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.
Through May, we will be posting one blog post each month that dives into a research data equity topic. 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.
To kick off the series, this month’s post will be focused on the CARE Principles for Indigenous Data Governance. Be sure to keep an eye on the RDS blog later this month for this post and future ones! Over the next four months you can look forward to the following topics:
- How to advance social justice and data equity, particularly in the local scope
- Tools and resources for evaluating data equity in your work
- Data disaggregation
- Bias in algorithm training sets
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!