The Medical Library Association guide to data management for librarians

It has been clear for more than a decade, even before “Big Data” became the buzzword du jour, that all areas of research have seen a shift from human-scale data to data sets that are beyond human-scale in their size, scope, and how they can be manipulated. Mandates from funders for data transparency, increasing requirements to deposit data as an essential submission element for publication in top-tier journals, and the establishment of supplemental National Institutes of Health (NIH) grants to support the work of librarians on multidisciplinary research teams have all helped bring opportunities to expand our scope of practice to be more directly involved with all aspects of the research data life cycle. The Medical Library Association Guide to Data Management for Librarians, edited by Lisa M. Federer, comes at an opportune time when interest and demand for librarian expertise in this area is growing exponentially. Federer, a research data informationist at the NIH Library, is well known in the profession as a strong advocate for, and expert in, expanding the role of librarians in the research enterprise. Her expertise is clearly communicated throughout the book from the preface, her contributed chapter, and her introductions to each section which place the contributions of the other authors in context. Additionally, the table of contents reads like a “who’s who” in research data management. Each author contributes a unique voice and perspective to create a well-curated mix of theory, practice, and emerging issues and challenges in data management. The book is divided into three sections: Data Management: Theory and Foundations; Data Management Across the Research Data Life Cycle; and Data Management in Practice. The first section touches on many disciplines that have influenced the development of data management as a practice, including data science, archival practice, and digital curation. This section also covers the structures and policies that affect data management initiatives, with chapters that discuss the economic and scientific case for data re-use, funder perspectives, and the importance of determining user needs and preferences when creating programs that support data disclosure. It closes with a chapter that suggests a range of resources for librarians who want to keep their skills current or learn more about specific data-related topics. Section two focuses more intently on supporting researchers throughout the research data lifecycle. It includes several chapters on data management planning and related