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This study, a conceptual paper, analyses the growth of curation in tourism and hospitality and the curator role in selecting and framing products and experiences. It considers the growth of expert, algorithmic, social and co-creative curation modes and their effects.

Narrative and integrative reviews of literature on curation and tourism and hospitality are used to develop a typology of curation and identify different curation modes.

Curational techniques are increasingly used to organise experience supply and distribution in mainstream fields, including media, retailing and fashion. In tourism and hospitality, curated tourism, curated hospitality brands and food offerings and place curation by destination marketing organisations are growing. Curation is undertaken by experts, algorithms and social groups and involves many of destination-related actors, producing a trend towards “hybrid curation” of places.

Research is needed on different forms of curation, their differential effects and the power roles of different curational modes.

Curation is a widespread intermediary function in tourism and hospitality, supporting better consumer choice. New curators influence experience supply and the distribution of consumer attention, shaping markets and co-creative activities. Increased curatorial activity should stimulate aesthetic and stylistic innovation and provide the basis for storytelling and narrative in tourism and hospitality.

This is the first study of curational strategies in tourism and hospitality, providing a definition and typology of curation, and linking micro and macro levels of analysis. It suggests the growth of choice-based logic alongside service-dominant logic in tourism and hospitality.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

Data librarianship, or data-driven librarianship, is the combination of information science, data science and e-science fields and is gaining gradual importance in the library and information science (LIS) profession. Hence, this study investigates the data librarianship core concepts (motivational factors, challenges, skills and appropriate training platforms) to learn and successfully launch data librarianship services.

A survey method was used and the data were collected through online questionnaire. Purposive sampling method was applied and 132 responses were received with 76 respondents from the public and 56 from the private sector universities of Pakistan. The statistical package for social sciences (SPSS version 25) was used, and descriptive and inferential statistics were applied to analyzed the data.

LIS professionals understand the importance of data-driven library services and perceive that such services are helpful in evolving the image of the library, helping with the establishment of institutional data repositories/data banks, developing data resources and services for library patrons and especially researchers, and receiving appreciation and acknowledgment from the higher authorities. The major challenges that emerged from the data were: missing data policies, limited training opportunities for data librarianship roles, no additional financial benefits, lack of infrastructure and systems, lack of organizational support for the initiation of data-driven services, and lack of skills, knowledge and expertise. Data librarianship is in its early stages in Pakistan, and consequently, the LIS professionals are lacking basic, advanced and technical data-driven skills.

The policy, theoretical and practical implications describe an immediate need for framing data policies. Such policies will help the libraries or any other relevant entities to store the data and assign metadata and documentation in such a way that it is easy to retrieve and reusable for others.

This is the first study in Pakistan to investigate the perceptions of LIS professionals about data librarianship core concepts: motivational factors, challenges, skills and appropriate training platforms to grasp data-driven skills and successfully launch library services.

In the era of digital intelligence, individuals are increasingly interacting with digital information in their daily lives and work, and a growing phenomenon known as digital hoarding is becoming more prevalent. Prior research suggests that humanities researchers have unique and longstanding information interaction and management practices in the digital scholarship context. This study therefore aims to understand how digital hoarding manifests in humanities researchers’ behavior, identify the influencing factors associated with it, and explore how they perceive and respond to digital hoarding behavior.

Qualitative research methods enable us to acquire a rich insight and nuanced understanding of digital hoarding practices. In this study, semi-structured interviews were conducted with 20 humanities researchers who were pre-screened for a high propensity for digital hoarding. Thematic analyses were then used to analyze the interview data.

Three main characteristics of digital hoarding were identified. Further, the research paradigm, digital affordance, and personality traits and habits, collectively influencing the emergence and development of digital hoarding behaviors, were examined. The subtle influence of traditional Chinese culture was encountered. Interestingly, this study found that humanists perceive digital hoarding as a positive expectation (associated with inspiration, aesthetic pursuit, and uncertainty avoidance). Meanwhile, humanists' problematic perception of this behavior is more widely observed — they experience what we conceptualize as an “expectation-perception” gap. Three specific information behaviors related to avoidance were identified as aggravating factors for digital hoarding.

The findings deepen the understanding of digital hoarding behaviors and personal information management among humanities researchers within the LIS field, and implications for humanities researchers, digital scholarship service providers, and digital tool developers are discussed.

This study aims to understand the acceptance of AI-curated fashion services among Chinese consumers by introducing consumer characteristics, such as fashion clothing involvement (FCI) and technological innovativeness (TI), as leading variables of the technology acceptance model (TAM). Furthermore, it aims to examine the impact of FCI and TI on attitudes towards AI-curated fashion services and the purchase intention of fashion products through perceived usefulness (PU), perceived ease of use (PEU), and perceived enjoyment (PE). Through this analysis, this study seeks to determine a marketing strategy that can support implementing AI-curated fashion services in the Chinese market.

This study used structural equation modeling to ascertain the results.

Regarding AI-curated fashion services' attributes, the analysis revealed that consumers' FCI did not significantly affect the PU and PE. However, FCI greatly impacted the PEU. In addition, consumers' interests in TI significantly affected PU and PE but did not significantly influence PEU, although PEU significantly affected PU. PU, PEU, and PE greatly impacted usage attitude. PU and usage attitude significantly affected purchase intention, whereas PE had no effect.

Through a practical survey of Chinese consumers, we investigated the impact of FCI and TI on the attitude and purchase intention of fashion products recommended by AI-curated fashion services.

This article reports on findings from interviews with ICT-based content creators whose work focuses on documenting and curating queer history and culture. The research specifically examines how as amateur historians, the participant’s embodied knowledge plays a central role in how they engage with discourse about queer historical figures, methods of queer historiography and community accountability.

The research deploys a queer constructivist framework to qualitatively gather and analyzes the semi-structured interviews of 31 North American content creators who curate digital project related to queer history and culture. The interviews were gathered between August 2022 and August 2023.

The research highlights how the subjectivity of queer embodiment aids, rather than hinders, participants' ability to collaborate with LGBTQIA+ communities while also addressing more significant ethical questions around intersectionality and inclusive historiographic work.

The content creators’ own positionality and commitments to community accountability and queer inclusivity fostered richer stories and historical documentation, while also helping make visible queer identity as affirming and valuable within queer culture. Additionally, practical implications include highlighting the value of ICT-based content within the distribution of educational and informational resources related to queer history.

This research offers an underexamined intersection of historiography and queer embodiment. While extensive scholarship on institutional and community-based historiography work exist the content creators interviewed within this study exist within the space of both, often using a combination of embodied knowledge and traditional curatorial work to translate between such spaces, inviting, in turn, new ways of thinking about queer archival knowledge.

The study aimed to identify the best practices for open educational resources (OER) management in Nigerian open education university libraries and the implications for policymakers.

A mixed-methods approach was used, which included a survey questionnaire administered via Google Forms to academic librarians and other library staff of the National Open University of Nigeria (NOUN). The study’s population was 398 and 273 participants responded to the survey. The study included all academic librarians and other library staff representing the six geopolitical zones in Nigeria. The data were analyzed using both qualitative and quantitative methods. The study’s results were presented using frequency counts, percentages tables and the qualitative data analysis was done thematically.

The findings of the study are consistent with existing literature on best practices for managing OER, which emphasized the importance of establishing clear policies and strategies for OER management practices, such as guidelines for acquiring, creating, curating and disseminating OER.

The originality of the study concludes by recommending that policymakers should develop policies that support the implementation of best practices in OER management to improve access to educational resources and reduce costs for students.

This study aims to explore children’s cognitions about data flows online and their understandings of algorithms, often referred to as algorithmic literacy or algorithmic folk theories, in their everyday uses of social media and YouTube. The authors focused on children ages 8 to 11, as these are the ages when most youth acquire their own device and use social media and YouTube, despite platform age requirements.

Nine focus groups with 34 socioeconomically, racially and ethnically diverse children (8–11 years) were conducted in California. Groups discussed data flows online, digital privacy, algorithms and personalization across platforms.

Children had several misconceptions about privacy risks, privacy policies, what kinds of data are collected about them online and how algorithms work. Older children had more complex and partially accurate theories about how algorithms determine the content they see online, compared to younger children. All children were using YouTube and/or social media despite age gates and children used few strategies to manage the flow of their personal information online.

The paper includes implications for digital and algorithmic literacy efforts, improving the design of privacy consent practices and user controls, and regulation for protecting children’s privacy online.

Research has yet to explore what socioeconomically, racially and ethnically diverse children understand about datafication and algorithms online, especially in middle childhood.

This paper aims to curate open research knowledge graph (ORKG) with papers related to ontology learning and define an approach using ORKG as a computer-assisted tool to organize key-insights extracted from research papers.

Action research was used to explore, test and evaluate the use of the Open Research Knowledge Graph as a computer assistant tool for knowledge acquisition from scientific papers.

To extract, structure and describe research contributions, the granularity of information should be decided; to facilitate the comparison of scientific papers, one should design a common template that will be used to describe the state of the art of a domain.

This approach is currently used to document “food information engineering,” “tabular data to knowledge graph matching” and “question answering” research problems and the “neurosymbolic AI” domain. More than 200 papers are ingested in ORKG. From these papers, more than 800 contributions are documented and these contributions are used to build over 100 comparison tables. At the end of this work, we found that ORKG is a valuable tool that can reduce the working curve of state-of-the-art research.

The increasingly active data practice in academic environments makes investigating college faculty users’ potential needs for library data services (LDS) essential. Guided by a conceptual framework rooted in the data lifecycle and the extended technology acceptance model, this study aims to investigate the relationship between faculty’s data engagement (DE) and their attitudes toward multiaspect LDS.

An online survey at a master’s college was conducted to collect data regarding faculty data practice, potential needs for data services (DS) and attitudes toward multiaspect LDS. Based on 139 complete and valid responses, the study built three conceptual models to demonstrate faculty users’ potential acceptance of LDS for research and teaching.

Participants’ research and teaching-related DE and background factors directly or indirectly affect their attitudes toward general DS, an institutional data repository if available and repository-based data curation.

The study contributes to DS and librarianship research by offering three conceptual models to explore LDS’ holistic support for faculty research and teaching. Moreover, the study provides insights into faculty’s job-related DE factors and calls for future research on effective DS in more college communities.