The Science of Data, Data Science: Perversions and Possibilities in the Anthropocene Through a Spatial Justice Lens

• In Event: De-signing Science Education in the Anthropocene

Abstract

Statistics, often dubbed the science of data (Davidian & Louis, 2012); and data science, the supposed new revolutionary frontier tasked with breaking the bonds of statistics, both have epistemological roots in exploring data. In the Anthropocene statistics, data science and mathematical models have become a perversion of reality that society has largely chosen to ignore and is embraced as a great savior because people often view numbers as objective purveyors of truth. However, numbers do not interpret themselves, they do not tell their own story; people do. In this theoretical paper, I began my discussion by making connections between the Anthropocene, in particular the Orbis Spike dating of its beginning and the human events of that time (Lewis & Maslin, 2015), to statistics and data science specifically through the context of spatial data. From this discussion, there are two main points I elaborate on and then connect to education. The first is that there is a dialectic tension involved in spatial data enquiry between creating new realities using spatial data and using spatial data to make sense of our reality. The second point is that people can choose how to investigate and use spatial data based on their ethics. I believe students should have opportunities to investigate and use spatial statistics both to learn about the world around them and to shape the world around them and that they should learn to do so through considering counter mapping and spatial justice.

To show my points in an educational example I discuss the example of Charlotte. Charlotte has a history of redlining, particularly after the Civil War. In an attempt to make the city more equitable in the future, the city has undertaken an initiative they refer to as Charlotte 2040, where they are seeking to create a more equitable city by the year 2040. Spatial representations help to show how strongly the practice of redlining influenced where people of different races were able to live in the city. Spatial depictions of housing and race data are a part of the Charlotte 2040’s interactive slide show to show the issue of housing inequity in Charlotte and is publically available for people to use. This could serve as a starting point for bringing the notion of spatial injustice and data into a class. This topic has potential for cross-disciplinary connections to science when you begin considering environmental factors. For example, in the areas where there is a greater density of Black residents there are also a higher levels of environmental exposure risk particularly near the airport. There are also possibilities for citizen science in this context looking at water quality, measuring soil samples, temperature, air quality or other environmental factors geotagging the data collected to then create spatial representations of the data. Investigations of spatial statistics hold promise for bringing important issues of spatial justice into the classroom and for interrogating both the world we live in and the world statistics creates for us.

Author

• Travis Weiland, University of Houston