The use of bigdata in the management of library resources: Nigeria university experiences

Abstract

Services of libraries have to be accessible to all members of the community; this requires well situated library infrastructure, facilities and information resources as well as relevant technologies. Therefore, this study explored the use of big data in the management of library resources in university libraries. Four objectives were proposed for the study to describe the use of bigdata in managing resources of university library. In addition, ethical concern related to the use of bigdata was also identified in the paper. Descriptive literature review was used as methodology. The study conclude that Bigdata as a tool in university libraries is an important mechanism that is meant to protect library information resources for use. The nature of the library resources call for more protection especially resources are ICT in nature. However, the important of Bigdata in any organization including library become an imperative to resources management. The nature of services delivery in this present age in university library calls for the use of Bigdata so that right information resources can be provided to right people at tight time and place. Based on the concluding part, the study recommends that awareness should be provided by university libraries and management on the opportunities of Bigdata to library clienteles and training, conference and workshop should be orgnise by library and university management in order to equip library personnel with the needed skills and knowledge on better use of Bigdata in service provision.

Keywords

Academic library bigdata library library resources

Introduction

With the rapid development of network and information technology, the era of big data has come to have impact on every field of life. Every day is accompanied by a huge amount of data with library also undergoing different changes in the processing of data and information resources. Adoption, use and integrating library resources with big data can be a system with greater value (Daniel, 2020). However, with the increasing the popularity of the concept of a smart library, the traditional information service of the library has gradually shifted to a user-centered personalized service model. For this reason, the data center of the library is showing a trend of massive growth which includes users’ privacy behavior information, library management system logs, and operational monitoring data that have becomes way of life in digital age (Bamiah et al., 2018).

Almost each sector has developed a fascination with the ostensibly new discovery of Big Data and its extraordinary capabilities to fuel analytical breakthroughs since 2012 (Murumba and Micheni, 2017). Daniel (2019) noted that the rapid development and wide application of information and network technology, the data information has also shown an explosive growth trend, indicating the beginning of the era of entering the big data. The library has always been greatly affected by the environment and technology. At the dawn of the era of big data, not only has the development of the library ushered in more opportunities, it has also brought challenges to the library. And in this context, Big Data refers to a huge volume of data with massive output and exponential growth, and neither processed/analyzed by any common analyzing technique, nor stored in any traditional storage (Hwang, 2019).

In the era of big data, the information resources of university libraries exist in the form of big data. Based on the consideration of personalized service needs of users, it is urgent to apply related technologies such as cloud computing to handle big data to information services in order to help university libraries, achieve “one-stop” information resources services. The so-called “one-stop'' resource service refers to the deep integration of data from various databases or knowledge bases, restructuring or heterogeneous data, making it easy for university users to access various physical and virtual collections (Haddad et al., 2018). Therefore, big data refer to the gargantuan bulk of data that cannot be dealt with by traditional data-handling techniques. Big data encompass the use of technologies to capture process, analyze, and visualize potentially large datasets in a reasonable timeframe (Anna and Mannan, 2020).

Big data have three characteristics namely; volume, velocity and variety. Volume refers to the large quantities of data that are generated continuously through e-commerce and social networking websites, online teaching, learning and assessment. The issue of big data consequently resulted in application of modern technology to capture the array of information that is generated (Kaladhar et al., 2018). Kamupunga and Chunting (2019) posited big data is defined as information overload due to the volume, velocity, variety, variability and veracity of the data which must be processed to get value and better visualization. Big Data contains the answer to several valuable questions related to patterns, trends and associations of user behavior. It plays a major role in helping libraries to clearly understand the changing user needs, accordingly reshape and restructure their services and procedures (Hamad et al., 2020).

Martin and Thawabieh (2017) posited that with regard to the time dimension of library digital resources, the integration of digital resources by libraries is to integrate all the data accumulated in the corresponding time period; in terms of the spatial dimensions of library digital resources, the library is to integrate digital resources. The data in the libraries in each area is effectively integrated. The digital information integrated in the library contains various digital resources such as business data, user information, industry information, and external data. In the context of big data, data integrity is also reflected in the Multi-purpose characteristics of the data. Therefore, in the process of integrating digital resources in libraries, we must also integrate data resources that differ in the same subject but from different sources, so as to ensure the integrity of digital resources (Hanapiyah et al., 2018).

Chong and Shi (2020) stated that big data is widely used in various fields, and many big data processing technologies and processing methods have also been formed. It is necessary to complete the integration of library services to ensure that user needs are met through big data (Almeida, 2017). Patade (2020) noted that under the big data environment, the sharing of digital resources is gradually improved, and the library digital resource integration platform integrates all kinds of data information to ensure that the library data information can be combined into a complete organism, which can further promote the digital library. To support the storage and process needs of Big Data applications, cloud has been found to be the most acceptable infrastructural resolution (Hwang, 2019). Libraries are progressively keen on utilizing datasets to deal with their collections, and use of space, as well as to evaluate the offered services.

Conventional library processes can create large measures of data, particularly for bigger libraries. Portions of the data can be divided into circulation transaction, user, online database usage and other library data activities (Olendorf and Wang, 2017). The improvement in learning success will be focused on the education system, which will revolutionize the way it develops students from higher education, who will select a career and be guided to acquire skills in any course. It’s observed that Surveillance that are common among Bigdata in university libraries seems to have helped resources harmonization in academic libraries. In this paper, the study covers areas such as: use of big data in managing of resources in University libraries; benefits of using Bigdata in managing resources in university libraries; factors influencing the use of Bigdata in the management of resources in university libraries, and the problems militating against the use of Bigdata in management of resources university libraries.

Uses of BigData in managing resources in university libraries

Services of libraries have to be accessible to all members of the community; this requires well situated library infrastructure, facilities and information resources as well as relevant technologies (Badawi, 2021). Fagan and Fagan (2020) posited that university library can make a fundamental contribution to daily survival and social and economic development by being directly involved in providing information to people in a community. Onyenachi (2022) opined that universities library are no longer the only source of information for academics and researchers, as the information boom concomitant with the complex transformation in information and communication networks. Maideen et al. (2019) stated that in the era of ICT and the information resources of university libraries exist in the form of big data.

Reinhalter and Wittmann (2021) noted that big data is widely used in various fields, and many big data processing technologies and processing methods have also been formed. Although big data processing methods are different, they basically include data collection processes, data organization, and processing processes (Rani, 2021). In the process of large data processing in the library, the same process should be followed. Daniel (2021) observed that the reasons why universities library adopt big data is to improve librarians’ professional skills, these skills includes technical skills, skills of the librarian itself, social skills, communication skills, interpersonal skills, technology, teaching and leadership skills. Adopting big data aid university librarians to help library users such as students, lecturers and researchers to be more efficient in the pursuit of their needs.

Onyenachi (2022) posited that through the adoption and integration of big data, people can discover knowledge and learn new skills, get information about personal health and well-being, find out about government and local authority service and seek information about employment and business development; the tremendous role of big data can never be over-emphasized. Another purpose of using Bigdata is that it analyze users’ needs to know exactly what they need and how to satisfy them, developing services to groups and individuals through selective dissemination of information to target user group, promoting user education to enlighten them how to search for needed and immediate information, co-operating and sharing resources with other library as well as other library users, developing electronic networks to encourage online discussion forum among users, ensuring access to services to all regardless of who you are prompt the library users to want to visit the library more often (Patel et al. 2022).

In Nigeria, it is hoped that there will be an increase in the computer-based learning environment which will increase power and ability to log fine-grained data about students’ learning. With the training and retraining of Information and Communication Technology (ICT) officers, big data in education will be better handled. The full benefit of big data in the system will begin to manifest when critical decisions are taken based on results of data analysis and when the assessment big data inform policy. There should be strategic plans for collecting data, record creating in all education activities. There should be education history for pupils and students. This will help in designing models for explaining learners’ behavior, attitude, and achievement and so on. The necessary infrastructure for generating and analyzing complex data needs to be put in place (Ball, 2019).

Benefits of using bigdata in managing resources in university libraries

According to Rani (2021), the digitization of our world is advancing relentlessly and a far-reaching and serious side effect of this transformation is the fact that humankind is producing ever more data. Thanks to technology such as faster broadband connections, mobile technology, ever more powerful computers, larger memories and the Internet of Things, the data volume which is set to increase exponentially in years to come. Adopting big data help university libraries in Nigeria to extract valuable raw scholarly data which are accurate with insurance and scalability. Since Big Data includes all types of information resources, especially those which can be combined for complicated evaluation due to the proliferation of private computing devices and smartphones. Massive quantities of data are generated every second through e-conversation, e-trade, GPS navigation, social media and online search (Reinhalter and Wittmann, 2021).

Big Data technology makes it easier to work with big datasets, hyperlink unique datasets, locate styles in real time, predict results, undertake dynamic risk scoring, and test hypotheses are allow users to have access to libraries resources with ease and everywhere (Daud, 2018). University libraries can benefit from making an investment in data and text miming techniques, in order to analyze their postings, benchmark against the postings of other libraries, and assess their buyers’ pride and level of engagement. In addition, wealth formation may be extracted from social media in real time, which could be used in enhancing and developing libraries and fact sources and services (Al-Daihani and Abrahams, 2019).

According to Murumba and Micheni (2017), the benefits of big data in university libraries are as follows: Big data helps an organization to plan by creating massive information provided to departments. It help corporation search and access to inner datasets, knowledge of external record sources, and specialists on copyright and intellectual belonging problems by creating data repository. Big data also help professional and a university community to theoretically understand the concept of big data and analytics in university libraries by working with large datasets, hyperlink exceptional datasets.

Big data therefore help in locating patterns in real time, anticipate effects, undertake dynamic risk scoring and test hypotheses. Big data help students, lecturers and researchers, by supporting their researchers. This is done by encourage biomedical researchers to impeach the safety and integrity of the records, and help them to track information throughout its life cycle. Big data help in text miming practice. Resource libraries studying their postings, benchmark towards the postings of other libraries can evaluate library purchasers’, user’s satisfaction and degree of engagement. With big data wealth data can be extracted using social media (Patel et al., 2022).

Under the big data environment, the sharing of digital resources is gradually improved, and the library digital resource integration platform integrates all kinds of data information to ensure that the library data information can be combined into a complete organism, which can further promote the digital library. The co-construction of resources and the development of sharing work, the era of big data, the scientific, share-ability, value, and ease of operation of data structures are the operational security and efficiency of relational library systems, user service models and content changes, and improved service capabilities (Murumba and Micheni, 2017).

Factors influencing the use of bigdata in the management of resources in university libraries

Tarmidi et al. (2018) posited that library management systems are relatively conservative, which weakens their competitiveness when it comes to rapid development. Therefore, most efforts in this respect have focused on how to qualify and maximize data. Usually, the data pass from the official records, and the data of the beneficiaries are captured through different systems and input policies that configure these data and records in various forms and classifications. Therefore, the libraries have redesigned all servers and modernized them to make them suitable for connections and integrations. All services related to the automatic index have been redesigned and made available through digital applications available on devices that support Android and IOS systems.

Many efforts have been made to digitize theses and dissertations and convert them into digital copies, available through digital repositories that can be accessed at anytime and anywhere. They are available with all technologies that enable the researcher to search in titles and within the content of a thesis. The manuscripts represent the history of the nation, as well as a major document that is a pillar of knowledge and cultural balance. They store knowledge, thought, science and art. They demonstrate their importance in preserving identity and history as they combine tangible and intangible heritage in form and content.

The importance of the manuscript remains, even with the presence of the printed book there from, because the value of the manuscript does not come only from the words it contains, but its supreme merit comes from it being a work of art from the era of mechanical production, its temporal and spatial existence, the types of calligraphy, its decoration, its relationship to the era, and its history. This makes the manuscript an open window on the art of calligraphy and the science of drawing the letter and its significance. Due to the scarcity of some of these manuscripts, the damage in some of the papers, or the lack of clarity about the calligraphy, there was great difficulty in them being accessible as a treasure of knowledge and benefiting users with their science and knowledge (Al-Barashdi and Al-Karousi, 2018).

Jain (2020) stated that the developments and challenges of 21st century have already influenced librarians to embrace ICT applications in daily library workings in order to provide effective and efficient services to the library users. With the onset of big data, it has now become important for professional such as librarians to know how big datasets can be made more useful, visible and accessible by creating taxonomies, designing metadata schemes, and systematizing retrieval methods. Kaladhar et al. (2018) stated that big data is creating a widespread presence in the world of information and is likely to impact on all kinds of libraries. Librarians depending on the type of library, in which they work, need to know the basics of big data and how it can affect the nature of work and how the big data can be used. It’s not just increased amount of data but also improved tools to store, aggregate, combine and analyze the data. For example, corporate librarians need to know how companies hold big data, how such data mining provides a competitive advantage, and how students might need to tackle with big data sets in future employment.

Librarians working in scientific research libraries need to know how big data differs from other scientific data and the impact of emerging software and hardware used for its analysis. Humanities and social science librarians should know that big data is becoming common in their disciplines as well, and is no longer restricted to science and business only. Digital archivists, data curators, and other types of librarians are also asked to advise their faculty on the storage and accessibility of big data sets. However, the factors militating against the adoption of big data can be seen in the readiness of the university management (Martin and Thawabieh, 2017).

Library administration and management always examine what types of big data sets their library could be gathering and analyzing using big data tools. Library professionals would discuss what new they can measure with the help of the big data tools example if the library is dealing with some massive data set related to faculty research which previously was out of reach because of software and hardware constraints. Use of big data can also be done for developing library collection, tracking the use of library materials by its users etc. Big data can be used by the librarians in different ways for library administration, user satisfaction and retrieval of information in least possible time (Ball, 2019).

Factors influencing the adoption and implementation of big data are in terms of cost, productivity, and innovation. Data must be processed with advanced tools to reveal meaningful information. Librarians have always been great at information organization and management. A librarian does not need to become a programmer but should try to know and have basic knowledge of how various software tools can transform the huge amount of data. Big data has given an opportunity to the librarians to play an important role in the big data universe because they have the skills, knowledge and service mentality to help all irrespective of their discipline (Daniel, 2021).

Libraries are in a unique position to use big data for their managerial purposes and also provide library services around big data analytics. Many libraries are already offering research data services such as data management planning, data collection, data curation and data archiving. The extent of the provided services is limited according to the users’ need and the current situation of the library or organization. More so, in this life cycle, there are some stages where libraries can play an important role, while in other stages libraries don’t have much importance. So, libraries will need to choose carefully what services to provide and how to resource them (Onyenachi, 2022).

Librarians play a role in the collection, development, and renovation of statistics units and usage records, as well as incorporating information, research information management, and data literacy into their academic programs. However, all of these require understanding of what information we have received, what statistics we need to create and what statistics we need to negotiate, in order to gain access and perform the evaluation (Rani, 2021).

Factors hindering the use of bigdata in management of resources in university libraries

However, big data poses many technical problems that include constant upgrading of resources and expertise, meaning university library need to have sufficient budgets to implement big data. Legitimate concerns about privacy do exist, particularly regarding data from online sources. This combined with the digital divide in many nations poses barriers to using Big Data’s power for the benefit of library users (Umezuruike and Ngugi, 2020). Hamad et al. (2020) stated another challenge that is becoming a major factor limiting against the use of big data in university libraries in Nigeria, is data access problems posed by the data owners, such as the students’ academic management center, strategic planning office, Alumni center and information technology center. Each specific strategic business unit, such as the academic management center, has to maintain its status quo for the students’ information data, in the name of confidentiality and student data secrecy. In most situations, it is reluctant to open their database to external party usage (big data analysts).

Another challenging factor limiting against the use of bigdata in university libraries is lack of understanding for what the purpose of the data to be analyzed by the big data analysts. The major challenge for university libraries in Nigeria in the use of big data is the notion of limitation of technology. It is widely believed that even engaging the latest big data technology, such as Hadoop and R-programming, it would not solve all the needs, wants and wishes for using the derived data. There are still limitations of what big data technologies could offer due to data quality, accuracy and legacy data which exist in many varieties of formats and platforms (Wang, 2021).

Within the university library, vast array of assessment data are gathered from (Hamad et al., 2016) students information systems, library usage, attendance data, participation in online fora, eye movement, facial recognition data to the widely-used data source, students interactions with the virtual learning environment. However, it is observed that factors limiting against the use of big data in university libraries in Nigeria include: low awareness on the need and advantages of assessment big data, security issues in contracting data analyst and low level of infrastructural development and technical knowhow (Hamad et al., 2020).

Another major challenge of open access is inadequate budgets of academic libraries. Many activities that can boost open access will need financial resources for their launching. The creation of an institutional repository, an open access journal or a digital library cannot be supported by the budget of academic libraries, especially in developing countries. It requires funding from external institutions. Academic libraries are not enthusiastic about establishing Institutional Repositories because funding is absent to acquire infrastructure and state of the art technology. The organization of activities like conferences, workshops, study days, seminars and a host of other open access related activities to create awareness and engage stakeholders to require sufficient financial resources (Wang, 2021).

In addition, Togia (2018) identified inadequate skills to navigate the internet, unstable power supply, unavailability of internet facilities, permanence of open access movement due to unstable financial support, lack of knowledge of the existence of big data in the internet as factor militating against the adoption and integration of big data by librarians.

Ethical issues on the use of bigdata

There are several ethical concerns surrounding the use of big data and data analytics, including:

1. Privacy: The collection, storage, and analysis of large amounts of personal data can raise concerns about privacy and the protection of personal information.

2. Bias: Data can reflect and perpetuate societal biases, and can be used to discriminate against certain users if proper precautions are not taken.

3. Transparency: The methods used to collect, analyze, and interpret data may be opaque or difficult to understand, making it difficult for users to know how decisions are being made about them.

4. Security: Large amounts of data stored in one place can be vulnerable to cyber attacks, and the potential for data breaches or misuse of information is high.

5. Accountability: It may be difficult to hold individuals or organizations accountable for the decisions or actions taken based on data analysis.

6. Fairness: Data collection and analysis can be used for unfair targeting of individuals for surveillance or profiling.

It’s important for library to be aware of these ethical concerns and to take steps to address them, such as implementing strong privacy and security measures, and being transparent about their data collection and analysis practices.

Conclusion

Bigdata as a tool in university libraries is an important mechanism that is meant to protect library information resources for use. The nature of the library resources call for more protection especially resources are ICT in nature. However, the important of Bigdata in any organization including library become an imperative to resources management. The nature of services delivery in this present age in university library calls for the use of Bigdata so that right information resources can be provided to right people at tight time and place. It is emanated from literature that resources in university libraries are in various forms that require being together for better output.

It is also established that storage of resources is easily done and achievable through Bigdata in university libraries. Furthermore, Bigdta helps corporation search and access to inner datasets, knowledge of external record sources, sharing resources among sister’s libraries, provide resources for potential users ahead of time and reserve resources to regular users. Big data also help professionals working in university library and a university community to theoretically understand how fast-tracking services with present reality around the globe can be provided in university libraries by working with large datasets and hyperlink exceptional datasets.

Recommendations

Based on the conclusion, the following recommendations are provided to guide the study.

1. Awareness should be provided by university libraries and management on the opportunities of Bigdata to library clienteles

2. Training, conference and workshop should be orgnise by library and university management in order to equip library personnel with the needed skills and knowledge on better use of Bigdata in service provision.

3. Provision of alternative power supply within the library so that when there is power failure, resources of library can still be accessed within the library by users.

4. Specifications should be known by library management and university before embracing the particular Bigdata.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Kabir Alabi Sulaiman

Author biographies

M. L. Akanbi is an Associate Professor of department of Library and Information Science, University of Ilorin, Ilorin Nigeria. Chartered Librarian, He has publications in Local, National and International Journals, editor and reviewer in many reputable outlets.

Kabir Alabi Sulaiman is a lecturer in a department of Library and Information Science, Kwara State University, Malete Nigeria. PhD student in department of Library and Information Science, University of Ilorin, Ilorin Nigeria.

Maliq Hammed Omolola is student in department of Library and Information Science, University of Ilorin, Ilorin Nigeria.

Bilqees Jumia Nallah Librarian II in University Library, Kwara State University, Malete Nigeria. PhD student in department of Library and Information Science, University of Ilorin, Ilorin Nigeria.

References

Al-Barashdi

Al-Karousi

(2018) Big Data in academic libraries: literature review and future research directions. Journal of Information Studies & Technology 2018(2): 13. DOI: 10.5339/jist.2018.13.

Al-Daihani

Abrahams

(2019) A text mining analysis of academic libraries’ tweets. The Journal of Academic Librarianship 42: 135–143.

Almeida

FLF

(2017) Benefits, challenges & tools of big data management. Journal of Systems Integration 8(4): 12–20.

Anna

NEV

Mannan

(2020) Big data adoption in academic libraries: a literature review. Library Hi Tech News 37: 1–5.

Badawi

(2021) Libraries as tools for promoting education in the society: an analysis of library utilization by women in Kano state. In: Paper delivered at the Nigerian Library Association, 42nd national conference and AGM, June 20th – 5th, 2021, Akure, Nigeria, p. 19.

Ball

(2019) Big data and their impact on libraries. American Journal of Information Science and Technology 3(1): 1–12. DOI: 10.11648/j.ajist.20190301.11.

Bamiah

Brohi

Rad

(2018) Big data technology in education: advantages, implementations, & challenges. Journal of Engineering Science & Technology 13: 229–241.

Chong

Shi

(2020) Big data analytics: a literature review. Journal of Management Analytics 2(3): 175–201.

Daniel

(2019) Big data & data science: a critical review of issues for educational research. British Journal of Educational Technology 50(1): 101–113.

10.

Daniel

(2020) Big Data & Learning Analytics in Higher Education: Current Theory & Practice. Cham: Springer, 1–272.

11.

Daniel

(2021) Big data and analytics in higher education: opportunities and challenges. British Journal of Educational Technology 46(5): 904–920. DOI: 10.1111/bjet.12230.

12.

Daud

(2018) Issues, challenges and opportunities of big data management in higher education institutions in Malaysia. Indian Journal of Science and Technology 11(4): 1–6.

13.

Fagan

(2020) Students perceptions of academic librarians students. Perceptions of Academic Librarians 37: 131. DOI: 10.1300/J120v37n78.

14.

Haddad

Ameen

Mukred

(2018) The impact of intention of use on the success of big data adoption via organization readiness factor. International Journal of Management & Human Science 2(1): 43–51.

15.

Hamad

Tbaishat

Al-Fadel

(2016) The role of social networks in enhancing the library profession and promoting academic library services: a comparative study of the University of Jordan and Al-Balqaa’ Applied University. Journal of Librarianship and Information Science 49(4): 397–408. DOI: 10.1177/0961000616656043.

16.

Hamad

Fakhuri

Abdel Jabbar

(2020) Big data opportunities & challenges for analytics strategies in Jordanian academic libraries. New Review of Academic Librarianship 28: 1–19. DOI: 10.1080/13614533.2020.1764071.

17.

Hanapiyah

Wan Hanafi

Daud

(2018) Issues, challenges & opportunities of big data management in higher education institutions in Malaysia. Indian Journal of Science and Technology 11(4): 1–46.

18.

Hwang

(2019) Adoption of big data in higher education for better institutional effectiveness. American Journal of Creative Education 2(1): 31–44.

19.

Jain

(2020) Promoting open access to research in academic libraries. Library Philosophy and Practice, Paper 737. Retrieved from: https://digitalcommons.unl.edu/libphilprac/737.

20.

Kaladhar

Naick

BRD

Rao

(2018) Application of big data technology to library data: a review. International Journal of Library and Information Studies 8(2): 25–30.

21.

Kamupunga

Chunting

(2019) Application of big data in libraries. International Journal of Computer Applications 178(16): 34–38. DOI: 10.5120/ijca2019918955.

22.

Maideen

Sheik

Olugbenga

(2019) A study on emerging technology trends in academic libraries: an overview. Reshaping of Librarianship, Innovations and Transformation.

23.

Martin

Thawabieh

(2017) The role of big data management and analytics in higher education. Business, Management and Economics Research 3(7): 85–91.

24.

Murumba

Micheni

(2017) Big data analytics in higher education: a review. International Journal of Engineering Science 6(6): 14–21.

25.

Olendorf

Wang

(2017) Big data in libraries. In: Suh

Anthony

(eds) Big Data and Visual Analytics. Cham: Springer, 191–202. DOI: 10.1007/978-3-319-63917-8_11.

26.

Onyenachi

(2022) Library Services and Uses. Aba: Jop-flows.

27.

Patade

(2020) Big data technology in libraries: opportunities & challenges. Studies in Indian Place Names 40(49): 413–422.

28.

Patel

Birla

Nair

(2022) Addressing big data problem using Hadoop and Map Reduce. In: 3rd Nirma University International Conference on Engineering, NUiCONE 2012, Ahmedabad, 07 December 2012, pp. 6–10.

29.

Rani

(2021) Big Data & Academic Libraries. International Conference on Big Data & Knowledge Discovery. Indian Statistical Institute. Retrieved from: https://km.ptar.uitm.edu.my/documents/10180/1099975/Big+data+&+Academic+Libraries.pdf/74bbc20c-cfc0-4cae-ba4b-ead791b8f406.

30.

Reinhalter

Wittmann

(2021) The library: big Data’s boomtown. The Serials Librarian 67(4): 363–372.

31.

Tarmidi

Ahmad

Roni

(2018) Readiness for big data among students in public universities. Global business and management research. An International Journal 10(3): 12–45.

32.

Togia

(2018) Attitudes towards open access: a synthesis of the empirical literature. Information Services and Use 34(1): 221–231.

33.

Umezuruike

Ngugi

(2020) Imminent challenges of adoption of big data in educational systems in Sub- Saharan Africa Nations. International Journal of Recent Technology and Engineering 8(5): 4544–4550.

34.

Wang

(2021) Big opportunities and big concerns of big data in education. Tech Trends 60(4): 381–384.