Inspiration
We wanted to make space economy data exciting and approachable. Traditional economic forecasts can feel dry, so we asked: What if the battle for resources, funding, and talent across space industries was framed like the Hunger Games? This narrative transforms abstract data into a vivid, competitive arena where “districts” rise, form alliances, or get eliminated.
What it does
The Space Economy Hunger Games analyzes and forecasts trends across space-related industries by treating each sector as a “district.” It identifies which sectors are winning or losing in terms of employment, funding, and GDP share. It also tailors insights for both risk-averse investors (stable districts) and risk-takers (volatile but high-reward sectors).
How we built it
We mainly used R and RShiny to build the website, along with HTML for aesthetics. For visualizations, we used Python and R. For data manipulation and selecting, we used Excel
Challenges we ran into
One of our challenges was figuring out how to categorize the districts. At first, we considered using PCA to create a hierarchy of districts made up of similarly behaving industries, but this approach proved overly complicated for the data. We ultimately decided to categorize the districts according to the largest industry categories, which already group together similar smaller industries.
Accomplishments that we're proud of
As a team, we are very proud of how the website turned out. The aesthetics and layout of the website is both appealing to the eyes and easy to understand.
What we learned
Working on this project, we learned how important it is to balance ambition with practicality and efficiency. Through trial and error, like our effort to implement PCA to create a district hierarchy, we found more success by taking a more streamlined approach based on the established industry categories in our dataset. Developing our interactive Hunger Games website taught us how to transform raw data into engaging, useful visualizations that allow users to compare industries across multiple metrics. Most of all, we learned how important it is to stay focused and grounded in our group's vision when working on collaborative projects.
What's next for The Space Economy Hunger Games
Building upon our current analysis, next steps are to expand the dataset to include international space industries, incorporate additional economic metrics, and improve the predictive potential of our analysis by implementing machine learning techniques. Additionally, expanding the interactive nature of our UI by adding custom scenario explorations will provide investors with the tools to see how industries react to economic recessions, scientific breakthroughs in real time.
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