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1. Introduction
Data science is a relatively new term which has gained considerable attention in recent years. The search of this phrase provides now more than 76m hits in Google. The data science field has emerged in response to the increased amount of data. Huge amounts of data have become available to people at all levels of society, through social networks, mobile devices and various sensor devices (i.e. “the Internet of Things”). These new types of data, in enormous volume, in various forms, often complex, unstructured and volatile, are being generated at an accelerating rate (Virkus et al., 2018). The majority of digital data is generated by consumers, in the form of movie downloads, VOIP calls, e-mails and cell-phone location readings (Regaldo, 2013). Cukier and Mayer-Schönberger (2013), defining this process as datafication, note that transforming all things under the sun into a data format and thus quantifying them is at the heart of the current world. Just as electricity changed industrial processes and domestic practices in the nineteenth century, a data-driven paradigm is the core of twenty-first century processes and practices (Schäfer and Van Es, 2017, p. 11). Yet only about 0.5 percent of data is ever analyzed (Regaldo, 2013). There is so much more data out there than anyone can capture or analyze and therefore the concept of data overload has been suggested (Virkus et al., 2018).
At the same time, computers have become much more powerful as technology has advanced, “networking is ubiquitous, and algorithms have been developed that can connect data sets to enable broader and deeper analyses than previously possible” (Provost and Fawcett, 2013, p. 51). This has led to the emergence of data science (Cervone, 2016). van der Aalst (2016, p. 4) notes: “Data abundance combined with powerful data science techniques has the potential to dramatically improve our lives by enabling new services and products, while improving their efficiency and quality.” This presents an opportunity for better decision making and strategy development (Aristodemou and Tietze, 2018, p. 37).
European library and information science (LIS) education has met a number of challenges in recent years including the financial crisis, negative demographic trends in some countries, emerging technologies, internationalization and globalization. For this reason, innovative ways to survive and achieve...