Data Science for Real People in the Real World
THE DATA MOM
My work changed when data became personal.
As both a data scientist and the parent of a child with a rare disease, I understand that data are never just numbers. They represent people, families, decisions, and hope. That perspective shapes everything I do — from research strategy and analysis planning to data quality, communication, and interpretation.
Watch JHU Grand Rounds presentation, Dr. Danielle Boyce & the Lived Experience in Observational Research Informatics Grand Rounds 4/13/23.
Careful Planning
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Thoughtful Analysis
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Trusted Results
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Careful Planning · Thoughtful Analysis · Trusted Results ·
My Approach
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Understand the Context
Good analysis begins before the data set opens. We start by clarifying the science, the people, the goals, and the decisions this work needs to support.
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Make a Practical Plan
Together, we create a clear path forward: research questions, key variables, timelines, deliverables, and the analytical approach. No vague handoffs. No black boxes.
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Roll Around in the Data
In the real world, data are rarely clean or simple. I look closely at structure, missingness, data quality, patterns, and surprises so the analysis reflects what the data can actually support.
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Deliver Work You Can Use
I communicate clearly, document decisions, explain limitations, and deliver thoughtful, reproducible work that helps you move forward with confidence.
ABOUT ME
I’m Danielle Boyce — a data analyst, researcher, teacher, writer, and rare disease mom. For more than three decades, I’ve helped people make sense of complex, messy, real-world data.
I work in several areas at once: data science, informatics, clinical research, patient advocacy, and education. I partner with researchers, clinicians, students, nonprofit organizations, and patient communities to turn data into insight — especially when the answers are difficult, urgent, and deeply human.
What I do
I currently serve as Director, Data Science and Biomedical Informatics and Principal Investigator, Real World Evidence at the ALS Therapy Development Institute. I am also affiliated with Johns Hopkins University’s Biomedical Informatics and Data Science Section, the University of Calgary, Emory University, and Data for the Common Good at the University of Chicago.
My expertise includes real world evidence, with a specialty in the secondary use of electronic health records for research, FHIR, Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), biostatistics, and multiple programming languages.
My most popular contributions are Registry Forge - Enterprise and Registry Forge - Patient Edition, an open source pipeline for getting your EHR data into research-ready shape free, using tools you already have.
Data analysis is technical work. It is also human work.
When my son Charlie was born with a rare neurological condition, the meaning of data changed for me. I began to understand, in a much deeper way, that every data point represents a person, a family, a decision, a delay, or a possibility.
That experience continues to shape how I approach analysis: with rigor, humility, curiosity, and care.
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"Danielle is a true pioneer — one of those rare 'unicorns' you encounter only a few times in a career. She has been a tireless advocate for her son since his birth, fighting countless battles on his behalf with such grace and poise that she elevates everyone around her. As a data scientist, she is nothing short of phenomenal — taking on challenge after challenge, championing the rare disease community while holding the science to the highest standard. I am deeply fortunate to know Danielle, and I continue to be inspired by her energy, compassion, and brilliance. "
—Samuel Volchenboum, MD, PhD
Director, Data for the Common Good, University of Chicago
BOOK TIME WITH DR. DANIELLE!