You can’t fight for something you don't know exists. That’s the problem a new guide to federal data aims to solve. UC Berkeley Executive Fellow in Applied Technology, Denice Ross, who served as the nation’s second U.S. Chief Data Scientist, and her former White House colleague Christopher Marcum have launched the Federal Data Field Guide, a free, plain-language resource designed to help Americans understand, use, and advocate for the full breadth of federal data.
“Federal datasets each have their own characteristics, use cases, and even personalities,” Ross said. “Too often, we think of federal data as limited to jobs, weather, and other high-profile datasets. This Field Guide widens the aperture so data users, advocates, journalists, AI engineers, and policymakers can have a clear-eyed understanding of the full diversity of the federal data ecosystem.”
“This Field Guide widens the aperture so data users, advocates, journalists, AI engineers, and policymakers can have a clear-eyed understanding of the full diversity of the federal data ecosystem.”
The guide addresses a fundamental gap: many people need to use federal data, but lack a mental model for the types of data the federal government produces. Without understanding collection methodologies, policy contexts, and the different categories of data, it is easy to overlook or take for granted datasets that are essential for running a modern society.
With the current Administration signaling changes to federal data policy and agency capacity to produce datasets, understanding the fundamentals of different types of federal data is increasingly urgent.
Marcum said, “It’s our hope that the Field Guide raises awareness about the great diversity of federal data and that it connects people to types of data they find new and exciting. The federal data ecosystem is much more resilient when more people know about, care about, and can advocate for the unique value of datasets that may be endangered.”
The Federal Data Field Guide is organized into eight categories of data: statistical data that measure population-level characteristics, administrative data generated through routine government operations like filing taxes or applying for assistance, geospatial data capturing spatial and environmental information, scientific data advancing knowledge across disciplines, accountability data for the primary purpose of transparency into government activities, evaluation data assessing program effectiveness, navigation data helping citizens access government services, and reference data providing standardization across systems. Each category has different collection methodologies, quality considerations, and range of appropriate uses, including a case study that features how a specific federal dataset benefits everyday Americans
This Federal Data Field Guide includes more than eighty specific examples of federal datasets across more than 50 federal agencies. It also provides plain-language explanations of the policy and legal contexts governing federal data collection and release, including policies on privacy, security, and transparency.
Professor Deirdre K. Mulligan of the School of Information, who established the Executive Fellowship in Applied Technology Policy, said she is “honored that the Executive Fellowship in Applied Technology Policy was able to provide the intellectual and creative context for this Federal Data Field Guide to become a reality. The Field Guide is a shining example of the enduring public benefits of providing tech policy leaders with an opportunity to reflect on their pivotal contributions to the country within an academic setting.”
The Federal Data Field Guide is available at: federaldatafieldguide.us/
Media Contact: Caitlin Appert-Nguyen cappert@ischool.berkeley.edu
The Field Guide was developed as part of Denice Ross’ Executive Fellowship in Applied Technology Policy at UC Berkeley’s School of Information and Goldman School of Public Policy. The fellowship program brings government technology leaders into academic settings to develop resources that bridge policy and practice. Berkeley student researchers Saanvi Arora, Chelsea Chen, and Isabelle Qian provided valuable research, writing, user engagement, and expertise on information organization and retrieval.
