About the challenge

The DawsonAI Data Challenge, in collaboration with AI Launch Lab, introduces participants to the dynamic field of Data Journalism, where complex datasets from various domains are transformed into compelling visual stories. These stories aim to enlighten the public, driving awareness and action on critical issues. This year participants will draw inspiration from the United Nations Sustainable Development Goals (SDGs). 

The 2030 Agenda for Sustainable Development lays out a blueprint aimed at fostering global peace and prosperity. Central to this agenda are the 17 SDGs challenging all nations to contribute to strategic advancements in health, education, and economic growth, alongside concerted efforts to address climate change and the preservation of natural resources. Participants will be tasked with creating visualizations and narratives that not only present real data in an accessible and engaging manner but also highlight the significance of one or more SDGs.  Whether you are inspired by climate action (SDG 13), quality education (SDG 4), gender equality (SDG 5), or affordable and clean energy (SDG 7) teams will be challenged to communicate data-driven insights that will contribute to a deeper understanding of these global objectives.

Get started

The overall goal of the challenge is to develop a data-driven story drawing inspiration from the 17 SDGs

 Instructions for Saturday workshop

  • Note tips from the Data Storytelling presentation [slides uploaded on discord].
  • Open a new jupyter notebook Google Colab (requires a Gmail account) to follow the Data Visualization presentation: Introduction to Data Visualization in Python [link on discord]. 
  • Select one or more preferred SDGs from the form provided. We want to ensure an array of SDGs are covered in the challenge. 
  • Explore the use of LLMs like ChatGPT for brainstorming and coding: Google Colab Setup and Code Generation Guide [see tutorial recording and colab notebook with tips linked on discord].
  • Teams will be provided support in selecting appropriate data sets by mentors during the challenge. For example, see this Our World in Data article, which gives the CO2 emissions over time, for any country, over the last 50 years.

See discord #challenge-resources for the tutorial recording and other resources.

 

Requirements

The overall goal of the challenge is to develop a story with your data. Take inspiration from the analysis and examples from the Warm-up tutorial.

What to submit

  • Data visual(s): At least one representative visualization of your data should be submitted. Feel free to include more, provided they add value and clarity to your narrative.
  • 200-word “news story”: Articulate your findings in a concise article, effectively communicating the significance of your data-driven insights.
  • Code: Share the code from your analysis in a Colab Notebook, ensuring transparency and reproducibility of your work. (submitted as link)
  • 5-minute presentation:  Prepare a brief yet impactful presentation to convey your findings and narrative to the judges. Provide presentation slides (link or uploaded file to discord).
  • LLM chat log: Submit a log (as a shared link) or document of your interactions with ChatGPT, along with a short summary reflection explaining how you used it to enhance your project. Some things to consider: Did you use ChatGPT for brainstorming? Was the code assistance helpful and accurate? 

Submission Tips

  • Try to use data-driven arguments
  • Be inspired by your data source (e.g., Our World in Data)
  • Explore the use of:
    §  Graphs
    §  Infographics
    §  Animations
    §  Video

All teams will make 5 minute presentations to the group of judges. Be sure to review the judging criteria!

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Prizes

$CAD 750 in prizes
Data Journalism Award
1 winner

Grand prize awarded to the best overall submission.

Honorable mention: Technical Award
1 winner

For the best technical implementation of the data visualization.

Honourable mention: Visualization Award
1 winner

For the most creative and/or aesthetically interesting data visualization.

Honourable mention: Communication Award
1 winner

For the most engaging story overall.

People's Choice Award
1 winner

Voted for by the community.

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

Judge

Judge
Dawson College

Judging Criteria

  • Technical Implementation
    How did you produce your visual(s)? Did teams rise to the technical challenge of manipulating data? Something innovative about the analysis? Is it remarkable that teams could hack this analysis together in just a day or two?
  • Aesthetic
    How "beautiful" or aesthetically interesting is your data visualization? Are visualizations beautiful/elegant/polished while coherently capturing the essentials of the story? Something unique about the visual? Creative? Crisp and clean?
  • Communication
    The overall story. How effective/engaging/coherent is the story overall? How well did the team present? Is the communication of the data analysis and accompanying visuals + methods used clear and understandable?

Questions? Email the hackathon manager

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