Data can elevate, empower, and uplift, but it can also erase, disempower, and harm when used in ways that are not inclusive and thoughtful. However, before having conversations about how we use data, it is important to consider the way our data is even structured: Who set up those structures? What were their biases? Data is fundamentally about and constructed by people, even though it may be abstracted on many levels from those who contributed their information (whether voluntarily or involuntarily) and those who shaped it. Oppression often centers itself in and shapes our data and data structures, perpetuating further marginalization and erasure of minoritized groups. As an example, Abigail Echo-Hawk states that “[o]ne of the ways that there is a continuing genocide against American Indians/Alaska Natives is through data. When we are invisible in the data, we no longer exist” (1). A related example is the flattening of identities based on single-select or binary structures for capturing demographic information. What are the consequences of our decisions on how we structure data and how we combine different groups of users to provide anonymity or significance? Who do we exclude when we make decisions based on the largest number of people or dominant groups? What are the impacts? This presentation would build on critical approaches to data that are already being discussed in libraries and related fields in order to ask questions about how data is (or is not) being critically examined in these spaces. It would ask those who work with data to implement critical perspectives to interrogate not just how we use data, but how we structure it in the first place. 1. Secaira, M. (2019), “Abigail Echo-Hawk on the art and science of “decolonizing data,” Crosscut, available at: https://crosscut.com/2019/05/abigail-echo-hawk-art-and-science-decolonizing-data<https://crosscut.com/2019/05/abigail-echo-hawk-art-and-science-decolonizing-data>