The Accidental Data Scientist: Big Data Applications and Opportunities for Librarians and Information Professionals

Citation

Gillian C. Oliver (2015), "The Accidental Data Scientist: Big Data Applications and Opportunities for Librarians and Information Professionals", Library Review, Vol. 64 No. 4/5, pp. 405-406. https://doi.org/10.1108/LR-03-2015-0030

The foreword by Thomas Davenport says it all. He makes reference to a paper written with Larry Prusak over 20 years ago which called into question the narrow focus of corporate librarians and the consequent danger of them becoming surplus to requirements (Davenport and Prusak, 1993). In The Accidental Data Scientist, Amy Affeldt provides insight into an area where the knowledge and skills of librarians and other information professionals are sorely needed. Given the length of time since Davenport and Prusak sounded the alarm, it is a little disturbing to realise that the information professions still seem to need to be alerted to the opportunities in the ever-evolving technological environment. As Affeldt herself asks in the introduction, “How is it that we keep missing these opportunities to transfer our skill sets and expand our career opportunities into cutting edge technologies?” (p. 3).

The book does not aim to answer this question, but instead sets out to explain to practitioners the nature of big data and to demonstrate how that understanding can be put to effective use. Accordingly, the first three chapters explain what big data are, what tools are used by technologists to process big data and argues convincingly for the appropriateness of librarians’ skills to work with big data. The next section of the book explores practical application of tools and techniques, such as Google Fusion Tables, Infogr.am, Text is Beautiful, Statwing, Tableau Public and BigML. A snapshot of big data applications by sector (health care, transportation, entertainment, legal, science and politics) provides a wealth of examples which demonstrate big data in action.

The final part of the book zeros in on roles for librarians and information professionals in the world of big data. Affeldt makes it clear that their skills come into play after big data have been programmed and formatted by computer scientists, when further analysis is needed. For example, to provide the context necessary to interpret a particular data set or to construct a narrative that illuminates the reliability and provenance of data. A further chapter is devoted to exploring the use of big data to respond to reference requests. In the final chapter, the discussion returns to career opportunities for librarians in a world characterised by big data. The point is made that traditional library positions are decreasing in number due to shrinking budgets and globalisation – the outsourcing of jobs to offshore locations. This is in contrast to an increasing number of jobs working with big data and documented skill shortages in this area. Affeldt provides very practical advice about how job seekers can present their library skills as being relevant to prospective employers. The range of data scientist jobs is illustrated with a sample list of position openings, although the inclusion of “digital archivist” as an example of a big data job is sadly misleading.

This book will be of value to anyone seeking to broaden their employment prospects and go beyond a narrow conceptualisation of library work. It should also be of considerable interest to anyone concerned with the future of libraries and librarians.