Inspiration
We were inspired by the devastating impact of natural disasters and wanted to create a tool that helps visualize their history and assess future risk.
What it does
Data Doomsday visualizes global disasters from 1900–2023 and maps current risk levels using the INFORM Index. It lets users explore patterns in disasters, casualties, and economic damage.
How we built it
We used Python. Data sources include EM-DAT and INFORM Risk Index.
Challenges we ran into
Merging datasets with inconsistent formats and building a clear, intuitive UI for complex data were major challenges.
Accomplishments that we're proud of
We created a functional, informative tool that combines historical and predictive disaster data with interactive visualizations.
What we learned
We learned about integrating large datasets, the importance of data storytelling, and how to present complex information in a user-friendly way.
What's next for Data Doomsday_Datanauts
We plan to add real-time disaster data, country-specific insights, and AI-based prediction features, and open it up for broader use.
Log in or sign up for Devpost to join the conversation.