Our inspiration for the research project came from the book, Data Feminism, which was recently released by the Data Feminism Lab at MIT.
What it does
Our research projects provide feminist context for the data sets Health Behavior in School Aged Children (HBSC, hbsc.org) and Youth Behavior & Health Survey. We used data visualization and other visual comparisons to show particular areas of interest in the data set and reenvision what is missing or biased in the data to better address issues of power and inequity.
How we built it
We built our data visualization for the Youth Behavior & Health Survey using the visualization tools in Google Sheets, and provided context using the feminist tools we learned from Data Feminism.
For the HBSC Survey, via qualitative research and exploratory data visualization in Tableau and online map tools, we examine the context of HBSC data through the principles of Data Feminism, highlighting examining power, rethinking binaries, and challenging power. Find more about this analysis here.
Challenges we ran into
Some of our challenges included managing everything under time constraints, coordinating so many people on such a big project, and figuring out how to properly use the data visualization tools. With such large datasets, distilling it down to core components was difficult, but we focused on issues we were passionate about (mental health).
Accomplishments that we're proud of
We are proud of accomplishing so much in just 24 hours. We are also proud of all that we learned about contextualizing data, creating meaningful data visualizations, and technical research over the course of the hackathon. We tackled 200,000+ size datasets, investigated the shortcomings of data processes conducted by national and multinational institutions, and have a better framework of critical thinking to tackle human issues, that do extend beyond the data.
What we learned
We learned a lot about technical research and data science through the research track. We learned a little about data visualization and how to contextualize data sets through a feminist lens.
What's next for data Feminism
In the future, when analyzing or interacting with data, we will continue to use the data feminist lens to question who the data is serving, why it is being collected, and to ask other essential questions when dealing with data.
As prospective researchers and data scientists, we hope to carry these Data Feminist tools when we engage in any data analyses, presentations and visualizations in the future and realize the inherently biased context in which they exist: and strive to make each process of collecting, analyzing, and presenting the data that is inclusive of all perspectives.