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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 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.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

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 res, moving iteratively between the LRM documentation, visual nomen identified in previous research and additional examples. This study used a constant comparative method to conduct a structured, focused comparison across different cases found in the source survey.

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 present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

Drones have become an important element within hospitality and tourism. The purpose of this study is to identify the corpus of knowledge and create a research agenda that establishes appropriate guidelines for future study of drone application in hospitality and tourism.

This work has been undertaken using a mixed-methods approach that combines quantitative and qualitative research and includes a review of the literature related to the study of drone use in hospitality and tourism.

The mixed-methods review identified gaps in the research, potential areas of study to enhance the scientific literature and potential uses of drones in tourism and hospitality for researchers, consumers and industry professionals.

This study makes an original contribution by establishing an integrated framework, which led to a synthesis of the research corpus and provided a holistic conceptualisation of the relationship between tourism and drones. In addition, the research agenda proposed will help boost and consolidate this emerging field of research.

无人机已经成为接待和旅游中的一个重要元素。本研究的主要目的是确定知识库, 并建立一个研究议程, 为未来无人机在酒店和旅游业的应用研究建立适当的指导方针。

这项工作采用了混合方法, 将定量和定性研究结合起来, 包括对与酒店和旅游业中无人机使用研究有关的文献进行回顾。

混合方法审查确定了研究中的差距、加强科学文献的潜在研究领域, 以及研究人员、消费者和行业专业人士在旅游和酒店业的无人机应用潜力。

这项研究通过建立一个综合框架做出了原创性的贡献, 它综合合成了研究语料库, 并对旅游和无人机之间的关系提供了一个整体的概念化。此外, 提出的研究议程将有助于促进和巩固这一新兴的研究领域。

Los drones se han convertido en un elemento importante dentro de la hostelería y el turismo. El objetivo principal de este estudio es identificar el corpus de conocimiento y crear una agenda de investigación que establezca las directrices adecuadas para el estudio futuro de la aplicación de los drones en la hostelería y el turismo.

Este trabajo se ha realizado utilizando un enfoque de métodos mixtos que combina la investigación cuantitativa y cualitativa e incluye una revisión de la literatura relacionada con el estudio del uso de drones en hostelería y turismo.

La revisión de métodos mixtos identificó lagunas en la investigación, áreas potenciales de estudio para mejorar la literatura científica y potencial de las aplicaciones de los drones en el turismo y la hostelería para investigadores, consumidores y profesionales del sector.

Este estudio aporta una contribución original al establecer un marco integrado, que conduce a una síntesis del corpus de investigación y proporciona una conceptualización holística de la relación entre el turismo y los drones. Además, la agenda de investigación propuesta contribuirá a impulsar y consolidar este campo de investigación emergente.

COVID-19 played a crucial role in the development and enlargement of learning via electronic media. Still, the recent fourth industrial revolution [Industry 4.0 (I4.0)] paved the road toward Education 4.0. In this regard, several research challenges arise, involving the preparation of gamification strategies in online learning environments. In this sense, this paper aims to investigate the relationship between technologies of I4.0 and gamification practices in online learning around the world. Specifically, to categorize the studies of the scientific literature in the area into knowledge domains and the mention of I4.0 technologies and to verify the relationship of these technologies with the different educational levels.

The preferred reporting items for systematic reviews and meta-analysis protocol was used as a research method with 130 papers included for full content analysis and obtained from the Web of Science.

The leading I4.0 technologies mentioned in the analyzed papers were simulation, Internet of Things and augmented/virtual reality, in this order. Although there are more mentioned technologies, the domain of knowledge to be applied and the educational level interfere in choosing these pillars. With this, the main findings of this relationship were exposed in a singular, modern, active, realist, technological framework to demonstrate how I4.0 relates to the practice of gamification in online educational environments.

To the best of the authors’ knowledge, this is the first study that brings together the relationship of gamification applied in e-learning with I4.0 technologies.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

Despite striving for resilience and a sustainable urban future, European cities face a multitude of crisis caused by both natural and human-induced risks. This paper asks two key questions: How have cities experienced and managed crises situations they encountered? and What are the plans and actions for embedding sustainability at a local level within a clear decision-making structure? Hence, it aims to examine urban resilience in the context of urban crisis and the associated health concerns that took place because of crisis situations, while identifying sustainable urban development initiatives and strategies that were conceived and implemented beyond crisis.

An evidence-based analytical approach is undertaken following two lines of inquiry. The first is case-based and identifies 11 cities that have experienced crisis situations and a further 10 cities that have instigated urban resilience strategies. The second is theme-based and engages with identifying strategies relevant to sustainable urban development at city and project levels. The outcomes of the two lines of inquiry are verified by mapping the lessons learned from the analysis to recent international guidance and a further co-visioning workshop with 6 experts.

The evidence-based analysis reveals key lessons which were classified under two primary types of findings: (a) lessons learned for a future urban resilience resulting from the 1st line of Inquiry (case-based) and (b) lessons learned for a future sustainable urban development resulting from the 2nd line of inquiry (theme-based). The verified lessons provide four areas that can be utilised as key priorities for future urban resilience and sustainable urban development including (a) Governance, effective communication, and decision making for city resilience and urban sustainability; (b) the social dimension of resilience and participatory practices for sustainable urban development; (c) from implicit strategies for health to positive impact on health; and (d) diversification of initiatives and localisation of sustainable development endeavours.

There is always limitation on what a bibliometrics analysis can offer in terms of the nature of evidence and the type of knowledge generated from the investigation. This limitation manifests in the fact that the analysis engages with the body of knowledge but not based on engaging physically or socially with the contexts within which the cases took place or through empirical investigations including systematic observations, focused interviews, and attitude surveys. While the study does not generate empirical findings, the rigour of the bibliometrics analysis offers a credible and reliable evidence on how cities experienced and managed crises situations and their current plans and priority actions for embedding and localising sustainable development measures.

This research conveys significant implications for policy, practice, and action in that it crystalises the view that understanding urban resilience and sustainability, at the city or urban level, requires coupling the two. The findings offer a solid foundation for a more contextualised, evidence-based examination of urban resilience and sustainability during and beyond crisis. Highlighting urban and health challenges that emerged from experienced crisis situations, how these were managed and developing an understanding of sustainable urban development and local resilience strategies elucidate insights that can be adopted and acted upon by city councils and built environment practitioners.

The analysis provides comprehensive insights into urban resilience and sustainable urban development at both city and continental Europe scales in the form of key lessons that represent the first step towards developing rudiments for building a better urban future. Little is known about resilience and sustainability at these scales. The originality of this work lies in the breadth and depth for capturing an inclusive understanding of urban resilience and sustainable urban development based on systematic inquiry and scrutinising the body of knowledge emerged over the past 2 decades.