As we celebrate Black History Month, it’s a critical time to engage in actively anti-racist and social justice-focused work. However, it’s not enough to celebrate and focus on this work during one month every year. Working anti-racism, ethics, equity, and care into our work is necessary to ensure a better future for everyone.
Part of our responsibilities as researchers, as research support, and as collectors and users of data is to engage deeply with the protocols, methods, and data structures that we design or use for our research. As humans we come to our daily work with implicit biases that are encoded in our research designs and data structures, and as members of a large research institution we come to research with inherently more structural power than those who may be participating in or impacted by our studies. Working to improve our ability to spot these issues when they happen and to adopt practices that help counteract them is critical in making research more ethical.
Throughout this series, we will be posting blogs that dive into important research data equity topics. These posts will serve as primers on the topic, introducing considerations and resources for being more aware, thoughtful, and inclusive in the ways we work with research data. You can find a list of the topics in our series below:
- CARE Principles for Indigenous Data Governance
- Tools for Data Equity Part 1: Acknowledging Your Worldview
- Tools for Data Equity Part 2: Community-Based Approaches
- The Impact of Data Invisibility and the Need for Disaggregation
Be sure to share any great resources, readings, or tools that relate to any of these topics on our Twitter, @UWMadRschSvcs or send them through the contact form and we’ll share them in future digests!