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This study aims to propose a model based on philosophical thoughts of Dr S.R Ranganathan and the lean-startup method for the execution of big data analytics (BDA) in libraries. The research paves a way to understand the role and required competencies of Library and Information Science (LIS) professionals for the implementation of BDA in libraries.

In the BDA analytics context, a session with a proposed model was presented to the audience to get the response of librarians about the required competencies and skills. The research tool was developed based on the literature review to know the role of LIS professionals and their required competencies/skills for BDA. The questionnaire was distributed in the BDA session to collect the responses of the participating audience on the variables that focused on the role and core competencies of LIS professionals in BDA. In the analysis of results, the independent t-test was applied to know the mean value of the overall response rate.

The findings show that perceptions of LIS professionals in the understanding of BDA ranked high in data privacy, data availability, data organization and data literacy. Digital data curation, policies supervision and providing the data consultancy also showed a significant relationship among these variables. Besides, the correlation between the required skills for BDA, metadata skills, data ethics, data acquisition, data cleaning, data organization, data analysis, digital curation, data clustering, data protection rules and digital visualization also showed a beneficial relationship.

This study also helps to understand the perspective of LIS professionals for the implementation of BDA in libraries and to fill the literature gap in the respective.

The purpose of this paper is to analyze the views and capabilities of librarians for the implementation of Big Data analytics in academic libraries of Pakistan. The study also sets out to check the relationship between the required skills of librarians and the application of Big Data analytics.

A survey was conducted to gather the required data from the targeted audience. The targeted population of the study was Head/In charge library managers of Pakistani university libraries, which were 173 in total. All the respondents (academic librarians) were invited through an e-mail to respond to the survey voluntarily. Out of 173 respondents from higher education commission of Pakistan chartered university libraries, 118 librarians (68.2 percent) completed the survey that was finally considered, and after checking data, recommendation for analysis was made. To analyze the collected data, statistical technique Pearson correlation was applied using statistical package for social science version 25 to know the strength of the mutual correlation of variables.

The findings of the study show a strong correlation between the required competencies and skills of librarians for the implementation of Big Data analytics in academic libraries. In all variables of the study, the correlation was highly significant, except two of the variables, including “concept of Big Data” and “different forms of data.” The study also reveals that most of the respondents were well aware of the concept of Big Data analytics. Moreover, they were using a large amount of data to carry out various library operations, including the acquisition, preservation, curation and analysis of data.

This study is significant in the sense that it fills a substantial gap in the literature regarding the perspective of librarians on Big Data analytics.

The purpose of this paper is to explore the roles of public libraries in the context of Big Data.

A mixed method approach was used and had two main data collection phases. A survey of public libraries was used to generate an overview of which professional roles connect public libraries with Big Data. Eight roles were identified, namely, educator, marketer, data organiser, data container, advocator, advisor, developer and organisation server. Semi-structured interviews with library directors and managers were then conducted to gain a deeper understanding of these roles and how they connect to the library’s overall functions.

Results of the survey indicated that librarians lack a proper comprehension of and a pragmatic application of Big Data. Their opinions on the eight roles are slightly stronger than neutral. However, they do not demonstrate any strong agreement on these eight roles. In the interviews, the eight roles attained more clear support and are classified into two groups: service-oriented and system-oriented roles.

As an emerging research field, Big Data is not widely discussed in the library context, especially in public libraries. Therefore, this study fills a research gap between public libraries and Big Data. In addition, Big Data in public libraries could be well managed and readily approached by citizens in undertaking such roles, which entails that public libraries will eventually benefit from the Big Data era.

This study aims to find out the role of big data in the field of library and information science by considering the opportunities and challenges.

This study, which was conducted on a desk, examined the rise and significance of big data in the field of library and information science in Nigeria. Also, systematic literature review is done, exploring blogs and wikis to gather data on the use of big data.

This study emphasizes that as data is the primary component in the creation of information, professionals in the fields of library and information science must develop the knowledge and abilities necessary to support big data analysis. It was determined that offering and facilitating big data analysis would guarantee our place as a priceless and crucial resource in the digital workplace.

To the best of the authors’ knowledge, this study will be one of its kind to examine the role of big data in the field of library and information science profession. Furthermore, the results of the study will expose librarians and information professionals on the opportunities and challenges inherent in the use of big data technologies.

This paper aims to propose a conceptual model for improving the organization of user needs information in the big data environment.

A conceptual model of the organization of user needs information based on Linked Data techniques is constructed. This model has three layers: the Data Layer, the Semantic Layer and the Application Layer.

Requirements for organizing user needs information in the big data environment are identified as follows: improving the intelligence level, establishing standards and guidelines for the description of user needs information, enabling the interconnection of user needs information and considering individual privacy in the organization and analysis of user needs.

This Web of Needs model could be used to improve knowledge services by matching user needs information with increasing semantic knowledge resources more effectively and efficiently in the big data environment.

This study proposes a conceptual model, the Web of Needs model, to organize and interconnect user needs. Compared with existing methods, the Web of Needs model satisfies the requirements for the organization of user needs information in the big data environment with regard to four aspects: providing the basis and conditions for intelligent processing of user needs information, using RDF as a description norm, enabling the interconnection of user needs information and setting various protocols to protect user privacy.

The purpose of the study was to investigate factors promoting innovation and application of internet of things in academic and research information organizations.

Quantitative research design involved survey of selected academic and research information organizations in public and private chartered institutions. Information professionals, digital content managers, information systems and technologists that normally consume big data and technological resources were involved in the process of data collection using structured questionnaire and content analysis. Information organizations and information practitioners were selected from public and private academic and research institutions.

Innovation of internet of things has increasingly transformed and changed academic and research information organizations as the source of knowledge in addition to expanding access to education, data, information and communication anywhere anytime through hyperconnectivity and networking. Internet of things technologies such as mobile of things, web of things, digital information systems and personal devices are widely applied by digital natives in academic and research information organizations. Mobilization platform and devices is the single biggest provider of data, information and knowledge in academic and research organizations. Modern trends in education and knowledge practices in academic institutions and information organizations depends upon internet of things, digital repositories, electronic books and journals, social media interfaces, multimedia applications, information portal hubs and interactive websites, although challenges regarding inadequate information communication technology infrastructure and social computing facilities still persist.

Information organizations in public and private chartered academic and research institutions were adopted in the study. Respondents handling and supporting information management, planning and decision-making provided the necessary data. Information professionals, digital content managers, information systems and technologists are proactively involved in data and information analytics.

Academic and research information organizations are powerhouses that provide knowledge to support research, teaching and learning for sustainable development and the betterment of humanity and society. Innovation of internet of things and associated technologies provides practical aspects of attaining sustainable information development practices in the contemporary knowledge society. Internet of things technologies, principles of economies of scale and investment and customer needs entail that information organizations and practitioners should provide appropriate and smart systems and solutions.

Modern academic and research information organizations have the social corporate responsibility to offer technological innovations to heighten access to knowledge and learning in academic and research institutions. Economically, innovation and application of internet of things provide unlimited access to big data and information in organizations all the time anywhere anytime.

Data management is a growing phenomenon that information practitioners need to fully understand in the digital economies. Information professionals need to embrace and appreciate innovation and application of internet of things technologies whose role in sustainable development practices is critical in academic and research organizations.

This study aims to examine Big Data and the management of libraries in the era of the Fourth Industrial Revolution and its implications for policymakers in Nigeria.

A qualitative methodology was used, involving the administration of open-ended questionnaires to librarians from six selected federal universities located in Southwest Nigeria.

The findings of this research highlight that a significant proportion of librarians are well-acquainted with the relevance of big data and its potential to positively revolutionize library services. Librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study exclusively focuses on the Nigerian context, overlooking insights from other African countries. As a result, it may not be possible to generalize the study’s findings to the broader African library community.

To the best of the authors’ knowledge, this study is unique because the paper reported that librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

Organizations are beginning to realize the potential benefits of big data and harnessing all of the data they are creating. However, a major impediment for many organizations is understanding where to start in big data and analytics implementation. In many respects, starting a successful implementation is not much different from any other project managed within the organization. The major stumbling block is knowing what questions to ask to get things going. This paper aims to help libraries and information organizations that are considering big data and analytics implementation to begin their journey by following a checklist of eight aspects to be considered in the development of a big data and analytics strategy.

The eight aspects to consider in big data and analytics implementation were developed using a combination of existing project management common knowledge, consultant recommendations and real-life experiences.

Organizations considering big data and analytics implementation need to explore aspects related to the data they have, what organizational problems they are trying to solve, how data governance will work in the new environment, as well as how they will define success in terms of their implementation. These are in addition to the technical issues one would normally expect in a systems implementation.

While there have been many articles written about the implementation of big data and analytics in organizations, most of these focus on technical issues rather than managerial and organizational concerns. In addition, none of these other articles have been from the perspective of library and information science. In this article, the focus is specifically on how information professionals may approach this problem.

With the exponential growth of the amount of data, the most sophisticated systems of traditional libraries are not able to fulfill the demands of modern business and user needs. The purpose of this paper is to present the possibility of creating a Big Data smart library as an integral and enhanced part of the educational system that will improve user service and increase motivation in the continuous learning process through content-aware recommendations.

This paper presents an approach to the design of a Big Data system for collecting, analyzing, processing and visualizing data from different sources to a smart library specifically suitable for application in educational institutions.

As an integrated recommender system of the educational institution, the practical application of Big Data smart library meets the user needs and assists in finding personalized content from several sources, resulting in economic benefits for the institution and user long-term satisfaction.

The need for continuous education alters business processes in libraries with requirements to adopt new technologies, business demands, and interactions with users. To be able to engage in a new era of business in the Big Data environment, librarians need to modernize their infrastructure for data collection, data analysis, and data visualization.

A unique value of this paper is its perspective of the implementation of a Big Data solution for smart libraries as a part of a continuous learning process, with the aim to improve the results of library operations by integrating traditional systems with Big Data technology. The paper presents a Big Data smart library system that has the potential to create new values and data-driven decisions by incorporating multiple sources of differential data.

Through the case analysis of China’s digital library, the purpose of this paper is to make readers understand the development status, achievements and problems of China’s digital library. At the same time, it also enables readers to understand the common application forms of these modern information technologies in digital libraries, so as to provide a reference basis for the application of new technologies in other countries’ digital libraries.

On the basis of literature review, the authors have analyzed a conspicuous collection of related papers in order to make a comprehensive summary and elaboration on the present situation of modern information technology application in Chinese digital libraries.

This paper defines and analyses the concepts, contents and relationships of the three most important modern Big Data information technologies, and then completes the analysis of the current situation of the application of information technology in Chinese digital libraries. The block chain can achieve more accurate information collection, more secure information storage and more effective information dissemination. Artificial intelligence can improve the existing digital library service level in three aspects: resource construction, information organization and information service. Internet plus will help transform the traditional digital library business mode in order to adapt to the change of user-centered service.

This is among the first structured attempts of comprehensively and generally summarizing the application of modern information technology in Chinese digital libraries. It also contains an original exploration of the relationship between the main kinds of modern information technology. Based on this, a relatively complete application scenario and possible vision of modern information technology in digital library can be built.