Federer, L. (Ed.). (2016). The Medical Library Association Guide to Data Management for Librarians. Rowman & Littlefield.
The Medical Library Association Guide to Data Management for Librarians (published by Rowman & Littlefield; September 2016; $65 paperback or $125 hardback) attempts to prepare librarians to meet the growing demands for data management assistance and instruction with chapters from librarians across the spectrum of libraries, including medical libraries, academic libraries, government libraries, and special libraries. The growing desire for data management services makes this edited volume particularly timely.
Lisa Federer, who edited the volume, is a well-known research data informationist at the National Institutes of Health (NIH) Library, holding an MLIS from UCLA, an MA in English, and graduate certificates in data visualization and data science. The other contributors are similarly well-credentialed, representing individuals with PhDs or library science degrees, researchers from different areas, and data scientists and librarians.
The volume is separated into three parts: Data Management: Theory and Foundations; Data Management across the Research Data Life Cycle; and Data Management in Practice. The final product provides a useful and expansive discussion of data management, making this an important book for librarians who are just getting their feet wet in the field, which is likely the case for many librarians who don’t have experience in data management but who are being asked to provide these services. However, this broad brush also means that some depth is lost. The chapters are generally short with about ten or fewer pages of text, which provides a useful and brief introduction for librarians to start thinking about data services—further facilitated by the “pearls” providing at the end of each chapter, reflecting key points. They also generally provide recommended readings and the bibliographies are extensive sources for possible future reading.
Nonetheless, as seems to be the case in many edited volumes, the usefulness and rigor of chapters is fairly variable. Several chapters fall too far down the theory rabbit hole. The chapters are already fairly short, which becomes more of an issue when half of the chapter is taken up in regurgitating theory. For example, the chapter “Data 101” spends considerable ink discussing adult learning theory but then only provides short paragraphs on interesting topics such as data information literacy. The chapter “Library Infrastructures for Scholarship at Scale” buries itself in theory to make the simplistic claim that different disciplines have different data needs.
On the other hand, many of the chapters provide incredibly useful insights, such as the chapter on Data Information Literacy (DIL), which expands on the lacking definition in “Data 101” to develop the topic, and the chapter on data visualization which provides practical advice for providing data visualization services in the library. Further, the final section on Data Management in Practice, provides important context in the academic library, the undergraduate population, the medical center, the lab, and the hospital, providing useful examples of the variance in implementation throughout different communities and environments.