If you’re a data management enthusiast like me (yes, we exist, and there’s actually a bunch of us), you’ve probably head about Kristin Briney’s Book, “Data Management for Researchers.” I received a copy for review a few months ago, and have been taking my time to savor it.1 But if you’ve heard of this book, chances are that although you’ll certainly find aspects of it useful, you’re probably the metaphorical choir that we, the data managers, are preaching to. You might even argue that there are lots of data management resources out there- why a book? But Briney does something unique here, and I have been enthusiastic to recommend it to everyone around me.2
This book offers a fantastic overview of all things data management, and -here’s the really important part- explains it all within the value system which currently dominates academic culture. Often, open science advocates, myself included, approach persuading people to become better data managers for idealistic, esoteric reasons.3 This can make our arguments sound a little tone-deaf, because proposing a radical shift in practice without tying it to the realities and constraints the researchers face (i.e. no time, evaluation based on impact factors and grantsmanship)- well, for many of the practices we advocate for, it just looks like opportunity cost. The thing is, open science, data management, reproducible practice isn’t just that- and this book shows us why. Data management makes all researchers better scientists.
This is a book that an open science advocate can hand to an academic administrator or a new graduate student, and they can flip through, and think “Hmm, these practices will help make my life easier and help me meet my goals and succeed by the metrics used to evaluate performance in the paradigm in which I exist!” 4 Briney lays it all out. She starts by dedicating the book to the memory of data lost, and then, chapter by chapter, outlines another important concept in data management. Each chapter starts with an anecdote (often, a cautionary tale) about some aspect of the typical research lifecycle that is affected by data management. She advocates a baby-steps approach:
Remember that good data management need not be difficult or complex, but instead is often the summation of many small practices over a range of data-related topics. The best solutions are the ones that become a routine part of your research workflow.
This book covers data management from before collection – data management planning- to sharing and reusing other people’s data, with specific reference to best practices, constraints, and concerns a data creator or user may face. Each topic is covered comprehensively and grounded by real-world examples peppered throughout, making the material relatable. Not all sections will be directly relevant to all researchers (for example, I’ve never had to anonymize data because the IRB doesn’t care if insects get doxxed), but it was certainly enlightening to read (and I read that I could save myself a lot of trouble by never working with human data 🙂 ) but much of it is relevant to all (see: metadata). This book is really for all researchers- those that love data (treat your data right!) and even those that hate data and all things quantitative (handle your data efficiently so you have to spend less time on it overall!).
I, personally, will use this book in a variety of ways- primarily to supplement my own cache of cautionary tales and anecdotes about data management, and as a way to connect what I do for open science5 to what I do in the lab/field/office. But I also intend to give a copy of this book to each graduate student / trainee that joins my lab, should/when this whole faculty job search pans out and I get my own lab.6 Putting this all out there, getting students on board with the ideas and techniques to treat data with the respect it deserves, will help us all succeed, by whatever metric, whatever paradigm.
1. Read: being mildly negligent about reviewing it while traipsing around the globe like some sort of bon vivant.
2. Read: shoving it in front of people at bus stops, leaving it on the lunch table. I’m insufferable.
3. Save the world! Advance the field!
4. This is what the voice in other people’s heads sound like, right?
5. I do this sort of thing. Professionally. Not all the time. But some of the time.