The Ideal Eviction Data Landscape

Responding to the challenges outlined in the last section, we envision an eviction data landscape governed by the following principles:

• Easy to Access: Data is easy for interested parties to locate, and available for free.
• Easy to Use: Data is easy to search, analyze, and draw insights from; supports a variety of uses; is provided up-to-date; is portable; and is easy to link with other useful data.
• Standardized across Jurisdictions: Data is comparable and uniform, with a shared taxonomy between counties.
• Centralized: Data is aggregated into a state or national database.
• Comprehensive and Reliable Quality: Data is comprehensive from the standpoint of geographic and temporal coverage, and all data points are consistently captured.
• Ethical, Equitable and Privacy Preserving: Data is privacy preserving and are also collected, stewarded, and shared through an equity lens that ensures data is not misrepresenting, under-representing or damaging vulnerable populations.

A specific set of changes must occur at both the national and local level to take us from the current eviction data landscape to the ideal eviction data landscape. These changes are broadly outlined below:

• Funding and staffing. Municipalities must dedicate financial and human resources to collecting, analyzing and sharing eviction data, and setting up rules and models for its stewardship. This may involve hiring new staff (for example, database administrators) and/or investing in building a data system, as well as investing in communications to share data insights with relevant audiences.
• Buy-in and political will at the local level. Streamlining data systems will require coordination across several different actors at the state level, including local policymakers, court administrators, data vendors, legal aid providers, housing rights organizations, among others. The federal government will need to use its political will to help shape local action, and local leadership will need to prioritize data collection and standardization. Courts will need to adopt data standards and be willing to put the protections in place to share their data. In many cases, this will require lowering the political cost of cooperation, notably in jurisdictions with high volumes of evictions, changing court culture to prioritize eviction data, and creating incentives for municipalities to prioritize eviction data.
• Legislation and regulation. Congress may need to pass legislation and Federal and State agencies may need to pass corresponding regulations that provide funding and infrastructure for data collection and standardization, as well as the oversight to ensure compliance with data standards.
• Building or improving data capacities and competencies. Local jurisdictions’ eviction data infrastructure exists at differing states of maturity. Municipalities will need to assess their own data infrastructure and determine where there are deficiencies and where there are opportunities to build on analyses. This includes creating data verification processes (e.g., to spot systemic undercounts or overcounts); developing protections against the misuse of data (e.g., code of conduct); collecting demographic data with a racial equity lens with sufficient granularity; simplifying data access procedures; and creating better data management tools to better link data sources.