vol. 27 no. 3, September, 2022

Book Reviews

Herndon, Joel (Ed.) Data science in the library: tools and strategies for supporting data-driven research and instruction Facet Publishing, 2022. xxx, 146 p. ISBN 978-1-78330-459-2. £60.00.

As a student, I have been taught, by my very meticulous teacher, to make sure that when writing one knows the definitions of the used terms. One of clear distinctions between terms denoting an activity was the type of this activity, which could be: professional (leading to a certain result, a product or a service) or just practical (the same, but relating to a result produced by non-professional for everyday purpose, e.g., grandma's buns), research or scientific (producing new knowledge), educational (producing competent members of society or labour force), or leisure (restoring the working capacity of workers). If we explore the term of 'data science' from this point of view, it will become clear that it means all types of actiivities and, thus, should be defined specifically for each setting or in each text. The Introduction to this book rather clearly states on p. xx that the authors are not limiting the term by any definition and leave it as a 'multi-faceted space... increasing research, instruction and job opportunities...'

A reader has to keep this multiplicity of meanings in mind when reading the book as it may mean professional work in providing data services for the purposes of researchers in this field, or instruction of professionals and students. This is quite legitimate within the environment of academic library where researchers explore data science, librarians provide data services and students are trained in both, the research area and the delivery of services. This little book, however, mainly addresses the professional and educational aspects of the data science within academic libraries, though some aspects of research area may be introduced by the authors of some chapters (e.g., Chapter 8 on research data management at the University of Washington).

The chapters consist of presentations of spacific cases, mainly in the United States university libraries (Chapters 1, 3, 4, 5, and 6), but also in Spain (Ch. 2) and Denmark (Ch.7). In the final chapter the editor of the book provides a discussion and the analytical summary of the content of the previous chapters. Several chapters address some educational aspect: training in data science for researchers (Ch. 1), professional development of librarians (Ch. 3 and 7) and instruction of students (Ch. 4). Chapters 2 and 6 are devoted to the development of data services, mentioning professional competence among other necessary conditions for these endeavours. Both these chapters take a historical perspective on how the services have evolved.

The overall impression that this collection leaves is about one more task that academic libraries seek to drive a stake in as a natural expansion from earlier open access repository management. It seems that they are again facing similar issues as in the case of open access: the lack of resources (both material and competence), and despite seeming competition from other academic units, they will succeed in taking over this new field as the others will leave it happily in their hands because of its complexity and lack of administrative support from the top managers of universities. I wonder, where from I got this impression while reading about successful cases presented in the book?

All the chapters are written by the experts in the area and provide much richer and wider context of each case, not only its plain description. The authors are intimately involved in these cases and know well what they are talking about from professional and academic point of views.

I believe that this book will be of use to practicing librarians and information professionals even outside the academic environment as the data (research, business or e-commerce) management has turned into one of their main activities. The described cases, though related to universities may provide useful material and become a source of interesting solutions in any data management area.

Elena Maceviciute

University of Borås
August, 2022

How to cite this review

Maceviciute, E. (2022). Review of: Herndon, Joel (Ed.) Data science in the library: Tools and strategies for supporting data-driven research and instruction Facet Publishing, 2022. Information Research, 27(3), review no. R741 [Retrieved from http://www.informationr.net/ir/reviews/revs741.html]

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