Dallas Homestead Exemption Map

The Texas homestead exemption is a meaningful property tax break, for households that claim it. In Dallas, the exemption can save a family hundreds to thousands of dollars per year, and stacking it with the over-65 or disability exemption multiplies that.

But take-up is uneven. Some neighborhoods file at near-universal rates. Others, often the same neighborhoods with the highest housing-cost burdens, leave the exemption on the table. The disparity is visible if you can see it, but Dallas Central Appraisal District (DCAD) data is published in a form that doesn't surface it. There was no public tool that let advocates, policymakers, or residents see who was claiming and who wasn't, broken down by neighborhood and demographics.

Without that visibility, outreach campaigns to expand take-up were essentially flying blind.

I built an R Shiny application that joins DCAD parcel data to American Community Survey demographics and renders the result as an interactive choropleth across three geographic scales (census tract, zip code, and neighborhood) with equity-focused filters.

The tool lets a user:

• See exemption take-up by tract / zip / neighborhood across the entire county
• Filter by race/ethnicity composition and household income to surface disparities
• Compare year-over-year changes to track the impact of outreach efforts
• Download the underlying data and a summary report for further analysis

Three design decisions shaped the final product:

• Equity defaults. The default view doesn't ask "where are exemption rates highest?" That question is uninteresting. It asks "where is the gap between high-burden households and exemption take-up largest?", which is the question the tool exists to answer. Default framing tells the story.
• Color scale honesty. Choropleth color choices can mislead. We chose a single-hue ramp anchored at the county median to make over- and under-take-up visually symmetric, rather than a divergent scale that implies a "right" rate.
• Multiple geographies. Tract-level data is statistically cleaner; neighborhood-level is more legible to non-technical users. We supported both rather than choosing one.

Hosted at dallashomesteads.tools.cpal.org with public access. No login, no friction.

The tool is built for Dallas housing advocates working to identify neighborhoods where outreach can have the highest impact, for policymakers evaluating proposals to expand exemption access, and for residents who want to check their own neighborhood's exemption rate.

It exposes downloadable reports and open data for journalists and researchers covering Dallas housing affordability. Internally at CPAL, it sits alongside other equity-focused analytics tools that support program design.

The lesson I keep coming back to from this project is that a data tool is making an argument whether you intend it to or not. Default views, color scales, filter orderings, what's foregrounded in tooltips: all of it shapes what the user concludes. The "neutral" choice is a choice.

For an equity-focused tool, getting the framing right is half the work. Showing exemption take-up rates without context implies the rate is the metric. Showing the rate alongside household income reframes the question to "who is left out." Same data, different conclusion.

The other lesson: geospatial transparency is advocacy. A static report on exemption disparities makes a number of points. An interactive map that lets a user pull up their own zip and see the gap makes one, and it's the one that tends to move people.