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Hackathon Challenge 1: Urban Innovation with Open Data


Introduction

Welcome to an engaging hackathon journey where your creativity and data science capabilities unite for the greater good! In collaboration with Technologiestiftung/ CityLab Berlin, we present a challenge that dives into the diverse and rich datasets capturing the essence of urban life in Berlin. The goal is to harness these datasets to improve various aspects of urban living, with a special emphasis on environmental sustainability, public safety, and enhancing the quality of life for all Berliners.

Challenge Overview

Your task is to leverage data science methods in uncovering insights and developing solutions that address the multifaceted challenges of urban living. While you have access to detailed datasets on accidents, air quality, and cycling infrastructure, we encourage you to think broadly. Your challenge is to design, explore, and prototype solutions that help make Berlin a safer, greener, and more livable city for everyone.

Data Sources

  • Accidents in Berlin (2021): Detailed records of road accidents, including geolocation data.
  • Air Pollution Data (2021): Air quality measurements from official monitoring stations throughout Berlin.
  • Urban Infrastructure Data: Data on existing cycling routes throughout the city, offering insights into Berlin's cycling infrastructure.

Note

If you are interested in the whole data generation and cleaning process, have a look at this notebook. In general, more detailed information about the dataset, sources, and documentation can be found in the Hacker's Manual.

Deliverables

  • A Jupyter Notebook containing your analysis, visualizations, and any models or algorithms developed.
  • A Presentation summarizing your findings, your proposed solution(s), and their potential impact. Highlight the creativity and data-driven approach behind your project.

Evaluation Criteria

  • Creativity and Innovation: Originality of your solution and approach to problem-solving.
  • Effective Use of Data: How well you integrate and analyze the provided datasets to support your solution.
  • Potential Impact: The feasibility and potential benefits of your solution for Berlin's government or its citizens.
  • Clarity and Persuasiveness: How effectively you communicate your ideas and findings in both the notebook and presentation.

Resources

While the challenge is centered around the provided datasets, you are encouraged to enhance your solutions with additional data and resources. The quality of your analysis and the innovation of your solutions will be key to your success.

Getting Started

A Jupyter Notebook template is available to help initiate your project. It includes preliminary steps for data loading and exploration, alongside tips for data cleaning, analysis, and visualization.

Ideas

  • Accident Hotspot Analysis: Identify and analyze areas with high accident rates, proposing infrastructure or policy changes to reduce risks.
  • Safest and Healthiest Cycling Routes: Determine routes that minimize safety risks and exposure to pollution, creating a healthier cycling environment.
  • Interactive Cycling Map: Develop an interactive map or app that guides cyclists based on their preferences for safety, air quality, or scenery.
  • Community Engagement Solutions: Create a platform/dashboard for cyclists to report issues, share experiences, or collaborate on improving cycling conditions.
  • Data-Driven Policy Recommendations: Use insights derived from the datasets to inform policy changes or city planning initiatives.

Good luck, and we're excited to see your innovative ideas! Happy Hacking!

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Data4Good Festival | Hertie School

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