The data is not about the data
This is a creative and exploratory space that examines how culture unfolds and informs the numbers we see.
In November 2023 I was invited to present to a select audience on how institutions of higher education could re-think their relationship with data. The guidance I was given touched upon two points. First, help get everyone to think more deeply about data and why we collect it — the purpose it serves, the problems it identifies and hopefully helps solve. Second, help bring the collective insights of the social sciences to the discussion so that we, as a group, can reflect upon and explore questions of meaning, culture, and the ways data often takes a life of its own (through storytelling, for example). “I want everyone to think about the big picture,” I was told. As I prepared I quickly realized that the presentation was not about anything technical or textbook in nature. Rather, it was really about all the fundamental things I wish I knew when I began the journey of becoming a social scientist. If I could rewind the clock and go back in time, what advice would I give my younger self? How should I think about data and the deeply interconnected and invisible relationships it invokes?
The title, The Data Is Not About The Data, pays homage to the French surrealist painter, René Magritte. One of Magritte’s major insights - which are shared in many fields in the social sciences - is that we have to question the relationship between what we see and what is actually there (Ceci n'est pas une pipe). In addition to understanding the world through numbers, whether they be through economics or statistics, p-values or r-squares, there are innumerable tensions and contradictions of culture, meaning, and context that must be navigated. Data, from this perspective, is both an interlocutor and language for describing reality, a phenomenon that can be glimpsed indirectly but never seen in its entirety.
I am creating this space because most conceptions of (quantitative and qualitative) data do not fully account for the dynamics and conditions that must be in place for data to exist. Data does not happen in a vacuum.
This is written for a general audience in a language that is meant to be accessible to everyone.
