Content area

Abstract

Purpose

Large volumes of complex and diverse data sources present a tremendous barrier for big data applications (BDAs) in digital library in terms of processing and extracting relevant insights. The purpose of this study is to examine librarians’ perceptions of BDAs and management for digital library services in selected academic libraries in Kwara State.

Design/methodology/approach

The research design that was adopted in this study is the cross-sectional research design. The total population for this study is 58 (58) library professionals. Owing to the small population of this study, total enumeration sampling technique was adopted for this study. Hence, the sample size for this study is 58 (58). Questionnaire was used for data collection. Collected data were analyzed using descriptive statistics.

Findings

The study demonstrated that digital library services provided include virtual reference services, institutional repositories and personalized content recommendation. Also, the librarians were aware of BDAs like Apache Hadoop and Python. It was showed that BDAs are used for resource transfer, borrowing management, user needs, usage tracking and personalizing content recommendations. Results showed that open-source software and hardware, and training on handling diverse data sets are essential for the management of big data. Challenges associated with the use of BDAs include scalability limitations, complex data structures, lack of big data processing, power supply issues and data privacy.

Originality/value

This study provides unaddressed questions and gaps in the area of using BDAs for the provision of digital library services, especially in developing countries like Nigeria.

Details

Location
Title
Big data applications and management for digital library services in selected academic libraries in Kwara state, Nigeria
Publication title
Volume
41
Issue
2
First page
229
End page
246
Publication year
2025
Publication date
2025
Publisher
Emerald Group Publishing Limited
Place of publication
Bingley
Country of publication
United Kingdom
ISSN
20595816
e-ISSN
20595824
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-02-27
Milestone dates
2024-06-04 (Received); 2024-08-15 (Revised); 2024-11-16 (Revised); 2024-12-16 (Revised); 2025-01-28 (Accepted)
Publication history
 
 
   First posting date
27 Feb 2025
ProQuest document ID
3200163780
Document URL
https://www.proquest.com/scholarly-journals/big-data-applications-management-digital-library/docview/3200163780/se-2?accountid=208611
Copyright
© 2025 Emerald Publishing Limited
Last updated
2025-11-14
Database
ProQuest One Academic