Login
The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant departments in formulating public opinion control measures for specific time and space contexts.
The spatiotemporal situational awareness framework comprises situational element extraction, situational understanding and situational projection. In situational element extraction, the data on the COVID-19 vaccine, including spatiotemporal tags and text contents, is extracted. In situational understanding, the bidirectional encoder representation from transformers – latent dirichlet allocation (BERT-LDA) and bidirectional encoder representation from transformers – bidirectional long short-term memory (BERT-BiLSTM) are used to discover the topics and emotional labels hidden in opinion texts. In situational projection, the situational evolution characteristics and patterns of online public opinion are uncovered from the perspective of time and space through multiple visualisation techniques.
From the temporal perspective, the evolution of online public opinion is closely related to the developmental dynamics of offline events. In comparison, public views and attitudes are more complex and diversified during the outbreak and diffusion periods. From the spatial perspective, the netizens in hotspot areas with higher discussion volume are more rational and prefer to track the whole process of event development, while the ones in coldspot areas with less discussion volume pay more attention to the expression of personal emotions. From the perspective of intertwined spatiotemporal, there are differences in the focus of attention and emotional state of netizens in different regions and time stages, caused by the specific situations they are in.
The situational awareness framework can shed light on the dynamic evolution of online public opinion from a multidimensional perspective, including temporal, spatial and spatiotemporal perspectives. It enables decision-makers to grasp the psychology and behavioural patterns of the public in different regions and time stages and provide targeted public opinion guidance measures and offline event governance strategies.
Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.
Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.
The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.
This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.
This study aims to evaluate the efficacy of a digital medical library, including department-based electronic journal access, library training course participation and scholarly publications.
The data on full-text electronic journal access, participants of library training courses and scholarly publications were exported from a digital medical library database during 2017–2021. In addition, electronic journal access and library training courses were divided into high-level and low-level groups, while scholarly publications were divided into physician and non-physician groups.
The scholarly publications had a positive correlation to library training courses and electronic journal access. Furthermore, scholarly publications showed a significant difference between the high-level and low-level electronic journal access groups but not between the high-level and low-level library training course groups. Scholarly publications and electronic journal access had positive correlations for both the physician and non-physician groups. Scholarly publications and library training courses, and electronic journal access and library training courses had positive correlations only in the non-physician group.
The importance of electronic journal access for scholarly publications is suggested based on the findings of the present study. The training courses held by the medical library had a positive effect on scholarly publications for the non-physician group.
The current study provides insights relevant to the electronic journal access of library-supported scholarly publications among medical departments. These results can serve as a reference for medical library development planning and decision-making in the future.
This study aims to investigate the factors that affect the intention to use public mobile libraries and enhance the quality of mobile library services to attract and retain users.
A questionnaire survey was conducted with 391 valid users in China. Based on the stimulus–response theory and user individual characteristics, a model was developed to examine the factors influencing the intention to use public mobile libraries. The model was tested using statistical software, such as SPSS 25.0 and AMOS 24.0.
The results indicate that technological factors, content factors, individual factors and psychological factors significantly influence the intention to use public mobile libraries. The impact of system quality and perceived ease of use in technological factors is relatively balanced. Among content factors, information quality is the most significant, while information literacy has a greater influence compared to subjective norms in individual factors. In psychological factors, perceived matching and perceived pleasure both positively influence usage intention, while perceived cost has a negative impact.
Firstly, this study only investigates users’ intention to use, but intention does not necessarily equate to actual usage behaviour (King and He,2006). Future research can introduce new variables to explore users’ adoption and continuous usage behaviours. Secondly, this study does not differentiate between different types of mobile library users. Future research can consider different user types, such as potential users and current users, to investigate the similarities and differences in their willingness to adopt mobile library services. Thirdly, this study is primarily cross-sectional. Future research can consider longitudinal studies to provide more in-depth insights into user behaviour.
This paper identifies external and internal stimulus factors and conducts a comprehensive investigation into the factors influencing the intention to use public mobile libraries, thus providing generalizable research findings. Unlike previous studies, this research introduces the information literacy variable, enriching the model of factors affecting users' intention to use mobile libraries and yielding more comprehensive conclusions. Consequently, the study aims to be grounded in the actual usage ideas and intentions of diverse user groups, constructing a model that highlights factors influencing the intention to use public mobile library services.
From a social perspective, this study offers four implications for improving the utilization of public mobile libraries. Firstly, it is crucial to integrate digital resources, enhance information quality in public mobile libraries and improve platform usability. Secondly, adopting a user-oriented approach is essential to improve the service level of public mobile libraries and stimulate residents’ participation. Thirdly, efforts should be made to strengthen user information literacy and increase information utilization. Fourthly, top-level design improvements, effective promotion efforts and user behaviour guidance are essential for the success of public mobile libraries.
This study contributes to the improvement of public mobile library services and the advancement of modern public cultural services by identifying the key factors that drive the intention to use such services. The findings have practical implications for promoting high-quality development and enhancing the popularity of public mobile libraries.
There is an increasing interest in the use of knowledge graphs to represent real-world knowledge and a common need to manage imprecise knowledge in many real-world applications. This paper aims to study approaches to solve flexible queries over knowledge graphs.
By introducing fuzzy logic in the query answering process, the authors are able to obtain a novel algorithm to solve flexible queries over knowledge graphs. This approach is implemented in the FUzzy Knowledge Graphs system, a software tool with an intuitive user-graphical interface.
This approach makes it possible to reuse semantic web standards (RDF, SPARQL and OWL 2) and builds a fuzzy layer on top of them. The application to a use case shows that the system can aggregate information in different ways by selecting different fusion operators and adapting to different user needs.
This approach is more general than similar previous works in the literature and provides a specific way to represent the flexible restrictions (using fuzzy OWL 2 datatypes).
Despite ongoing research into archival metadata standards, digital archives are unable to effectively represent records in their appropriate contexts. This study aims to propose a knowledge graph that depicts the diverse relationships between heterogeneous digital archive entities.
This study introduces and describes a method for applying knowledge graphs to digital archives in a step-by-step manner. It examines archival metadata standards, such as Records in Context Ontology (RiC-O), for characterising digital records; explains the process of data refinement, enrichment and reconciliation with examples; and demonstrates the use of knowledge graphs constructed using semantic queries.
This study introduced the 97imf.kr archive as a knowledge graph, enabling meaningful exploration of relationships within the archive’s records. This approach facilitated comprehensive record descriptions about different record entities. Applying archival ontologies with general-purpose vocabularies to digital records was advised to enhance metadata coherence and semantic search.
Most digital archives serviced in Korea are limited in the proper use of archival metadata standards. The contribution of this study is to propose a practical application of knowledge graph technology for linking and exploring digital records. This study details the process of collecting raw data on archives, data preprocessing and data enrichment, and demonstrates how to build a knowledge graph connected to external data. In particular, the knowledge graph of RiC-O vocabulary, Wikidata and Schema.org vocabulary and the semantic query using it can be applied to supplement keyword search in conventional digital archives.
A makerspace has recently been identified as an essential learning field for cultivating students’ creative and thinking abilities. Creating a makerspace service within a university library is vital, as it fosters innovation, interdisciplinary learning, practical skills, entrepreneurship and career readiness while transforming the library into a dynamic centre for hands-on education and collaboration. Nevertheless, the wide-ranging functions and uses of makerspace equipment can potentially lead to a situation where librarians are overwhelmed by their duties due to manpower constraints. Therefore, this study aims to develop a novel game-based augmented reality navigation system (GARNS) based on the Octalysis gamification framework and scaffolding theory to support makerspace user education, hoping to promote learners’ learning motivation and their immersive experience and to enhance the learning performance of makerspace user education.
With a true experimental research method, 24 grade 11 students from a high school in Keelung City, Taiwan, were recruited to participate in the experiment on makerspace user education. Among them, ten students were randomly assigned to the experimental group using the GARNS and the other seven students were randomly assigned to a control group using the Web navigation system. The remaining seven students were assigned to a second control group using the narrative guided tour with a librarian to conduct makerspace user education.
Analytical results show that learners can achieve significant learning effectiveness using the GARNS, Web navigation system or traditional narrative guided tour with a librarian for makerspace user education. There were no significant differences in learning effectiveness and motivation neither between the GARNS group and the narrative guided tour with a librarian group nor between the Web navigation system group and the narrative guided tour with a librarian group. However, there were significant differences in learning effectiveness and motivation in terms of the value and expectation dimensions of learning motivation between the GARNS group and the Web navigation system group, and the GARNS group was significantly better than the Web navigation system group.
The study’s practical implication on makerspace user education is to reduce the manpower of a university library with makerspace services by the proposed GARNS that can offer a practical solution to enhance the learning effectiveness and motivation of makerspace through immersive game-based autonomous learning. Additionally, the study’s theoretical contribution lies in its innovative combination of game-based learning and scaffolding theory, while its practical significance stems from its potential to revolutionize makerspace user education, enhance motivation and performance and influence the broader landscape of educational technology.
This study combines game-based learning with augmented reality tools to develop a novel GARNS, which provides an innovative and effective learning tool suitable for the characteristics of makerspace and contributes to promoting makerspace user education and diversified learning modes. Additionally, most interviewees believed that using GARNS for educating makerspace users could assist them in consistently evaluating, choosing and discovering educational tasks in a library makerspace. This study contributes to promoting the popularization of makerspace user education.
Through examination of the Library Reference Model (LRM) specifications for nomen and the potential challenges visual nomen might present for their description and use in information systems, the purpose of this study was to investigate two questions: (1) how do nonlinguistic or nonalphanumeric signs or symbols act as nomen to identify entities? and (2) what details or attributes are relevant to describe and classify such nomen to integrate them into information systems?
This research was built on an exploratory, qualitative instrumental case study design using multiple (or comparative) cases. Using the International Federation of Library Associations and Institutions LRM conceptualization of nomen as the basis, this research explored the similarities and differences between the LRM definition, its attributes and the use of nonlinguistic and nonalphanumeric “strings” for visual nomen to represent a
A close review of the history of the development of the nomen entity was made to understand the semiotic relationship between entities and their symbolic representation, how those symbols are then reified to be further classified and described and how such definitions in the LRM offer a path forward for better understanding the role and function of visual nomen. Based on the foundation of the nomen entity and its attributes established in the LRM, this research then looked at visual representations of concepts and entities to suggest a nascent framework for describing aspects of visual nomen which may be relevant to their use and application
This exploratory study of the use of supralinguistic ways of referencing entities delineates novel insights into a potential framework for describing and using visual nomen as a way of labeling or naming entities represented in information systems. By examining the specifications of the nomen entity and its attributes as delineated by the LRM, this study reinforces the applicability of LRM-defined attributes in the use of visual nomen in addition to offering other attributes or dimensions.
The purpose of this study is to investigate the relationships between the information system success model constructs including information quality (IQ), system quality (SysQ) and service quality (ServQ) with user satisfaction (US) and intention to use (IU).
A meta-analysis approach was used to achieve the objectives. For this purpose, the PRISMA-P guideline was used, and a search strategy was designed to search in three indexing databases including Google Scholar, Scopus and LISTA.
The findings of this research revealed that IQ, SysQ and ServQ are positively related to US and IU regarding library systems. The strength of the relationship between IQ and IU, IQ and US, ServQ and US and SysQ and US was high.
This study is a unique addition to the literature, as it provides a collective and comprehensive conclusion regarding different information systems’ (ISs) success in libraries. Therefore, it fills the literature gap. The findings also work as guidelines for system developers, designers and library high-ups to consider IQ, SysQ and ServQ while designing and developing ISs for libraries.
This paper aims to delve into the complexities of terminology mapping and annotation, particularly within the context of the COVID-19 pandemic. It underscores the criticality of harmonizing clinical knowledge organization systems (KOS) through a cohesive clinical knowledge representation approach. Central to the study is the pursuit of a novel method for integrating emerging COVID-19-specific vocabularies with existing systems, focusing on simplicity, adaptability and minimal human intervention.
A design science research (DSR) methodology is used to guide the development of a terminology mapping and annotation workflow. The KNIME data analytics platform is used to implement and test the mapping and annotation techniques, leveraging its powerful data processing and analytics capabilities. The study incorporates specific ontologies relevant to COVID-19, evaluates mapping accuracy and tests performance against a gold standard.
The study demonstrates the potential of the developed solution to map and annotate specific KOS efficiently. This method effectively addresses the limitations of previous approaches by providing a user-friendly interface and streamlined process that minimizes the need for human intervention. Additionally, the paper proposes a reusable workflow tool that can streamline the mapping process. It offers insights into semantic interoperability issues in health care as well as recommendations for work in this space.
The originality of this study lies in its use of the KNIME data analytics platform to address the unique challenges posed by the COVID-19 pandemic in terminology mapping and annotation. The novel workflow developed in this study addresses known challenges by combining mapping and annotation processes specifically for COVID-19-related vocabularies. The use of DSR methodology and relevant ontologies with the KNIME tool further contribute to the study’s originality, setting it apart from previous research in the terminology mapping and annotation field.
With the worldwide open government data (OGD) movement and frequent public health emergencies in recent years, academic research on OGD for public health emergencies has been growing. However, it is not fully understood how to promote OGD on public health emergencies. Therefore, this paper aims to explore the factors that influence OGD on public health emergencies.
The technology–organization–environment framework is applied to explore factors that influence OGD during COVID-19. It is argued that the effects of four key factors – technical capacity, organizational readiness, social attention and top-down pressure – are contingent on the severity of the pandemic. A unique data set was created by combining multiple data sources which include archival government data, a survey of 1,034 Chinese respondents during the COVID-19 outbreak and official COVID-19 reports.
The data analysis indicates that the four factors positively affect OGD, and pandemic severity strengthens the effects of technical capacity, organizational readiness and social attention on OGD.
This study provides theoretical insights regarding how to improve OGD during public health emergencies, which can guide government efforts in sharing data with the public when dealing with outbreak in the future.
This study aims to collect distributed knowledge organization systems (KOSs) from various domains, enrich each with meta information and link them to the multilingual KOS registry, facilitating integrated search alongside KOSs from various languages and regions.
This research involved collecting and organizing KOS information through three primary steps. The initial phase involved finding KOSs from Web search results, supplemented by the Korea ON-line E-Procurement System (KONEPS) and the National R&D Integrated Notification Service. After obtaining these KOSs, they were enriched by structuring contextual meta information using Basic Register of Thesauri, Ontologies and Classification (BARTOC) metadata elements and established dedicated media wiki pages for each. Finally, the KOSs were linked to the multilingual KOS registry, BARTOC, ensuring seamless integration with KOSs from various languages and regions and creating connections between each registry entry and its associated KOS wiki page.
The research findings revealed several insights, as follows: (1) importance of a stable source for collecting KOS: no national body currently oversees KOS registration, underscoring the need for a systematic approach to collect dispersed KOSs. For Korean KOSs (K-KOSs), KONEPS and National R&D Integrated Notification Service are effective data sources. (2) Importance of enhanced metadata: merely collecting KOSs were not enough. Enhanced metadata bridges access gaps and dedicated wiki pages aid user identification and understanding. (3) Observations from multilingual registry uploads: When adding KOSs to a multilingual registry, similarities were observed across languages and regions. Recognizing this, the K-KOSs were linked with their international counterparts, fostering potential global collaboration.
Due to the absence of a dedicated KOS registry agency, the study might have missed KOSs from certain fields or potentially over-collected from others. Furthermore, this study primarily focused on K-KOSs and their integration into the BARTOC registry, which might influence the methods and perspectives on collecting and establishing links among analogous KOSs in the registry.
This research pursued a stable method to detect KOS development and revisions across various fields. To facilitate this, we used the integrated e-procurement and R&D notification system and added meta information to aid in the identification and understanding of KOSs, which includes media wiki pages. Furthermore, link information was provided between the BARTOC registry and the Korean KOS websites and media wiki pages.
This study aims to discover the factors which influence user satisfaction levels and their continuous use intention (CUI) of academic library social media, and then considers how to promote and improve further work on library social media to reduce user churn and increase user satisfaction.
An updated DeLone and McLean information systems success (D&M ISS) model and the expectation confirmation model for information systems continuance (ECM-ISC) with new variables of emotions are used to examine the factors which influence user satisfaction levels and CUI of academic library social media through 445 questionnaires. Partial least squares structural equation modelling was used to analyse the data and presented in tables.
The results show that information quality, system quality and emotions affect user satisfaction and CUI, and reveal that emotions can affect that most obviously.
The WeChat public platform is mainly used in China, so the study only focuses on Chinese academic libraries. There are still limitations on the settings of observed variables which cannot cover all the causes of users’ positive and negative emotions. In addition, although the respondents of this questionnaire can represent academic library users, 445 samples are still fairly low in contrast to the great number of academic library WeChat public platform users.
This study integrates ECM-ISC and D&M ISS models, adds positive and negative emotions as new variables, to broaden the application scope of these models, and demonstrates the applicability of these two models in the fields of researching academic library social media, expanding and deepening related theories above. This also provides practical reference for academic libraries on how to improve user satisfaction and CUI of academic library social media and academic library WeChat public platforms, promoting the development of academic library social media.
This study aims to discover how domain familiarity and language affect the cognitive load and the strategies applied for the evaluation of search engine results pages (SERP).
This study used an experimental research design. The pattern of the experiment was based upon repeated measures design. Each student was given four SERPs varying in two dimensions: language and content. The criteria of students to decide on the three best links within the SERP, the reasoning behind their selection, and their perceived cognitive load of the given task were the repeated measures collected from each participant.
The evaluation criteria changed according to the language and task type. The cognitive load was reported higher when the content was presented in English or when the content was academic. Regarding the search strategies, a majority of students trusted familiar sources or relied on keywords they found in the short description of the links. A qualitative analysis showed that students can be grouped into different types according to the reasons they stated for their choices. Source seeker, keyword seeker and specific information seeker were the most common types observed.
This study has an international scope with regard to data collection. Moreover, the tasks and findings contribute to the literature on information literacy.
The purpose of this article is to contribute to the digital development and utilization of China’s intangible cultural heritage resources, research on the theft of intangible cultural heritage resources and knowledge integration based on linked data is proposed to promote the standardized description of intangible cultural heritage knowledge and realize the digital dissemination and development of intangible cultural heritage.
In this study, firstly, the knowledge organization theory and semantic Web technology are used to describe the intangible cultural heritage digital resource objects in metadata specifications. Secondly, the ontology theory and technical methods are used to build a conceptual model of the intangible cultural resources field and determine the concept sets and hierarchical relationships in this field. Finally, the semantic Web technology is used to establish semantic associations between intangible cultural heritage resource knowledge.
The study findings indicate that the knowledge organization of intangible cultural heritage resources constructed in this study provides a solution for the digital development of intangible cultural heritage in China. It also provides semantic retrieval with better knowledge granularity and helps to visualize the knowledge content of intangible cultural heritage.
This study summarizes and provides significant theoretical and practical value for the digital development of intangible cultural heritage and the resource description and knowledge fusion of intangible cultural heritage can help to discover the semantic relationship of intangible cultural heritage in multiple dimensions and levels.
Although governments have used social media platforms to interact with the public in an attempt to minimize anxiety and provide a forum for public discussion during the pandemic, governments require sufficient crisis communication skills to engage citizens in taking appropriate action effectively. This study aims to examine how the National Health Commission of China (NHCC) has used TikTok, the leading short video–based platform, to facilitate public engagement during COVID-19.
Building upon dual process theories, this study integrates the activation of information exposure, prosocial interaction theory and social sharing of emotion theory to explore how public engagement is related to message sensation value (MSV), media character, content theme and emotional valence. A total of 354 TikTok videos posted by NHCC were collected during the pandemic to explore the determinants of public engagement in crises.
The findings demonstrate that MSV negatively predicts public engagement with government TikTok, but that instructional information increases engagement. The presence of celebrities and health-care professionals negatively affects public engagement with government TikTok accounts. In addition, emotional valence serves a moderating role between MSV, media characters and public engagement.
Government agencies must be fully aware of the different combinations of MSV and emotion use in the video title when releasing crisis-related videos. Government agencies can also leverage media characters – health professionals in particular – to enhance public engagement. Government agencies are encouraged to solicit public demand for the specific content of instructing information through data mining techniques.
The purpose of this study is to assess the awareness and preparedness level of the chief librarians (CLs) of the universities of Punjab and the Federal area in Pakistan concerning censorship. The study also aims to identify the preferred sources the respondents use to update their knowledge about censorship.
The research work is based on the survey method. A questionnaire was used to collect data from the CLs of 105 universities. The collected data was analysed descriptively.
The major findings of the study are that there is a dire need to improve the awareness level of the university library CLs regarding censorship. It was also found that a majority of the CLs do have not any formal written policy to handle censorship issues. However, religion was the main cause of censorship in a majority of cases. The study also indicated that social media was the most preferred source CLs use to update their knowledge.
The current study covers only the CLs of universities of Punjab and the Federal area. Therefore, its findings cannot be generalized to all the library professionals of Pakistan.
The study will help to understand the awareness level of CLs about censorship-related issues and provide an opportunity for university authorities to arrange training programs for the CLs to enhance their capabilities to deal with censorship issues.
The study will provide awareness and preparedness status of CLs regarding censorship issues.
For the provision of smart library services to end users, tools of the Internet of Things (IoT) play a significant role. The study aims to discover the factors influencing the adoption of IoT in university libraries, investigate the impact of IoT on university library services and identify challenges to adopt IoT applications in university libraries.
A systematic literature review was carried out to address the objectives of the study. The 40 most relevant research papers published in the world’s leading digital databases were selected to conduct the study.
The findings illustrated that rapid growth in technology, perceived benefits, the networked world and the changing landscape of librarianship positively influenced the adoption of IoT in university libraries. The study also displayed that IoT supported library professionals to initiate smart library services, assisted in service efficiency, offered context-based library services, provided tracking facilities and delivered effective management of library systems. Results also revealed that a lack of technical infrastructure, security and privacy concerns, a lack of technological skills and unavailability of policy and strategic planning caused barriers to the successful adoption of IoT applications in university libraries.
The study has provided theoretical implications through a valuable addition to the current literature. It has also offered managerial implications for policymakers to construct productive policies for the implementation of IoT applications in university libraries for the attainment of fruitful outcomes. Finally, the study provides a baseline for understanding the adoption of IoT in academic libraries.
The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts from unstructured text corpus. In the human disease domain, ontologies are found to be extremely useful for managing the diversity of technical expressions in favour of information retrieval objectives. The boundaries of these domains are expanding so fast that it is essential to continuously develop new ontologies or upgrade available ones.
This paper proposes a semi-automated approach that extracts entities/relations via text mining of scientific publications. Text mining-based ontology (TmbOnt)-named code is generated to assist a user in capturing, processing and establishing ontology elements. This code takes a pile of unstructured text files as input and projects them into high-valued entities or relations as output. As a semi-automated approach, a user supervises the process, filters meaningful predecessor/successor phrases and finalizes the demanded ontology-taxonomy. To verify the practical capabilities of the scheme, a case study was performed to drive glaucoma ontology-taxonomy. For this purpose, text files containing 10,000 records were collected from PubMed.
The proposed approach processed over 3.8 million tokenized terms of those records and yielded the resultant glaucoma ontology-taxonomy. Compared with two famous disease ontologies, TmbOnt-driven taxonomy demonstrated a 60%–100% coverage ratio against famous medical thesauruses and ontology taxonomies, such as Human Disease Ontology, Medical Subject Headings and National Cancer Institute Thesaurus, with an average of 70% additional terms recommended for ontology development.
According to the literature, the proposed scheme demonstrated novel capability in expanding the ontology-taxonomy structure with a semi-automated text mining approach, aiming for future fully-automated approaches.
Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.
Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.
This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.
This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.
The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the Resource Description Framework (RDF). Alongside Named Graphs, this approach offers opportunities to leverage a meta-level for data modeling and data applications.
In this extended paper, the authors build onto three modeling use cases published in a previous paper: (1) provide provenance information, (2) maintain backwards compatibility for existing models, and (3) reduce the complexity of a data model. The authors present two scenarios where they implement the use of the meta-level to extend a data model with meta-information.
The authors present three abstract patterns for actively using the meta-level in data modeling. The authors showcase the implementation of the meta-level through two scenarios from our research project: (1) the authors introduce a workflow for triple annotation that uses the meta-level to enable users to comment on individual statements, such as for reporting errors or adding supplementary information. (2) The authors demonstrate how adding meta-information to a data model can accommodate highly specialized data while maintaining the simplicity of the underlying model.
Through the formulation of data modeling patterns with RDF-star and the demonstration of their application in two scenarios, the authors advocate for data modelers to embrace the meta-level.
With RDF-star being a very new extension to RDF, to the best of the authors’ knowledge, they are among the first to relate it to other meta-level approaches and demonstrate its application in real-world scenarios.
This paper aims to examine the impact of the COVID-19 infodemic on the public’s online information behaviour, offering insights critical for shaping effective informational responses in future public health emergencies.
This paper uses a structured online survey with 27 targeted questions using a five-point Likert scale to measure eight variables. Data analysis is conducted through structural equation modelling on 307 valid responses to rigorously test the research hypotheses.
This paper indicates that information quality significantly impacts the public’s capacity to select, share and use online information. Additionally, the comprehensibility of information plays a crucial role in shaping the public’s behaviours in terms of online information exchange and usage. The credibility of information sources emerges as a key determinant influencing the public’s online information selection, exchange and utilization behaviour. Moreover, social influence exerts a substantial effect on the public’s online information selection, acquisition, exchange and utilization behaviour. These findings highlight the presence of universality and sociality, mediation and guidance, as well as the purposefulness and selectivity performed by the public’s online information behaviour during an infodemic.
This paper introduces a novel research model for assessing the influence and identifies the patterns of the public’s online information behaviour during the COVID-19 infodemic. The findings have significant implications for developing strategies to tackle information dissemination challenges in future major public health emergencies.
This study aims to develop a model for integration of information and communication technologies (ICTs) in resource sharing practices for enhanced service delivery in academic libraries in Southeast Nigeria. Seven objectives guided the study; ICT-based resource sharing practices in academic libraries in Southeast Nigeria; ICT infrastructure for resource sharing; ICT needs of librarians for resource sharing practices; stages of ICT integration in resource sharing; perception of librarians towards ICT-based resource sharing; challenges to integration of ICT in resource sharing practices; design a model for the integration of ICT into resource sharing; all in academic libraries in Southeast Nigeria.
The research design adopted for this study is the mixed research design containing the “descriptive survey” research design and the “research and development, R&D.” The population of the study is 164, comprising all of the librarians in federal universities in Southeast Nigeria. All of the librarians of the five federal universities will be involved in the study. Hence, there was no sampling. The instrument for data collection is a structured questionnaire.
The findings of the study revealed that 88.8% of the librarians use ICT to boost the volume of resources; while 74% of the librarians were positive in all responses pertaining to ICT-based resource sharing practices in the libraries. The study also revealed that ICT infrastructures in the library for resource sharing are highly available and applicable; while computers and internet networks are the most needed gadgets for the operations. Libraries in Southeast Nigeria are in the applying and transforming stages of ICT adoption at a 69.7% response rate; while the librarians have a strong belief and understanding that a lot can be achieved in resource sharing through ICT; and would recommend such. Poor electrification, inadequate funding and unavailability of some ICT technologies were equally identified as challenges. The study conclusively developed a resource sharing model, the Southeast Federal University Library Connect; accessible at https://southeastfeduniconnect.njh.com.ng
The research study is one of the few types of research that has developed a functional model for resource sharing in academic libraries in Southeast Nigeria.
This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the DDiv index, for this purpose.
The DDiv index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.
The sensitivity analysis demonstrated the DDiv index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the DDiv index reached the highest prediction accuracy of 0.8. Furthermore, the DDiv index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.
This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.
Noticias em eLiteracias