An analysis of academic librarians competencies and skills for implementation of Big Data analytics in libraries. A correlational study

Published date01 April 2019
Pages201-216
DOIhttps://doi.org/10.1108/DTA-09-2018-0085
Date01 April 2019
AuthorKhurshid Ahmad,Zheng JianMing,Muhammad Rafi
Subject MatterLibrary & information science
An analysis of academic
librarians competencies and
skills for implementation of
Big Data analytics in libraries
A correlational study
Khurshid Ahmad, Zheng JianMing and Muhammad Rafi
Department of Information Management, Nanjing University, Nanjing, China
Abstract
Purpose 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.
Design/methodology/approach 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.
Findings 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 Dataand
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.
Originality/value 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.
Keywords Competencies, Academic libraries, Librarians, Skills, Analytics, Big Data
Paper type Research paper
1. Introduction
The developmentin this digital era, the use of information communication, Internetof Things
and cloud system technology caused an extensive data growth in almost every
area of life in this digital environment (Liu et al., 2018). In this perspective, due to the
information explosion and the extensive use and growth of data, the problem is being
faced to organize thismassive unstructured growth of data. This situation provides genuine
reasons to evaluate these factors, as it is described that the growth of data on such a large
scaleisreferredtoasBig Data(Djafri et al., 2018). Nowadays, the Big Data isa hot topic of
discussion in the business, industry, education and government agencies globally;
the research and developmental practices are being conducted to overcome the challenges
and the opportunities of analytic use in Big Data(Cuzzocrea, 2014). It can say that Big Data is
leading pathway toward the emerging digital native economy of the world. However, in the
current literature, there is no unified definition of Big Data. Different circles have
defined Big Data in different ways. Some of the definitions mentioned as follows: Big Data
refers to such datasets whose volume is outside the capacity of traditional softwares
(Manyika et al., 2011). Big Data comprises of those data sets which are so large and complex
that commonly used softwares are incapable of dealing with them(Garcia and Wang 2013).
Data Technologies and
Applications
Vol. 53 No. 2, 2019
pp. 201-216
© Emerald PublishingLimited
2514-9288
DOI 10.1108/DTA-09-2018-0085
Received 30 September 2018
Revised 10 November 2018
Accepted 15 January 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2514-9288.htm
201
Implementation
of Big Data
analytics in
libraries
Similarly, Laney (2001) first presented the concept of Big Datathat it has some special
characteristics that differentiate it from ordinary data. These characteristics are categorized
and explained into 5Vs, that is, huge volume, high velocity, high variety, low veracity, and
high value(Jin et al., 2015). The size of Big Data is enormous in comparison with
regular ordinary data. There is no specified limitation for data volume and growth. The
velocity of Big Data refers to its dynamic and fast creation. The feature and variety of data
sets create the difficulties to the utilization process and organization of data. The data
that are collected systematically in a proper type by the data scientists or business
organization can be structured. However, some types of data are found in an unstructured
form that are gathered from different resources as e-mails and online collected data (Wang
et al., 2016). The development of Big Data creation, acquisition,storage and flow has come up
with some challenges and opportunities for modern libraries. The advancement in the
communication andinformation technology has changed thestructures of organizations that
are being modified to compete the environmental and social changes in the society.
In this context, the importance of Big Data in librarianship is also being recognized in the
circles of library professionals (Zhan and Widén, 2017). Another research by Ilesanmi (2013)
described thatlibraries are the centers of knowledgeorganization, retrieval anddissemination
of informationand maintaining informationsystems in the societyto meet the requirements of
community. However, now the emergence of Big Data is forcing libraries to redesign the
patterns of theirservices that they usually had for carrying out theiroperations (Affelt, 2015).
To respond the change in this digital ere,Noh (2015) argued that the presentform of libraries
can be convertedinto library 4.0. The library 4.0can be defined as an intelligent library,which
can analyze the massive data utilization and present the findings to their users. Itmeans that
the unique feature of library 4.0 will be the handling of the substantial form of data. It also
shows that the emerging trend of Big Data is a helpful toward the improvement of libraries
and infrastructure development to provide the better services to the users of libraries and
community. In present situation, libraries are facing the challenge of data handling and the
lack of skills of library professionals. There is also a need for these skills to be improved to
handle the opportunities and issues that are created in this Big Data era (Gordon-Murnane,
2012). This shifting paradigm from traditional to contemporary library infrastructure and
services creates an unusual situation that is to be analyzed. This study has some important
implications of Big Data analytics for the academic libraries. The literature review of
conducted studies and the current paradigm shift helps us to know the competencies and
skills of librarians reflecting the librariescapacity that is also necessary to address the
potential utilization of Big Data analytics in academic libraries.
1.1 Objectives
The objectives of this study are as follows:
(1) to explore the extent to which the Big Data analytics is being used in Pakistani
university libraries;
(2) to analyze the perceptions of LIS professionals toward the use of Big Data analytics; and
(3) to check the relationship between the competencies and skills of librarians for the
implementation of Big Data analytics.
2. Literature review
In previous studies, researchers have concentrated on the opportunities, merits and
demerits, required qualifications and skills, organization, and some other aspects of Big
Data analytics. In this section, the researchers review some selected studies conducted on
Big Data-related aspects. In this digital environment, the production, storage, organization
202
DTA
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