Search results

This paper considers the exhibition: UnDoing. This research-through-curation project examined interactions within existing spaces and situations. This established links between the selected exhibits, the gallery, the city and with the continuum of the previous exhibition.

Carefully selected architects, designers and artists were invited to contribute—those who pursued a contextual approach; whose practice explored the way buildings, places and artefacts are reused, reinterpreted and remembered.

Through the act of curation, this research uncovered a series of different approaches to constructed sites and existing buildings, from layered juxtaposition, the refusal to undo, to interventions of new elements within architectural works.

Curation offered the opportunity to consider works of architecture and of art through the same lens, for direct comparisons to be made and the influence of one upon the other to be comprehended.

The examination processes the architect employs is similar to that of the artist; the development of an understanding of place, and from this synthesis, creative interpretation. However, despite the similarities in the starting position, the elucidation developed by the artist can be vastly different to that of the architect.

The juxtaposition and new classifications created by the exhibition encouraged visitors to look at art, architecture and the city in a different way; to grasp the direct link between the different subjects; and the possibilities created.

The two driving factors for UnDoing were places of previous occupation and the city of Manchester. The qualities of surrounding constructed environment combined were combined with attitudes towards existing structures and places.

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.

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 article examines curatorial practices, both traditional and digital, in the Guizhou Provincial Museum’s ethnic exhibition to assess their effectiveness in representing ethnic minority cultures, fostering learning and inspiring curiosity about ethnic textiles and costumes and associated cultures. It also explores audience expectations concerning digital technology use in future exhibitions.

A mixed-methods approach was employed, where visitor data were collected through questionnaires, together with interviews with expert, museum professionals and ethnic minority textile practitioners. Their expertise proved instrumental in shaping the design of the study and enhancing the overall visitor experience, and thus fostering a deeper appreciation and understanding of ethnic minority cultures.

Visitors were generally satisfied with the exhibition, valuing their educational experience on ethnic textiles and cultures. There is a notable demand for more immersive digital technologies in museum exhibitions. The study underscores the importance of participatory design with stakeholders, especially ethnic minority groups, for genuine and compelling cultural representation.

This study delves into the potentials of digital technologies in the curation of ethnic minority textiles, particularly for enhancing education and cultural communication. Ethnic textiles and costumes provide rich sensory experience, and they carry deep cultural significance, especially during festive occasions. Our findings bridge this gap; they offer insights for museums aiming to deepen the visitor experiences and understanding of ethnic cultures through the use of digital technologies.

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The purpose of this study is to propose a solution to this problem.

The current study identifies relevant literature and provides a review of big data adoption in libraries. It also presents a step-by-step guide for the development of a BDA platform using the Apache Hadoop Ecosystem. To test the system, an analysis of library big data using Apache Pig, which is a tool from the Apache Hadoop Ecosystem, was performed. It establishes the effectiveness of Apache Hadoop Ecosystem as a powerful BDA solution in libraries.

It can be inferred from the literature that libraries and librarians have not taken the possibility of big data services in libraries very seriously. Also, the literature suggests that there is no significant effort made to establish any BDA architecture in libraries. This study establishes the Apache Hadoop Ecosystem as a possible solution for delivering BDA services in libraries.

The present work suggests adapting the idea of providing various big data services in a library by developing a BDA platform, for instance, providing assistance to the researchers in understanding the big data, cleaning and curation of big data by skilled and experienced data managers and providing the infrastructural support to store, process, manage, analyze and visualize the big data.

The study concludes that Apache Hadoops’ Hadoop Distributed File System and MapReduce components significantly reduce the complexities of big data storage and processing, respectively, and Apache Pig, using Pig Latin scripting language, is very efficient in processing big data and responding to queries with a quick response time.

According to the study, there are significantly fewer efforts made to analyze big data from libraries. Furthermore, it has been discovered that acceptance of the Apache Hadoop Ecosystem as a solution to big data problems in libraries are not widely discussed in the literature, although Apache Hadoop is regarded as one of the best frameworks for big data handling.

This study aims to understand the research data management (RDM) services offered by academic libraries in South Asian and Southeast Asian countries. This study aims to evaluate the library and information science professionals’ required RDM skills and the challenges faced with providing RDM services.

The research methodology for this study used a survey method with purposive sampling. Data were collected through online structured questionnaires, which were used to examine the current state of RDM services offered in academic libraries in South Asia and Southeast Asia.

South Asian and Southeast Asian region major types of RDM services provided were data repository, data management training, maintaining Web resources, data study and analysis, and promoting awareness of reusable data sources. Little attention was given to advisory services on data analysis/mining/visualization and supporting reproducibility and workflow transparency. The results indicated that most respondents agreed that metadata standards and data management planning skills were required for RDM services in South Asia and Southeast Asia.

This study is significant because it offers a comprehensive assessment of ongoing RDM services in academic libraries of South Asia and Southeast Asia. Most current literature focuses on best practices in developed nations. This study highlights the need for more competent and dedicated academic staff for effective RDM services. Library professionals can use this study to identify the gaps in RDM services and suggest formative measures to overcome such challenges.

This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger.

This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study.

This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method.

The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.

Librarians play a critical role in curating, organizing and facilitating access to open data (OD) resources, supporting research, learning and information dissemination. This study aims to explore the use of OD for reference services delivery in academic libraries. It is believed that the concept of OD in librarianship refers to the practice of making publicly available data freely accessible, usable and shareable by anyone.

This research examined how the utilization of OD may affect library services and operations. This paper used the systematic review of literature to answer the research questions; hence, it was a desk study.

Given that there has been recently a research shift in linking OD to library metadata, this study revealed some interesting findings. More specifically, it discovered that incorporating OD into reference services can provide several benefits and enhance the quality and relevance of the information provided to library users. In addition, this paper reported that OD enriches reference services by providing comprehensive, current and interdisciplinary information, supporting evidence-based research, enabling data visualization and analysis, fostering community engagement and promoting innovation.

This paper proposes that libraries that possess extensive collections are in a favorable position to embrace the shift toward becoming OD and open big data libraries. It is also believed that academic libraries, through reference services, meet the challenge of providing access to their institutional repositories by holding many sets of data in various formats and providing various interfaces, developing metadata systems for various data streams, supporting all ecosystems of software and data products for reformatting and reusing large and complex data, and support for data sets identifiers. By actively engaging with OD, librarians can play a vital role in facilitating access to information and promoting the use of open knowledge for academic pursuits.

Metadiscourse is an important dialogue technique used in productive knowledge building to help a group evaluate and advance their knowledge progress. Previous studies have identified and defined various types of metadiscourse. However, there is scant knowledge about how different metadiscourse types emerge among different groups or what implicit correlations lie between progressive discourse and metadiscourse. Moreover, research on how different types of metadiscourse influence groups' knowledge advancement and artifacts is still inadequate. Therefore, this study aims to further examine the roles that different types of metadiscourse play in the collaborative knowledge building community on both a fine-grained (i.e. progressive discourse) and coarse-grained (i.e. group knowledge advancement and group artifacts) level.

Data for this study are drawn from the behaviour of undergraduate students participating in a 12-week course at a key university in China. On the fine-grained level, epistemic network analysis (ENA) is applied to illustrate how metadiscourse promotes the development of progressive discourse. On the coarse-grained level, two different chi-square tests are conducted to examine the roles of different types of metadiscourse in groups' knowledge advancement and artifacts.

The analysis allowed several conclusions to be drawn. First, the types of metadiscourse that students most often adopted were reflecting on ideas development (RD) and commenting on ideas (CI); they less frequently adopted setting group goals (SG) and making group plans (MP). Second, most types of metadiscourse correlated with developments in progressive discourse, particularly RD and CI. Third, the metadiscourse types RD, CI and coordinating group efforts (CE) played essential roles in knowledge advancement. Fourth, higher-quality artifacts could be created by using the metadiscourse type reviewing the state of knowledge building progress (RP).

A more profound comprehension of the role that metadiscourse plays in the collaborative knowledge building community not only contributes to the literature in the knowledge building field but also carries a significant meaning in regulating community, promoting learner agency and sustained knowledge, and consequently improving collaborative learning performance.