28.09.2023

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Data Science for Social Good Closing Ceremony

The Data Science for Social Good (DSSG) Practice-Oriented Summer Program 2023 Has Come to an End

In addition, Keynote speaker Professor Leah J. Welty from the Institute for Public Health & Medicine and Northwestern University gave a lecture on the topic “Robust data science: lessons learned from medical applications”.

Even though the project is over for 2023, there will be another DSSG program next year. Or in the words of our PI Professor Frauke Kreuter:

After DSSGx Munich 2023 is before DSSGx Munich 2024. Stay tuned.

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The DSSGx Munich 23 team

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Keynote speaker Professor Leah J. Welty on the topic "Robust data science: lessons learned from medical applications"

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Congrats to the teams by MCML PI Frauke Kreuter

Brief project overview

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Project 1: Land sealing dataset and analysis for better understanding of climate change

The European Commission decided to reduce land sealing to net zero land-take by 2050. Protecting biodiversity and strengthening climate-adaptation affords integrated and climate-oriented planning on state, regional and local levels. Stakeholders have no central platform to analyze land use plans on regional and local level. This leaves them with an unstructured bulk of single documents and impedes democratic negotiation and action on tackling land sealing.

The solution

The project team created a comprehensive dataset about land parcels from the state of Nordrhein-Westfalen in Germany. They provide applications that allow for structured search and analysis of relevant terms. For each land parcel, the dataset supplies important details about their land use planning and land sealing and connects it to the regulations and guidelines on a regional and state level. The deployed tools supply users with the required information for topics like flood risk protection measures or building guidelines.

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Project 2: Fire Hydrant Range-Finder Web Application.

The fire brigade currently lacks a fast, comprehensive and reproducible tool that estimates and visualizes the range of fire extinguishing sources (such as hydrants) on a map. Additionally, natural obstacles such as stairs, rails, buildings, etc. are not taken into account when this range is calculated. However, this is essential for planning, since a representation of the range of water extraction points as the crow flies is insufficient and may lead to misplanning.

The solution

The project team developed and deployed a web application which allows for visualizing the coverage of multiple water extraction points, while taking into account important parameters, such as mode of hose transport, elevation and fire hose length. Additionally, it can be used for sighting of water sources in the vicinity of known or probable fire sites (e.g. chemical plants).

About DSSG

Data Science for Social Good, is an initiative founded by Rayid Ghani at the University of Chicago in 2013. Its mission is to create and sustain programs, solutions and communities that enhance the use of data science and Artificial Intelligence for social good. From the very beginning, the flagship project of DSSG has been its annual fellowship program, now at multiple locations globally.

28.09.2023