Data Tools: Assessing Datasets with Data Nutrition Labels
At-a-glance "ingredients list" and snapshot of dataset quality and composition — designed to help data teams assess fit before EDA and encourage responsible documentation by dataset creators.
What’s in Your Data? A Look at Data Nutrition Labels
In this post from Data x Direction, we explore the concept of Data Nutrition Labels—tools designed to promote transparency, trust, and accountability in datasets. Much like food labels, these frameworks help researchers, developers, and policymakers evaluate the quality, composition, and context of the data they use.
We review some recent examples and discuss what a more standardized, practical approach to "data transparency" might look like—especially in high-stakes or socially impactful applications.
👉 Read the full post on Data x Direction
🧭 This piece is part of our ongoing effort to bridge data science and social responsibility by exploring the tools that shape how decisions—and futures—are built.
Thanks for reading! I'm Jesse, a data scientist, strategist & founder, and interdisciplinary researcher & exploring how we lead, learn, and innovate in complex times. On this Substack, I write across a few core themes:
Leadership & Innovation Strategy — navigating vision, decision-making, and team dynamics
Data Science, AI & Ethics — building from my MSc DS, this is my main technical area at the nexus of emerging AI, human-centered technologies and responsible systems
Mentorship & Early Career Growth — advice and frameworks for changemakers at every stage
Projects & Dispatches — updates from JOPRO and other research and product endeavors
Reflections & Media — commentary on culture, books, ideas, and the future we're building
🔗 Explore the different sections here
🧭 You can also find my work with JOPRO, From Here to There, and Data x Direction
Subscribe to follow along, and reach out if something resonates—I’m always up for a conversation around mapping & building the future and the cultivation required to get there.