Many advocates for better science communication argue that transparency in science is necessary for the public to contribute to informed decisions about scientific issues, yet transparency is not straightforward (Kahan 2010, Priest 2013, Fischhoff 2019). Particularly when communicating research results, scientists are commonly taught that data should be presented without interpretation and that the meaning of data is self-evident (Nisbet and Scheufele 2009, Wolfe, 2009). Increasingly, and perhaps ironically, evidence indicates this approach is unrealistic (Kahan 2010, Davies et al. 2019, Iyengar and Massey 2019). Even as we communicate within our own scientific communities, we are constantly shaping and instilling meaning, intentionally or not. Furthermore, our audiences do the same. Renowned environmental writer Barry Lopez articulated this reality over two decades ago: The kernel of indisputable information is a dot in space; interpretations grow out of the desire to make this point a line, to give it direction. The directions in which it can be sent, the uses to which it can be put by a culturally, professionally, and geographically diverse society are almost without limit (Lopez 1986, p.190).