Abstract
The chapter showcases the awareness of big data usage among librarians in Zimbabwe. The concept of big data is new, and librarians are building capacity to move with the current trends in librarianship. This chapter assists in pointing areas where big data can be applied in libraries. It also documents the challenges that are faced when using big data applications and proffer solutions that can be applied to deal with those challenges. It answers the question of whether it is practical to utilise big data in any type of library. A qualitative study was done where an online questionnaire was administered to twenty librarians in research institutions in Zimbabwe. The findings revealed that librarians are aware of the big data concept but are not utilising the tools and techniques in data mining and analysis. The authors recommend that capacity building should be done to equip librarians with the requisite skills.
TopIntroduction
Big data has become a buzzword and catchphrase in the technology industry and academia. With big data organisations have come to know more about their operations than before. The big data revolution transcends across all industries and academic institutions stand to benefit from it. Libraries were not spared from the use of big data applications although the concept is still new to librarians. Zhan and Widen (2017) point out that big data is used to refer to different things depending with the field of study and its characteristics are not the same in various subjects. The emergence of the library 4.0 due to the changes in information communication technologies led to the generation of a lot of data in libraries as stated by Noh (2015). This chapter documents the awareness among librarians of big data applications in Zimbabwe. The objectives of the study were:
- 1.
To assess the knowledge of librarians about big data.
- 2.
To examine the use of big data by librarians
- 3.
To document the challenges faced by librarians when using big data applications.
The rest of the chapter has sections which documents the definitions of big data; big data applications in the library; use of big data by librarians; challenges of big data usage by librarians; methodology that was used for this study; findings; discussion; recommendations; areas of further study; conclusion; references; and definitions of key terms.
TopDefinitions Of Big Data
Even though big data has become so pervasive in today’s world, the term big data itself has been taken to mean a lot of things. Big data has instead evolved so quickly and disorderly that such a universally accepted formal statement denoting its meaning does not exist (De Mauro, Greco & Grimaldi 2015). Most researchers define big data in terms of its characteristics, the most common which are volume, velocity and variety (Zhan and Widen 2017). However, these definitions do not bring out the aspect that makes big data what it is, that is, the issue of the complexity of working with big data. The Method for an Integrated Knowledge Environment (MIKE2.0) project contends that complexity and not size is the dominant factor in defining and dealing with big data.
Zhan and Widen (2017) did a study on understanding big data in librarianship and provided a number of definitions for big data that were used by researchers. They found out that big data refers to the tools, processes, technologies or ideas for handling large amounts of data and the characteristics of such data which include volume, velocity, variety, value, and veracity. Some definitions included challenges, demand and benefits of big data in line with the changing technological landscape and what is needed in processing big data. Therefore, the definition that would be used in this study includes a mixture of the MIKE.2.0 definition and the characteristic based definition;
Big data is a term describing the storage and analysis of large and or complex data which exceed(s) the capacity or capability of current or conventional storage, computational methods and systems, has high volume, velocity and is composed of a variety of data types and sizes.
TopBig Data Applications In The Library
Li et al. (2019) opine that few studies have been done relating libraries to big data. Therefore the question is, “Do libraries have big data at all?”. Libraries have moved from the traditional setup where the only data generated by the Library Management System and resources were catalogued meticulously via a limited set of metadata. Nowadays, libraries now collect data from a variety of sources both structured and unstructured data and no longer focus on books, journals and catalogue data only (Ball, 2019). Library data sources include, LMS transactions, library social media applications, blogs, texts, metadata, images, audio files, videos, research data, 3D digital copies and software, chat facilities and user generated data (Ball, 2019; Zhan and Widén, 2017). A number of scholars have pointed out that libraries have lots of data which fits the definition that was adopted for this paper. Simovic (2018) is of the view that the complexity of data collected by libraries and the different types of formats and sources qualifies it to be categorised as big data.
Key Terms in this Chapter
Digital Divide: The gulf between those who have ready access to computers and the Internet and those who do not have that facility.
Librarian: A person trained in library science and engaged in library service.
Electronic Resources: Are materials in digital format accessible electronically using a computer which is connected to the internet.
Big Data: Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
Library Management System: Enterprise resource planning system for a library, used to track items owned, orders made, bills paid, and patrons who have borrowed.
Data Librarian: Librarian engaged in managing research data, using research data as a resource, or supporting researchers in these activities.