Equity in Data Community of Practice

CT Data Collaborative

Who is the Equity in Data Community of Practice?

We are a group of data users in Connecticut (mostly) who are supporting one another as we work toward integrating more equitable data practices. We focus on racial equity explicitly but not exclusively. Our group is a project of the Connecticut Data Collaborative.

Members of our group serve in many kinds of roles related to data, including data analysts, evaluators, or researchers, to data coordinators and GIS analysts, to program managers, case managers, and administrative staff.

Our common thread is that we are each involved in data in some capacity, and we each know the importance of integrating equitable practices into that work.

If you are unsure whether your background or skill set would make sense in the group, please feel free to email Sarah Eisele-Dyrli, Data Engagement Specialist at the Connecticut Data Collaborative.

Why did we form?

At CTData, we have been looking for ways to support a data community of practice. We started this group as an informal lunch discussion in order to understand the interest in this topic of equity and ethics in data. There was a great deal of interest, and so we decided to move forward in developing a community of practice.

What is a community of practice? The term is a modern description of an old idea. Etienne and Beverly Wenger-Traynor, the leading researchers of the concept, define it as "a group of people who share a concern or a passion for something they do, and learn how to do it better as they interact regularly."

Our goal is to become a group that can contribute to a more equitable data culture in Connecticut (or wherever else our members may be located).

While our culture views data as cold and factual, those of us who work in data know that human decision-making is involved in every step of the data process. That means our own perspectives, ideas, and biases inevitably influence the process. In the areas where we don't recognize these blinders we or our institution has, then we will inadvertently, unintentionally cause more harm than good with our data work. We are working together to remove these blinders and identify ways to proactively integrate equitable data practices into our data work.

In 2021, we will strengthen relationships in the Equity in Data Community of Practice so we can be a supportive community to one another, and will create and formalize knowledge that will improve our equitable data practice.

When do we meet?

We currently meet on the third Tuesday of each month from 11:30am - 1:00pm ET via Zoom. We do require a simple registration, which you can find on our Schedule page.

What do we do?

Beginning in June 2020, our group started meeting almost monthly to talk about how we could improve our equity in data practice. Our primary mode of connection right now is these discussions, but we hope that in 2021 we will find ideas on which to collaborate and develop knowledge that can benefit ourselves and data users in Connecticut.

Format: Our monthly sessions are interactive, and everyone contributes to the discussion in some way (sometimes via the chat box). We break into small groups if the topic and size of the group allow it. We focus our discussion on an article, or we have guests come to speak about a topic that is relevant to us.

Time Commitment: Members of the group spend about 2 hours each month on group-related activities, which include the 90 minute meeting and less then 30 minutes of reading or thinking about a question before-hand.

Topics: As of February 2021, we are beginning to invite experts in specific topics that we want to learn about. Some of the topics we have talked about include:

  • How can we make sure we don't make certain groups invisible through how we disaggregate our data?

  • How can we learn to focus our attention on the strengths, rather than the deficits, of groups we are seeking to serve or support?

  • How can we learn from the people who we hope will benefit from our products or services about what their data means to them?

  • How can we help the institutions that we are part of to be trustworthy so that people will trust us with their information/data?