Data Disaggregation Action Network

What is data disaggregation?

Disaggregation means breaking down large data categories into more specific subcategories. “Data disaggregation” refers to the collection, reporting, and analysis of information on specific subgroups by race, ethnicity, and other characteristics. When data are disaggregated, researchers are better able to analyze differences between groups, as well as the relationship between multiple variables, such as race and age.

Why do we need disaggregated data?

Aggregated data hide inequities. In many existing state and federal data collection systems, data are not sufficiently disaggregated by race and ethnicity (including subgroups and first language), sex (including sexual orientation and gender identity), disability, age, income, and other characteristics like geographic area or social determinants of health. This masks the nuanced realities of many communities behind larger trends, and makes it more difficult to address inequities. As just one example, aggregate data may perpetuate the model minority myth — that all Asian Americans have high levels of income, homeownership, education, and health — but disaggregated data reveal large disparities among AANHPI groups. For instance, the percentage of Asian Americans living below the poverty line ranges from 6.8 percent of Filipino Americans to 39.4 percent of Burmese Americans.

What are we doing about it?

The Education Fund and our partners in the Data Disaggregation Action Network are working to advance federal and state policies as they relate to data disaggregation by race and ethnicity. Through the creation of a state and national advocacy infrastructure to engage stakeholders and policymakers on the need for disaggregated data, we will ensure the collection, analysis, and reporting of critical federal- and state-level data that will help to identify gaps in and achieve racial equity.

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Data disaggregation resources

Resources on OMB race and ethnicity standards revision

The U.S. Office of Management and Budget (OMB) is currently in the process of revising its Statistical Policy Directive No. 15: Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity (Directive 15), which sets forth the minimum categories that federal agencies must use when they collect information on race and ethnicity.

See here for resources providing background on the current standards and information on the initial proposals for revisions by OMB’s Federal Interagency Technical Working Group on Race and Ethnicity Standards.

The Leadership Conference and several members of our Data Disaggregation Action Network submitted comments on OMB’s initial proposals, calling for modernized race and ethnicity data standards that will better reflect the diversity of our communities. See comment letters below from:

Research and reports:

Data report series from The Leadership Conference:

Data disaggregation blog series