About¶

The book¶

Slow Registry: Old-Fashioned Tools for Building High-Quality, Reproducible Research is a free book published on this site. It brings together the reading, the case studies, the graphics, exercises on a fictional practice registry, and the Slow Registry Workbook, so the book, its practice, and its templates live in one place and change together.

This is version 0.9. It is a living book, revised as it grows and as readers contribute. Danielle Boyce's other books are listed on her LeanPub author page.

The author¶

Danielle Boyce, MPH, DPA, is a data scientist and informatician. She is Director of Data Science and Biomedical Informatics at the ALS Therapy Development Institute, is on the faculty of Johns Hopkins University and Emory University, and is an AI, research, and data science advisor to many rare disease groups. As the parent of a child with a rare disease, she has served on patient and caregiver advisory panels for the Patient-Centered Outcomes Research Institute, the U.S. Food and Drug Administration, academic institutions, pharmaceutical companies, and nonprofit organizations. She is the author of the Ten Habits series, including Ten Habits of Great Data Analysts and Ten Habits of Great Grant Writers.

Registry Forge, a free, open-source pipeline for turning patient-directed health record data into research-ready outputs
Registry Forge, Patient Edition, which turns a person's own downloaded health records into a research-ready data set and walks them through getting the records
The Ten Habits Series, the Ten Habits books with their free companion tools for data analysts and grant writers
Demonstration registry, a mock-up of a multi-condition registry seen from both sides: the participant journey, with live counts of the questions asked, and the study team's workspace
Boyce Data Science

Privacy¶

The site has no analytics, no sign-in, and no cookies of its own. Entries in the workbook and clicks in the interactive lab stay in your browser and are never sent anywhere. GitHub, which hosts the site, keeps standard server logs.

License¶

The text, exercises, workbook, and practice data are licensed under Creative Commons Attribution 4.0 International (CC BY 4.0): you may share and adapt them for any purpose, including in your own trainings, with credit. The site's code is licensed under the MIT License.

How to cite¶

Boyce D. Slow Registry: Old-Fashioned Tools for Building High-Quality, Reproducible Research. Version 0.9. Boyce Data Science; 2026. https://boycelab.github.io/SlowRegistry/