The Data Management Workbook: Practical Exercises for Better Organization, Storage and Use of Your Research Data (Paperback or Softback)

Data management and sharing are standard expectations of researchers across the sciences. But while you might have been given some basic guidelines and requirements for a data management plan, it’s not always easy to put these into practice or figure out how to adapt them to your specific research.

The Data Management Workbook helps researchers design useful data-management plans through a step-by-step series of structured exercises, worksheets and checklists, including:
- creating a data dictionary
- evaluating a lab notebook
- finding the best way to organize your files
- setting up useful file naming conventions
- writing effective README.txt files
- selecting the right data repository
- determining data stewardship
- preparing data for future use

Suitable for researchers working in many different disciplines, this guide also shows how to customize data-management plans to better fit your individual workflows, methodologies, laboratories and datasets. Author Kristin Briney builds on the foundations in her previous book, Data Management for Researchers, to help bridge the gap between understanding the principles and being able to implement data management as part of your research practice.

If you want to manage your research data better but don’t know where to begin, this short workbook will help you get started!

Kristin Briney is the Biology & Biological Engineering Librarian at the California Institute of Technology. She is the author of Data Management for Researchers and coauthor, with Becky Yoose, of Managing Data for Patron Privacy. She has a PhD in chemistry and an MLIS, both from the University of Wisconsin-Madison. She specializes in research data management, institutional data policy, and patron privacy with respect to library data handling. Kristin is an advocate for the adoption of the international date standard ISO 8601 (YYYY-MM-DD) and likes to spend her free time making data visualizations out of yarn.