that the field\u0026rsquo;s research focus remains firmly anchored in the life and medical sciences\u0026mdash;a finding consistent with the actual state of the field (Renault et al., 2021).\u003c/p\u003e\n\u003cp\u003eOverall, these analyses indicate that research methods in the biosafety field are highly diverse, spanning five major domains: life sciences and medicine, material sciences, social sciences, applied sciences, and the humanities and arts. In addition, widely applicable approaches such as reviews and systematic analyses are extensively employed. While traditional methods remain predominant, the field has also pursued methodological innovation, reflecting both the diversity of approaches and the strong interdisciplinarity characteristic of biosafety research.\u003c/p\u003e\n\u003ch3\u003e3. Analysis of research themes in the field of biosafety\u003c/h3\u003e\n\u003cp\u003eIn the biosafety domain, biosafety issues can be conceptualized as research themes. In this study, these issues were classified in accordance with the \u003cem\u003eBiosafety Law of the People\u0026rsquo;s Republic of China\u003c/em\u003e (see supplement A, Table A1). Linking disciplinary categories with biosafety issue categories allows for the identification of thematic preferences across disciplines and the primary disciplines addressing each biosafety problem. Accordingly, this section examines the associations between disciplinary categories and biosafety issue categories, as illustrated in Fig. 6. In the figure, the first column on the left represents knowledge-contributing disciplinary categories: type_1\u0026thinsp;=\u0026thinsp;core disciplines, type_2\u0026thinsp;=\u0026thinsp;emerging disciplines, type_3\u0026thinsp;=\u0026thinsp;substitute disciplines, type_4\u0026thinsp;=\u0026thinsp;marginal disciplines, and mix_type\u0026thinsp;=\u0026thinsp;hybrid disciplines comprising at least two distinct knowledge-contributing categories.\u003c/p\u003e\n\u003cp\u003eThe results indicate that research themes in biosafety span multiple disciplinary domains. All disciplines exhibit heightened attention to biotechnology-related themes, likely due to the wide range of applications\u0026mdash;including gene editing, nanomedicine, and cell technologies\u0026mdash;that support studies on life processes, disease mechanisms, production of biological materials, and drug development. Consequently, biosafety in biotechnology has been extensively studied across all disciplines. Core and emerging disciplines show secondary emphasis on animal infectious diseases, whereas substitute disciplines focus primarily on human infectious diseases. Data for marginal disciplines are limited, making their thematic focus less apparent. Hybrid disciplines, while emphasizing animal infectious diseases, also demonstrate substantial attention to issues related to invasive species. Overall, with the exception of marginal disciplines, all categories exhibit broad engagement with diverse biosafety issues, reflecting the thematic diversity characteristic of research in the biosafety field.\u003c/p\u003e\n\u003ch3\u003e4. Comprehensive analysis of interdisciplinary behavior in the field of biosafety\u003c/h3\u003e\n\u003cp\u003eIn a single biosafety publication, research objects, research methods, and biosafety categories coexist. To explore the relationships among these three dimensions, this study visualized their associations (Fig.\u0026nbsp;7). The figure comprises five columns representing three types of categories: the first column (from the left) denotes biosafety categories, columns two through four represent a three-level classification of research methods in the biosafety field, and the fifth column corresponds to research object categories. Data from the first and second columns indicate that all types of research methods employ both field-specific and general methodologies, with a clear preference for field-specific methods in biosafety research. Notably, biosafety categories that currently attract considerable attention\u0026mdash;such as biotechnology safety, human infectious diseases, animal infectious diseases, hybrid categories, and laboratory biosafety\u0026mdash;show a relatively higher proportion of general method usage. This may be attributed to the abundant research accumulated in these areas and the availability of extensive data resources, enabling more comprehensive reviews, meta-analyses, and other integrative approaches. Consequently, these areas of biosafety research lend themselves to more multidimensional reviews and meta-analyses, which ultimately results in a greater application of general methods.\u003c/p\u003e\n\u003cp\u003eThe results further reveal that, for each type of research object, scholars employ both domain-specific and general methods, although domain-specific methods are generally preferred. However, when investigating biosafety itself, researchers are equally likely to adopt general or domain-specific methods. This pattern likely reflects the nature of biosafety research, which often focuses on non-material aspects such as principles, concepts, developmental trends, legislation, and protocols. Non-material research objects are typically composed of knowledge, concepts, or text, which increases the likelihood of applying general methods such as systematic reviews, meta-analyses, classification approaches, surveys, and other evaluative techniques. Additionally, the analysis shows that new methodological developments predominantly appear in the natural sciences and are applied to material-related research objects. This observation aligns with actual research practices in the field (Renault et al., 2021), further confirming the reliability of the methodology employed in this study.\u003c/p\u003e\n\u003cp\u003eHowever, the above Sankey diagram cannot reveal which areas of research methods are applied to specific biosafety issues, nor can it clarify the distinctions among research objects across different biosafety domains. To further illuminate these details, this study constructed a Sankey diagram linking second-level research methods, biosafety categories, and biosafety research objects (Fig.\u0026nbsp;8). The results show that biosafety in biotechnology primarily focuses on research objects related to materials science, followed by technology, pests and pathogens, and life mechanisms. The dominant methods applied in this area derive from the life sciences and medicine as well as the physical sciences. Research on animal infectious diseases and related conditions primarily targets pest- and pathogen-related research objects, with secondary attention to agricultural research objects. These studies mainly employ methods from the life sciences and medicine. For example, parasitic infections on farms can cause significant economic losses in livestock production and may even infect humans. Addressing such issues requires life sciences and medical approaches to obtain species-level information on parasites, including biological characteristics and behavioral traits, which are essential for drug development and disease prevention.\u003c/p\u003e\n\u003cp\u003eIn addition, the treatment of animal infectious diseases also draws on methods from the social sciences. This likely reflects work by scholars who investigate farm biosafety issues and collect data through surveys of livestock farmers. Research on mixed biosafety issues tends to focus on pest- and pathogen-related objects but does not display clear methodological preferences. This is likely because pests and pathogens can involve humans, animals, and plants\u0026mdash;for instance, zoonotic diseases\u0026mdash;which encompass multiple types of biosafety problems. Such challenges often remain difficult to resolve or treat, thereby requiring collaborative application of diverse research methods.\u003c/p\u003e\n\u003cp\u003eThe remaining biosafety categories exhibit no distinctive features, instead comprising a mixture of diverse research objects and methods. This finding also illustrates that biosafety is inherently a complex, multidisciplinary, and integrative field, characterized by interdisciplinary interactions in research objects, methodologies, and research themes. The visualization provides an intuitive depiction of these interdisciplinary dynamics. The results further indicate that the principal research themes (issues) in biosafety include human infectious diseases, animal infectious diseases, plant infectious diseases, biotechnology safety, clinical biosafety, laboratory biosafety, genetic resource security, biological resource security, biodiversity, species invasion, antimicrobial resistance, bioterrorism, and biological weapons threats. Across these themes, scholars widely employ both general methods and domain-specific methods drawn from the life sciences and medicine, natural sciences, applied sciences, and social sciences. These methods are applied to investigate a broad spectrum of research objects, including agriculture, animals, plants, materials, biosafety, ethics, food, laboratories, medicine, aquatic products, reagents, pests, humans, cells, measures, technologies, biomolecules, and ecosystems.\u003c/p\u003e\n\u003cp\u003eThis study also visualized the research methods and research objects associated with the Others biosafety category (Fig.\u0026nbsp;9). The results indicate that this category employs both domain-specific and general research methods. The domain-specific approaches are concentrated in sociology and the life sciences and medicine, and are typically traditional in nature. Moreover, the Others category primarily addresses biosafety, agriculture, and pests. Research on biosafety and agriculture-related objects predominantly utilizes sociological methods, whereas studies on pest-related objects mainly rely on life sciences and medical methods. Agricultural biosafety has attracted not only broad scholarly attention but also increasing concern from national policymakers. As an integral component of agricultural development, agricultural biosafety deserves corresponding emphasis.\u003c/p\u003e\n\u003ch3\u003e5. Fine-grained analysis of the interdisciplinary knowledge graph in the biosafety field\u003c/h3\u003e\n\u003cp\u003eExisting analyses of knowledge graphs remain relatively coarse, as current classification schemes are broad in scope and unable to capture interdisciplinary research at a finer level of granularity. To address this limitation, this study further excavates the biosafety interdisciplinary knowledge graph, with the aim of revealing research dynamics within specific subdomains. In practical contexts, the primary goal of biosafety is to prevent risks posed by diseases and biological agents (Renault et al., 2021). However, during the analysis of interdisciplinary patterns in the biosafety field, a small portion of research related to \u0026quot;physicochemical processes and products\u0026quot; was identified. To explore the reasons for the presence of such research objects in the biosafety domain, as well as the specific components included in \u0026quot;physicochemical processes and products,\u0026quot; this study separately extracts the data corresponding to this category, in order to further investigate the interdisciplinary knowledge graph of the biosafety field.\u003c/p\u003e\n\u003cp\u003eBased on the research object analysis method, a total of 710 articles related to research objects in the \u0026quot;physicochemical processes and products\u0026quot; category were collected. After applying DeepSeek-V3 for the interpretation and annotation of technical terms, it was found that the research objects in this category were primarily associated with chemistry and biochemistry, though a small number of physics-related terms were also present. Because these research objects contained a large number of interdisciplinary technical terms with highly similar annotated meanings, it was not feasible to classify them using word-vector-based methods such as k-means clustering or cosine similarity. Therefore, this study classified the research objects according to the annotation results generated by DeepSeek-V3. Ultimately, the \u0026quot;physicochemical processes and products\u0026quot; category was divided into six subcategories: chemical and biochemical reagents, chemical and biochemical products, chemical and biochemical processes, chemical and biochemical hazards, and physics-related research objects. To provide a more fine-grained perspective, further analysis was conducted on these six subcategories.\u003c/p\u003e\n\u003cp\u003eThe category of chemical and biochemical reagents encompasses a wide range of research objects used for diverse purposes, including contrast agents (Li et al., 2024), antimicrobials (X. Yang et al., 2022), pH indicators (Fathi et al., 2022), photosensitizers (Gu et al., 2022), disinfectants (Hasan et al., 2022), catalysts (Xu et al., 2022), and radioprotective agents (Zhou et al., 2023). These reagents are often closely associated with the prevention, diagnosis, and treatment of diseases. To examine the biosafety issues to which these reagents are related, as well as the research methods employed in relevant studies, this study conducted a visualization analysis of the biosafety categories and research methods associated with chemical and biochemical reagents within the \u0026quot;physicochemical processes and products\u0026quot; category (Fig.\u0026nbsp;10). In Fig.\u0026nbsp;10, the leftmost column represents biosafety categories, while the remaining columns denote categories of research methods.\u003c/p\u003e\n\u003cp\u003eThe results show that chemical and biochemical reagents are most strongly associated with biotechnology safety, followed by clinical biosafety, laboratory biosafety, animal infectious diseases, antimicrobial resistance, mixed biosafety types, human infectious diseases, and other biosafety categories. In contrast, their relevance to issues such as invasive species, biological resource security, bioweapons threats, biodiversity, and plant infectious diseases is relatively limited. This may be due to the broad application scope of chemical and biochemical reagents, which extends to biotechnology development, pharmaceutical research, clinical studies, and disease treatment, thereby linking them to biotechnology safety, clinical biosafety, animal and human infectious diseases, antimicrobial resistance, and other biosafety types. Furthermore, characteristics such as toxicity and volatility also connect these reagents to laboratory biosafety.\u003c/p\u003e\n\u003cp\u003eWith regard to choosing research methods, studies on chemical and biochemical reagents show a preference for domain-specific approaches, particularly methods from the natural sciences and the life sciences and medicine. Concurrently, many novel methods have been developed in this context, primarily new techniques for synthesizing or creating reagents. The domain-specific methods also included sociological approaches, which appear inconsistent with the field. Upon closer examination, however, five articles were identified that applied methods from the social sciences\u0026mdash;such as qualitative pilot studies and expert evaluation\u0026mdash;to investigate antimicrobial resistance in livestock and farming contexts. This finding further highlights the interdisciplinary nature of biosafety research and validates the fine-grained analytical capacity of the method employed in this study, demonstrating its ability to uncover otherwise overlooked knowledge in interdisciplinary research.\u003c/p\u003e\n\u003cp\u003eChemical and biochemical products encompass a wide range of substances, including chemical elements, chemical by-products, biochemical products, chemical metabolites, and compounds\u0026mdash;non-reagent chemical materials generated in chemical or biological processes. These substances serve diverse purposes and are associated with a broad range of research themes. To investigate which biosafety issues these products are linked to and which research methods are employed, this study visualizes the associations between biosafety categories and research methods for chemical and biochemical products (Fig.\u0026nbsp;11). The results are largely consistent with those for chemical and biochemical reagents. Research on chemical and biochemical products shows the strongest association with biotechnology safety, followed by clinical biosafety, hybrid biosafety, human infectious diseases, laboratory biosafety, antimicrobial resistance, and other biosafety categories. In contrast, links to other biosafety issues are relatively limited.\u003c/p\u003e\n\u003cp\u003eIn terms of methodological choices, research on chemical and biochemical products\u0026mdash;similar to that on chemical and biochemical reagents\u0026mdash;tends to favor domain-specific methods, with substantial reliance on approaches from the natural sciences and the life sciences and medicine. Moreover, alongside the application of established natural science methods, numerous new methods have been developed, primarily focused on the synthesis or creation of new chemical or biochemical products.\u003c/p\u003e\n\u003cp\u003eThe category of chemical and biochemical hazards encompasses studies addressing the harmful properties of chemical or biochemical products, including issues such as chemical pollutants (X. Chen et al., 2022), chemical toxicity (El-Sherbiny et al., 2022), and chemical exposure (S.R. et al., 2023). Research in this area primarily focuses on laboratory biosafety and biotechnology safety, and typically employs traditional methods from the life sciences and medicine or the natural sciences. The category of chemical and biochemical processes includes investigations into various chemical and biochemical reactions, such as chemical immunotherapy based on Zn\u0026sup2;⁺ chelation reactions (Y. Yang, Zhu, et al., 2023), removal of nitrogenous waste from water through nitrification/denitrification reactions (Preena et al., 2021), and studies on the toxicity generated by ozonation (Wei et al., 2021). These reactions are highly diverse and serve complex purposes: some contribute therapeutic benefits, while others produce by-products that may cause environmental pollution. The category of physics-related research objects examines the effects of physical factors, such as magnetic fields and near-infrared lasers, on biological systems. This research is largely situated within biotechnology safety, for example, demonstrating that extremely low-frequency electromagnetic fields may promote wound healing with favorable biosafety profiles (Saliev et al., 2014), and that near-infrared lasers show biosafety potential as a modality for photobiomodulation therapy (Khan et al., 2015).\u003c/p\u003e\n\u003cp\u003eOverall, the field of biosafety encompasses numerous distinct disciplines, employs a variety of research methods, and addresses existing biosafety issues from multiple perspectives. Although the core focus of biosafety research is typically disease prevention and biological risk management, studies within the \u0026quot;physicochemical processes and products\u0026quot; category also constitute a notable proportion, reflecting the complexity of this field within the biosafety domain.\u003c/p\u003e\n\u003cp\u003eTo characterize the features of interdisciplinary research, this study classifies interdisciplinary studies based on research methods, research objects, and research themes, as illustrated in Fig.\u0026nbsp;12. In the figure, different colors represent different disciplinary themes, while the same color indicates the same disciplinary theme. The categories of interdisciplinary research are defined as follows: non-interdisciplinary, weakly interdisciplinary, moderately interdisciplinary, and highly interdisciplinary. Non-interdisciplinary research refers to studies in which the research objects, methods, and themes all belong to the same discipline; weakly interdisciplinary research refers to studies in which any two of the three components\u0026mdash;research objects, methods, or themes\u0026mdash;belong to the same discipline, while the third belongs to a different discipline; moderately interdisciplinary research refers to studies in which any one component belongs to a discipline, while the other two belong to other disciplines; and highly interdisciplinary research refers to studies in which research objects, methods, and themes all belong to different disciplines. It should be noted that distinguishing between weakly and moderately interdisciplinary research requires focusing on a specific discipline. Based on the analysis of interdisciplinary behavior in the biosafety field, this domain can be classified as a highly interdisciplinary area.\u003c/p\u003e"},{"header":"Conclusion and future directions","content":"\u003cp\u003eInterdisciplinary research behaviors help to clarify both the concrete pathways through which interdisciplinarity is implemented and the critical nodes at which it occurs. In this study, an interdisciplinary dataset was constructed based on the dimensions of research process, by integrating research objects, research methods, and research themes (categorized according to biosafety issues), together with commonly used metadata such as publication year and discipline. Using DeepSeek-V2 in combination with manual validation and annotation, a training dataset was rapidly developed. The LLaMA3.1-8-Chat model was then fine-tuned through the LoRA approach and prompt-based learning strategies to enable efficient identification and extraction of interdisciplinary research behaviors. Furthermore, a knowledge graph of interdisciplinary research in biosafety was constructed using Neo4j, accompanied by an interpretive analytical framework for its examination.\u003c/p\u003e \u003cp\u003eBy constructing an interdisciplinary knowledge graph with a fine-tuned large language model and developing an associated analytical framework, this study examines the characteristics of interdisciplinary research behaviors in the field of biosafety from the perspectives of research objects, research methods, and research themes (problems). The results demonstrate that interdisciplinarity is present across all three dimensions. Through a joint analysis of research materials (objects), methods, and themes (biosafety issue categories), the study further uncovers patterns of interdisciplinary research behaviors, tests their defining characteristics, and verifies both the effectiveness and applicability of the proposed analytical approach. These findings underscore the broad utility of this method for characterizing interdisciplinary behaviors.\u003c/p\u003e \u003cp\u003eHowever, this paper also has certain limitations. First, in the method of characterizing interdisciplinary behaviors, the extraction of interdisciplinary data still requires improvement. Interdisciplinary research involves complex professional knowledge, and the writing styles of papers differ across disciplines and journals. Moreover, some studies do not mention research methods in their abstracts, titles, or keywords. Therefore, accurately extracting research methods and research objects is still challenging. In addition, accurately determining biosafety categories is also difficult, since such judgments require substantial expertise in biosafety. Although this paper has already provided training data for the large language model, some papers treat biosafety only as a research theme without actually studying or discussing specific biosafety issues, and under the condition of large-scale data, rapidly identifying such literature remains a challenge. Future studies may incorporate algorithms to model and analyze the transient states in the process of knowledge formation, and combine them with techniques such as theme recognition, semantic mining, in order to reveal the underlying evolution mechanisms of ideas and knowledge in further depth.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of interests\u003c/h2\u003e \u003cp\u003eThe authors declared that they have no conflicts of interest to this work.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, Wang Xi, Li Dongqiao and Liu Xiwen; methodology, Wang Xi; Data collection and processing, Wang Xi; investigation, Wang Xi, Li Dongqiao and Liu Xiwen; visualization, Wang Xi; writing - original draft, Wang Xi and Li Dongqiao; writing-review \u0026amp; editing, Wang Xi, Li Dongqiao and Liu Xiwen; funding acquisition, resources, supervision, Li Dongqiao and Liu Xiwen. All authors contributed to the manuscript and approved the final version.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors want to thank Xinrui Wang for her efforts in the article modification. The work was funded by the National Social Science Fund of China (24BTQ046), the Youth Innovation Promotion Association for Chinese Academy of Science (E329040901), and the Youth Talent Program of the National Science Library, Chinese Academy of Sciences (E555040201).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen, X., Tao, G., Wang, Y., Wei, W., Lian, X., Shi, Y., Chen, S., \u0026amp; Sun, Y. (2022). Interactive impacts of microplastics and chlorine on biological stability and microbial community formation in stagnant water. 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Colloids and Surfaces B: Biointerfaces, 232, 113614. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.colsurfb.2023.113614\u003c/span\u003e\u003cspan address=\"10.1016/j.colsurfb.2023.113614\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Biosafety, Research Behaviors, Interdisciplinary Research, Large Language Model","lastPublishedDoi":"10.21203/rs.3.rs-8390102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8390102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe deployment of scientific research projects through interdisciplinary models has become a consensus and is increasingly seen as an important approach to addressing major scientific and societal issues. The process of interdisciplinarity involves combining research materials, methods, themes, theories, and tools to achieve the integration of knowledge across disciplines. However, only a limited number of works have conducted bibliometric analyses of interdisciplinarity from the perspective of the interdisciplinary process itself. This paper defines the interdisciplinary research process as Interdisciplinary Behaviors. By analyzing those behaviors, it seeks to reveal the characteristics of interdisciplinarity. A fine-tuned large language model (LLM) is employed to construct a disciplinary knowledge graph, supporting research on interdisciplinary behaviors. Focusing on the field of Biosafety, the study quantitatively analyzes interdisciplinary behaviors from three perspectives: research materials, research methods, and research themes. It uncovers the internal behavioral processes and pathways of interdisciplinarity, aiming to provide a theoretical foundation and research tools for dissecting interdisciplinary phenomena, as well as a reference for describing interdisciplinary behaviors in the biosafety domain.\u003c/p\u003e","manuscriptTitle":"Study on Interdisciplinary Research Behaviors in the Biosafety","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-06 20:04:02","doi":"10.21203/rs.3.rs-8390102/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a672d77c-d6ba-4a22-bfe2-1df602cb06f7","owner":[],"postedDate":"February 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T14:39:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-06 20:04:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8390102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8390102","identity":"rs-8390102","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}