Continuing our Practicing Data Equity series, Part 2 of our Tools for Data Equity post explores additional frameworks, approaches, and tools for building data equity in your research practices, especially those that center community-based approaches. This post is meant to serve as an introduction to these resources and we encourage you to click through to explore them more in depth on your own. This blog has been divided into two parts. You can read Part 1, which focuses on how our worldviews impact the research process here.
Principles for Advancing Equitable Data Practices
The Principles for Advancing Equitable Data Practices by the Urban Institute, a nonprofit research institution, advocates for applying the 1979 Belmont Report three principles for protecting human subjects – justice, respect for persons, and beneficence – throughout the data life cycle in a way that makes “affected communities and groups of people a first-tier consideration.” Although the principles have been institutionalized in the practice of institutional review boards (IRBs), they suggest that a more general application is necessary to ensure collective harm is considered in addition to potential harm to individuals, to evaluate the impact of secondary and aggregate datasets, which is typically exempt from review, and to keep up with changes in data and technology. You can read their report and about their Principle-Aligned Practices for the Data Life Cycle in more detail here.
The Urban Institute also offers the following resources and tools for thinking about your data through an equity lens:
- A guide for Applying Racial Equity Awareness in Data Visualization
- Video of a webinar with slides on Centering Racial Equity in Data Use
- A data walk methodology which shows a way for community stakeholders to engage in dialogue about research findings about their community
- A spatial equity data tool for evaluating bias in datasets policymakers use to make decisions or in how resources are distributed
Toolkit for Centering Racial Equity Throughout Data Integration
The Toolkit for Centering Racial Equity Throughout Data Integration was created by Actionable Intelligence for Social Policy (AISP) at the University of Pennsylvania. It acknowledges that although cross-sector data sharing and integration can turn individual-level data into information to support community needs, it can also be used to reinforce racist policies and inequity. The authors of the toolkit compare the potential of data infrastructure to the impact of railroads and highways on communities, creating wealth and opportunities for some, while displacing others and offer strategies and best practices for using a racial equity lens.
The toolkit provides the following frameworks, tools, and activities:
- A framework for understanding your individual and institutional starting point and planning for change
- Tips for centering racial equity throughout the data life cycle, including examples of positive and problematic practices
- An activity to make sure that those most represented in the data have a seat at the decision-making table as stakeholders
- An activity for developing a shared understanding of local racial, social, and historical contexts among stakeholders
- An activity using factor analysis to collaboratively identify causal factors and root causes
- Case studies in using a racial equity lens at various parts of the data life cycle
Are there any resources or tools that you’ve found helpful in thinking about data equity? You can share them with us on our Twitter (@UWMadRschSvcs) or through our contact form!