Big Data, Little Data, No Data

Once again, Borgman hits it out of the park. She moves beyond the trendy discussion of 'big data' to focus on the real issue: data, the very concept of which differs among scholarly communities. The challenges to successful data sharing are legion, and she spells them out in detail. Those who follow her insights will save a lot of time and money.

John Leslie King, W. W. Bishop Professor of Information, University of Michigan

We live amidst a sea of data. In Big Data, Little Data, No Data, Christine Borgman explores the depths and swells of that data and how they connect with scholarship and, more broadly, systems of knowledge. The result is an invaluable guide to harnessing the power of data, while remaining sensitive to its misuses.

Jonathan Zittrain, Professor of Law and Computer Science, Harvard University; Co-founder, Berkman Center for Internet & Society; Director, Harvard Law School Library

Data by itself has no value. It's the ever-changing ecosystem surrounding data that gives it meaning. Borgman gets all of this and much more. Big Data, Little Data, No Data is filled with thoughtful discussion, examples, and case studies that provide a foundation for the much-needed conversations and decisions to be made about research data. This book is a primer for anyone trying to understand data relevancy in scholarship today.

Gregg Gordon, President and CEO, Social Science Research Network

This reading might be of enormous value to interdisciplinary scholars, seeking to test or adapt different data methods, but also for students, that need to get introduced to them. Without holding back, I would recommend this book, for its clarity, well-organised arguments and throughout approach as a university handbook in the area. It is more than enough to get known to status, practices and procedures concerning any type of data in different research field areas.

Leonardo

Big Data, Little Data, No Data is no mere bibliography or literature review, nor is it a how-to-do-it manual on data curation. It is an extended thought-piece, firmly grounded in the author's extensive experience with all-things data, and her knowledge of the work and writings of hundreds of other scholars over time.

Journal of the Association for Information Science and Technology