Data journalism has an important role in redefining data as non-neutral, and therefore assumes a huge responsibility to the public. Nikki Stevens discusses the lack of “neutrality” inherent to data in their article “Data Set Failures and Intersectional Data” – even in cases where data is collected for more ethical and intersectional goals. Stevens asks us to consider if data can itself be intersectional – to which I say that data as it interacts with other data can perhaps be intersectional, but likely not on its own. In “Moving Targets: Collecting Queer Data,” Kevin Guyan raises some critical questions related to the data collection process in writing about the necessary contextual framing and interpretation of data with regards to space, time, other participants, and researchers.  In their piece, Guyan asks: “in moments when data is captured, whose interests are prioritized? The interests of individuals or groups about whom the data relates (in other words LGBTQ people) or the interests of those who possess the power and resources to collect the data?” I believe that more times than not, data is captured and shaped by the interests of those who possess the power and resources to collect the data.  The mere act of collecting the data leads many to assume that therefore the interests of the groups about whom the data relates to is reflected in the data, even if that may not be the case… which can have dangerous implications in attempts to relay an “objective truth” that is at the same time being constructed and self-validated. There is no denying that data is always situated in the context of the collector. The “queering” of collection methods in data journalism involves redefining the relationship between researcher and participant, through communal and consensual processes of building knowledge in non-hierarchical ways. It also asks for more fluidity in the “moving targets” of identity, reinforcing the dynamic nature of who we are and how we change as humans throughout our life. Above all, data journalism has a responsibility in taking time to think and share about how journalistic intent shapes the data collected. It’s crucial to be honest about positionalities when presenting a data journalism project, and to consider the context in which participants may view themselves in relation to others in the act of attempting to codify one’s own identity. Given the ability of data to not only shape our reality but also present itself as “natural”, there is immense responsibility to the public needed for accountability when we realize failures in data collection practices. Steven’s article is an example of what this accountability can look like. “One Size Fits Man” by Caroline Criado-Perez exemplifies the wide-ranging consequences of misogyny and patriarchy as it relates to women’s experiences with technology that was simply not built for them. The power dynamics of domination are reinforced in datasets that center men more than women, and misrepresent women in the representation that does exist. Sometimes, the existence of data at all creates attitudes that disregard the very real critiques made in hopes of data collection that enables building technology for all people,as shown in the example given by Criado-Perez about Tom Schalk’s offensive and lazy response to reports of faulty voice technology in car navigation systems. A nuanced approach in data journalism is essential to reinforcing the importance of intersectional voices.