Knowledge Library Research Articles

Analysis of knowledge services efficiency and influencing factors of public libraries in China: a mixed study based on the SBM model and dynamic QCA

PurposeThe core objective of this study is to provide an in-depth quantitative assessment of the efficiency of public library knowledge services (PLKS) in China and to scrutinize the factors that have a significant impact on the efficiency of PLKS. Furthermore, this study also aims to examine the characteristics and evolving patterns of PLKS in China and to propose strategies for enhancing the quality of services provided by public libraries. The findings of this paper are expected to provide valuable references for current academic research and practice areas, guiding and promoting exploration and development in related fields.Design/methodology/approachTo analyse and evaluate the operation mechanism and efficiency of PLKS, this study creatively constructs a multi-stage PLKS efficiency evaluation model and provides related indicators. Based on this process, the super-efficiency network slacks-based measure model was used to analyse the efficiency, and dynamic qualitative comparative analysis was adopted to analyse the recipes about the influencing factors of PLKS. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.FindingsIn the first stage, PLKS in China meets the basic requirements, but in the second stage, there is evident resource wastage. In addition, there are five recipes in PLKS of China. These five recipes reveal the configuration relationship between the factors that affect PLKS. The results show that PLKS in China are different in different regions, and the effects of the influencing factors are also different.Originality/valueIn this study, the authors provide an exhaustive deconstruction and interpretation of PLKS, thereby proposing a three-stage PLKS efficiency conversion process. Furthermore, the authors have identified a set of readily accessible and quantifiable indicators. It is worth emphasizing that the authors have taken a unique approach to analyse the elements affecting PLKS from the perspective of configuration, which has significantly broadened the boundaries and depth of PLKS research.

Linking Between Molecular and Biodiversity Data: A BiCIKL Perspective

Molecular sequencing data generation is being driven by global and regional efforts to discover, understand and monitor biodiversity. To fully explore this data in biodiversity research we need a network of connected data resources, linking sequence data with natural history collections, taxonomy and literature. The BiCIKL project (Biodiversity Community Integrated Knowledge Library, Penev et al. 2022) has set the groundwork towards creating this network of linked data and fostering FAIR (Findable, Accessible, Interoperable and Reusable) practices in the biodiversity domain. Connecting biodiversity and molecular data along the biodiversity research cycle requires a foundation of well-structured and rich metadata in the molecular sequence databases. Referencing the physical specimens is important as this provides context about the source of the material that was used for generating the molecular sequence data, including information about origin and species identification. To connect biodiversity and molecular data, we developed tools and workflows for improving and standardising metadata, federated searches and validations for specimen reference in sequence data, such as the SpASe tool, which enables the discovery of links between natural history collections and sequences, and the European Nucleotide Archive Source Attribute Helper API, which facilitates the construction of specimen attributes in a structured format. This work was done in close collaboration with DiSSCo (Distributed System of Scientific Collections) and some biodiversity genomics projects (e.g. Biodiversity Genomics Europe, BGE). Furthermore, we enabled community curation of biological source annotations such as specimen references in sequence data through the PlutoF platform and the ELIXIR Contextual Data Clearinghouse (Abarenkov et al. 2021, Balavenkataraman Kadhirvelu et al. 2022) and increased bidirectional linking from sequences in the European Nucleotide Archive (ENA) to collections, taxonomy and literature services (e.g., Plazi TreatmentBank, OpenBioDiv). We also worked closely with the community to enable the structured publication of environmental DNA data, promoting and engaging in the definition of standards and developing tools to facilitate data deposition and retrieval. Overall, the project has contributed significantly to strengthen the connections between the biodiversity and genomics communities towards higher data integration and interoperability. Structured, enriched, accessible and linked sequence data will provide a strong foundation for the application of biodiversity knowledge in the response to global challenges, such as biodiversity loss, ecosystem change and food security. Beyond BiCIKL, we will continue our work as a community to promote a culture of FAIR linked molecular data, towards a fully integrated biodiversity knowledge ecosystem.

Beyond BiCIKL: Towards Building an AI-Assisted “Biodiversity Supergraph”

BiCIKL (Biodiversity Community Integrated Knowledge Library) is a European Union (EU) Horizon 2020 project (2021–2024) building a new community of research infrastructures (RIs), researchers and other stakeholders, through improved access to interlinked, open and FAIR (Findable, Accessible, Interoperable, Reusable) biodiversity data along the biodiversity research cycle (specimens, sequences, taxon names, publications) (Penev et al. 2022). The project’s 14 partners developed or substantially improved 16 tools and services currently in process of onboarding to the European Open Science Cloud (EOSC), presented in the FAIR Data Place (FDP) of BiCIKL’s flagship product, the Biodiversity Knowledge Hub (BKH). The tools and data were used in Open Call projects, performed by research groups worldwide. A key achievement of BiCIKL is the establishment of several new bi-directional links between the participating RIs through shared and interoperable data standards and web services. The sustainability of the BiCIKL services and especially of the strong collaborative spirit developed through the project will be ensured by a membership agreement for the BKH maintenance and further development. The results of BiCIKL are diverse and tackle various aspects of the implementation of open science practices in biodiversity research. The project partners and external collaborators from the Open Call projects published more than 80 papers and conference abstracts (see the article collections in Penev et al. 2022a and Thessen et al. 2023), two policy briefs (Penev et al. 2024, Agosti et al. 2024), three Biodiversity Information Science (TDWG) symposia (2021, 2023, 2024), several videos and factsheets and other training materials, guidelines and best practice recommendations, and so on. In the special focus of BiCIKL was the extraction and liberation of data from the PDFs of several thousands of published biodiversity articles making it accessible and re-usable. The new BiCIKL community proved to be successful in both technological innovation and long-lasting spirit of collaboration between biodiversity and genomics researchers, data repositories, RIs, publishers and other stakeholders. Beyond BiCIKL, we envisage our work towards further integration and interoperability between data domains by embracing human-in-the-loop collaborations, enhanced by Artificial Intelligence (AI). The implementation of AI and Large Language Models (LLM) should be possible when considering an important condition: to understand the complexity of past, recent and future changes in biodiversity and natural environments the use of AI tools should be based on аdequately curated, semantically structured and interlinked biodiversity data. We see this radical new step as a concerted community effort towards building a “Biodiversity Supergraph” (Fig. 1), understood here as a two-component ecosystem consisting of: centrally orchestrated system of tools and services, and distributed sources of transformed, semantically enhanced FAIR Linked Open Data, supplied by the partnering RIs. centrally orchestrated system of tools and services, and distributed sources of transformed, semantically enhanced FAIR Linked Open Data, supplied by the partnering RIs. The “Biodiversity Supergraph'' will provide integration of the biodiversity data on a scale and operational level that has never been attempted before. It is key for the next decade, to enable a baseline of global, biodiversity-related information serving organisations, academia, industry and society.

Optimization of Library Knowledge Services under the Background of Interdisciplinary and Transdisciplinary Integration

Optimization of Library Knowledge Services under the Background of Interdisciplinary and Transdisciplinary Integration

When Large Language Models Meet Optical Networks: Paving the Way for Automation

Since the advent of GPT, large language models (LLMs) have brought about revolutionary advancements in all walks of life. As a superior natural language processing (NLP) technology, LLMs have consistently achieved state-of-the-art performance in numerous areas. However, LLMs are considered to be general-purpose models for NLP tasks, which may encounter challenges when applied to complex tasks in specialized fields such as optical networks. In this study, we propose a framework of LLM-empowered optical networks, facilitating intelligent control of the physical layer and efficient interaction with the application layer through an LLM-driven agent (AI-Agent) deployed in the control layer. The AI-Agent can leverage external tools and extract domain knowledge from a comprehensive resource library specifically established for optical networks. This is achieved through user input and well-crafted prompts, enabling the generation of control instructions and result representations for autonomous operation and maintenance in optical networks. To improve LLM’s capability in professional fields and stimulate its potential on complex tasks, the details of performing prompt engineering, establishing domain knowledge library, and implementing complex tasks are illustrated in this study. Moreover, the proposed framework is verified on two typical tasks: network alarm analysis and network performance optimization. The good response accuracies and semantic similarities of 2400 test situations exhibit the great potential of LLM in optical networks.

Locating Indian knowledge in modern libraries: Incorporating the traditional classification of knowledge in India

Locating Indian knowledge in modern libraries: Incorporating the traditional classification of knowledge in India

Exploring the Impact of the Gamified Metaverse on Knowledge Acquisition and Library Anxiety in Academic Libraries

This paper investigates the potential of the Gamified Metaverse as a platform for promoting library services. The study compares the effectiveness of a traditional library program with a Metaverse-based library program in terms of knowledge acquisition and library anxiety. The research also examines students’ perceptions of implementing gamification within the context of the Gamified Metaverse platform. A mixed-methods approach was adopted, including pre- and post-test analysis, statistical analysis, and qualitative data collection. The results indicate that both the traditional and Metaverse-based library programs effectively increased the participants’ knowledge, with no significant difference between the two approaches. However, the Metaverse-based program was found to be less effective in facilitating interaction with librarians and reducing library anxiety. Additionally, students expressed positive perceptions of implementing gamification in the Gamified Metaverse platform, finding it engaging and motivating. These findings contribute to the understanding of the effect of the Metaverse as a tool for promoting library services and enhancing knowledge acquisition. However, it is not as effective in reducing library anxiety, particularly in terms of interaction with librarians and staff. It should be noted that the platform may have limitations such as high costs and potential side effects of virtual reality, making it more suitable as an additional tool for promoting library services, taking into account its feasibility and potential benefits for specific student populations and larger libraries.

A data‐driven identification method for impedance stability analysis of inverter‐based resources

AbstractObtaining inverter controller information may be a premise for seeking its dynamic behaviour. But accurate knowledge of such information would be unrealistic for real functioning inverter‐interfaced generators (IIGs), which hinders the stability analysis of the IIG. A new data‐driven impedance identification method is proposed for stability analysis, which involves an improved sparse identification algorithm as an ancillary function within the system identification framework. It contains mainly two design stages. First, the transform basis matrix (TBM) is devised systematically as a prior knowledge library to contain the possibly existing control structures. In the second stage, a sparse identification algorithm is reformulated in order to extract the relevant structures in TBM while obtaining controller parameters. The authors demonstrate that the sparse vector between the TBM and output signal is closely related to the controller structure. The effectiveness of the proposed method is verified on grid‐connected inverters based on droop control and virtual synchronous machine control.

Cervical Cancer and Quality of Life: Systematic Review

Cervical cancer is diagnosed annually in thousands of women around the world, and thousands die from it. The main objectives of this systematic review were to understand and characterize cervical cancer and understand what impacts it has on the lives of diagnosed women and survivors. To this end, a systematic review based on the PRISMA principles was carried out. The search was carried out through the Online Knowledge Library (B-on), obtaining 1179 articles, which were verified, considering the inclusion and exclusion criteria, with 18 articles and 20 additional references included in this review. The results demonstrated that cervical cancer (1) is preventable and can be treated with good results if identified early; (2) it is caused by Human Papilloma Virus infection; (3) it can be treated using different techniques; and (4) it has significant impacts on women's quality of life.

Development of Medical and Health Science Collection to Support Scientific Integration at UIN Syarif Hidayatullah Jakarta

Integrating knowledge is familiar to the State Islamic University, which has a Faculty of Medicine and Health Sciences. One of the problems that arise is the library's role as an institution that manages knowledge and can meet the information needs of the academic community in the form of collections in various media, namely printed and online. Therefore it is necessary to evaluate the collection development provided by the library. So the purpose of this research is to analyze how far the library collections of the Faculty of Medical Sciences and the Library of Health Sciences have developed in supporting scientific integration efforts at UIN Syarif Hidayatullah Jakarta. The research approach used is descriptive qualitative. This study found that library managers carried out collection development by considering the courses and study programs in the faculties of health and medicine. The library focuses on gathering resources and materials relevant to the fields of health and medicine and paying attention to related aspects of Islamic ethics and culture. So the more relevant the collections provided by the library, the higher the quality of knowledge and information library users need.

Attitude of Library Professionals Towards Information Communication Technology in the Select Central University Libraries of Delhi and Uttar Pradesh

With the advent of new technological transformations in libraries and information centres, library professionals have experienced major challenges with changes in the generation, creation, dissemination, and preservation of knowledge in libraries. The objectives of the present study are to find out the hindrances to implementing ICT, and incorporation in libraries has a prominent place in fulfilling the needs of users, but one must not ignore the fact that ICT is not only the factor responsible for achieving the goals of libraries; it is also the library professional’s positive attitude that endorses the implementation of the same. There are many factors that can help library professionals develop a positive attitude, including prior knowledge, proper training, and continuing education like in-service courses, workshops, and seminars. If the staff of the library shows a positive attitude towards the adoption of ICT in their organisation, it will raise their self-confidence, thereby increasing productivity, while also raising their morale and motivation among colleagues. On the other hand, a negative attitude will raise high levels of anxiety, lower levels of self-efficacy, technophobia, cyberphobia, and fear of losing their jobs. The negative attitudes of library professionals are the main hindrance to the implementation of ICT in libraries. The present study’s findings can advance our understanding of ICT adoption in libraries and provide practical recommendations for maximizing the use of ICT resources in library services. The study concluded that the major objectives have been accomplished by those in the library industry who adopt a critical stance toward the adoption and rejection of new technologies

LSVC: A Lifelong Learning Approach for Stream-View Clustering.

Multiview clustering (MVC) can achieve more accurate results by utilizing complementary information from multiple perspectives, compared to traditional single-view methods. However, current multiview techniques require all views to be available upfront, making them inadequate for dealing with prevalent data sources that arrive as streams, such as stem cell analysis and multicamera surveillance. To address this problem, in this article, we propose a method called lifelong stream-view clustering (LSVC), which comprises an embedding anchor knowledge library and three key components, enabling the capability to perform asynchronous clustering on stream views. These three components are specifically: 1) the knowledge extraction module that extracts the abstract knowledge of the newcome view over time and updates the shared knowledge library; 2) the knowledge transfer module that aligns the newcome view with the historical knowledge library, enabling the transfer of structure information to the knowledge library; and 3) the knowledge rule module that constraints the knowledge library to enjoy a fair amount of anchors for each cluster, improving the discrimination of knowledge. The experimental results show that LSVC outperforms traditional single-view clustering (SVC) and MVC methods as it gradually improves with the accumulation of stream views and tends to be stable over time.

Interdisciplinary Knowledge in Library and Bibliographic Classification and Universal Decimal Classification

Library classification was originally created for the purpose of thematic arrangement of books on the shelves in libraries on the basis of classification systems. The creation of the latter, in turn, is closely related to the classification of sciences, as works devoted to certain fields of knowledge or spheres of human activity are classified.Throughout their history, classification schemes have been transformed and structurally changed, based on the basic principles and levels of scientific knowledge. Originating in the ancient period, science has been developing for centuries according to the disciplinary principle. However, in the process of evolution of scientific knowledge there is interdisciplinary integration, which involves both natural, technical and social sciences. Complex fields of study are formed as a result of interscientific interaction, when the most distant sciences can discover a direct connection. This is a joint cognitive activity of specialists from different scientific disciplines, involving not only research, but also other types of activity (organizational, communicative, journalistic, etc.). Thus, the sphere of interdisciplinarity is formed.The article considers the representation of the problems of interdisciplinary research in the Universal Decimal Classification (UDC) and in the Library and Bibliographic Classification (LBC), recognized as the national classification system of Russia.

Designing an axial code pattern for absorptive capacity of knowledge in academic libraries: examining the effect of individual and organizational learning

PurposeThe purpose of the present study was to identify the conditions that affect the absorptive capacity (AC) of knowledge, discover its consequences and design an AC paradigm pattern in public academic libraries. To do so, AC was investigated at the levels of individual and organizational learning.Design/methodology/approachIn this paper, to answer the three major questions of this qualitative-survey study, the views of 24 experts were examined using an in-depth semi-structured interview and grounded theory strategy. The data were collected using a nonrandom combined targeted sampling procedure (targeted and snowball) and analyzed based on Strauss and Corbin’s (1998) approach and utilizing MAX Qualitative Data Analysis (MAXQDA) software.FindingsThroughout the grounded analytic stages, 121 open codes were identified. These were distributed around the AC axial category in academic libraries in terms of individual and organizational learning. The 33 axial concepts were then categorized into 16 selective general categories. The paradigm pattern was initially designed to explore the relationships between causal, intervening, strategies, context and consequences conditions. The transition from academic libraries to learning organizations, their increased functional value and the development of their innovation were identified as the consequences of AC development.Originality/valueThis qualitative research is the first in the field of Library and Information Science (LIS) to support AC both theoretically and empirically in terms of learning in academic libraries. This study thus not only addresses a key research gap in LIS but also provides significant insights and direction to interested librarians and researchers.

MMLKG: Knowledge Graph for Mathematical Definitions, Statements and Proofs

Nowadays, Knowledge Graphs (KGs) are important and developing in different areas. However, there is a lack of genuinely interoperable datasets representing mathematics that allow for information exchange between datasets in the Web ecosystem. In this paper, we address this matter based on the Mizar Mathematical Library (MML), a collection of articles written in the Mizar language. MML includes definitions and theorems with proofs to which authors can easily refer from newly written Mizar articles. However, extracting information directly from Mizar scripts by external projects is not very straightforward. Therefore, we propose a new data storage and retrieval approach based on the Knowledge Organization System (KOS) model and the KG concept that provides a way to organize and access knowledge. We present Mizar Mathematical Library Knowledge Graph (MMLKG), a thesaurus for describing mathematical objects. MMLKG supports semantic interoperability and allows linking data from different sources, e.g., Wikidata. Moreover, it satisfies the FAIR data principles. The data is publicly available via a Cypher endpoint.

The soil knowledge library (KLIB) – a structured literature database on soil process research

Abstract. In this technical note, we introduce a web-based application, the BonaRes Knowledge Library (KLIB, https://klibrary.bonares.de, last access: 26 July 2023), for the compilation and classification of scientific publications on soil processes according to the specific site conditions and experimental boundary conditions. The tool was developed based on the understanding that experimental findings in soil science are highly dependent on soil type, land use, and climate. The KLIB, therefore, goes beyond other available digital libraries by providing metadata on the site conditions and experimental settings for each publication. A number of visualization tools have been developed in the form of graphical networks to illustrate, for example, publications sharing the same type of scientific questions or soil properties that are affected by different types of drivers. This should help to explore the contents of the literature database more efficiently in order to support and facilitate the literature search efforts of the users. The KLIB is designed as a collaborative effort to encourage soil scientists to participate by entering their own studies and extending the existing database.

Tingkat Pengetahuan Pustakawan terhadap Brand Identity Perpustakaan

Libraries, as educational and cultural institutions, face various challenges and changes. One of the ways to enhance the reputation of libraries is through branding as a reliable access to information. Library branding goes beyond more than identity or a level of awareness. It aims to improve the continuous experience of library users. Brand identity is often perceived primarily through visual aspects such as logos, colors, shapes, and visual identification. Vision, Mission, core values, organizational culture, and competencies are vital elements of the internal component of corporate branding. This study examined librarian’s knowledge levels regarding brand identity using three corporate communication elements: communication, behavior, and symbolism. The total population is more than 100 with a confidence level of 90% and a 10% margin of error, namely 40 librarians—data collection targeting librarians and the staff in a university library. The validity test results were from 15 questions; 13 were valid, and 2 were invalid. The reliability test stated that this study was reliable. The results showed that the level of knowledge of librarians for communication got a score of 3,92, which means high. Behavior got a score of 4,47, which means very high, and symbolism got a score of 3,57, which means high. The mean total score is 3,57, which is high. The conclusion is that the librarian’s level of knowledge about brand identity is high. The most influential factor for internal brand identity in this study is behavior.

A Novel Chinese Address Segmentation Method with Self-growth Feature

Chinese Address Segmentation (CAS) is a crucial step that can greatly enhance the performance, accuracy, and reliability of geo-coding technology. However, it presents a tremendous challenge due to the inherent lack of obvious word boundaries, complex grammatical and semantic features. To address this challenge, we propose a novel CAS method or model that starts from scratch, without relying on any pre-installed knowledge about Chinese addresses. Instead, it dynamically evolves and grows its knowledge library by leveraging contextual information and comparing addresses during the process of dividing them into address elements. Our approach does not rely on Chinese language or address-element dictionaries, nor does it depend on address statistics. The knowledge library is automatically extracted and organized in a tree data structure. This unique approach allows our method to effectively segment addresses from any area of China, including regions with intricate address expressions, such as the Inner Mongolia Autonomous Region. Experimental results demonstrate that our method achieves high precision in address segmentation.

Data-Driven Prediction of Students’ Online Learning Needs and Optimization of Knowledge Library Management

Thanks to the advancement of information technology, online learning has become a crucial tool of modern education, and the management of modern education is facing the challenges of how to effectively predict students’ learning needs and how to optimize the management of the knowledge library to support these needs. However, existing data-driven prediction approaches are flawed in handling complex learning environments and timely adapting to changes, so this study attempts to solve these questions by exploring the correlation between learning needs, the extraction of knowledge linkages, and the optimization of knowledge libraries based on rule updates. In our work, a new method was proposed for extracting learning needs and knowledge linkages to more accurately identify and predict students’ learning needs, and a rule-based knowledge library management optimization method was introduced to allow the knowledge library to more flexibly adapt to students’ learning needs and the changes in educational resources. In this way, this study offers a comprehensive and flexible solution for education management via the combination of these two aspects, which not only increases student satisfaction and improves teaching quality but also reduces resource waste and gives students a more personalized and efficient learning experience. Furthermore, the methods and findings of this study could also be used as references for data-driven decision-making in other fields.

Multi-Level Text Clustering in Subject Knowledge Library and its Visualization

The large-scale and complex data generated in the teaching field of business administration poses challenges for decision-makers and managers of companies, and how to effectively extract and manage the useful information contained in these data has become a problem to be solved. Currently available methods of subject knowledge library clustering and visualization struggle to handle the complexity and multi-hierarchies of such subject data effectively or meet users’ requirements for advanced semantic understanding and retrieval. In view of these matters, this study aims to probe deeper into the problem of multi-level text clustering in the subject knowledge library and its visualization. Firstly, an innovative strategy-based subject semantic representation method for knowledge libraries was proposed to better interpret and represent the semantic information of subject data. Secondly, a subject clustering model of the knowledge library was constructed based on an improved hierarchical Dirichlet polynomial distribution, enabling efficient and accurate clustering of subject data. Lastly, visualization technology was employed to display the cluster results, allowing users to gain a clear understanding of the internal relationships and structure of the subject data. The research findings of this study could provide valuable new tools and methods for solving the problem of subject knowledge library management and utilization, analyzing the subject data, and supporting decision-making. As a result, they hold both theoretical and practical significance.