Github Repository for the COP27 Datathon

Introduction

The GST Climate Datathon is a call for open data and tools to support the GST ahead of COP27. Outcomes should be aimed toward making data sets interoperable, providing aggregated insights, support tools, and visualizations. Three winners from each category will have the opportunity to present their findings at the COP27 Presidency’s ‘Science and Information Day’.

There are three thematic areas of the global stocktake: mitigation, adaptation, and means of implementation and support (including finance, and loss and damage). Information is being prepared for the global stocktake between now and June 2023, with technical dialogues also ongoing until June 2023. At COP28 in 2023 the outputs of the global stocktake will be considered and are expected to inform parties in updating their commitments toward the Paris Agreement.

We ask the hackers to embark on an unusual task — help us collectively build the web that expands upon and ties different datasets together. Hackers are to examine publicly available data sets, determine their data taxonomies, make recommendations for improvements, develop tools for interoperability, fill in data gaps with modeling, record metadata, establish clear data provenance for databases, use projection analysis to determine collective action.

Logistics

Timeline

September 21st @ 9:00-9:30 AM ET | Launch Datathon @ NY Climate Week
October 15th | Submissions closed
October 15th-20th | Submissions reviewed
October 21st | Winners identified and announced
November 10th @ COP27 | Winners will present on Science Day

Judging Criteria

Submissions will be evaluated based on their quality, clarity, credibility, and potential impact across these dimensions:

Help data sets talk to one another for aggregated insights to enable insights on collective progress
Develop new insights and analyses about our collective progress toward the Paris Agreement
Help to visualize our collective progress toward the Paris Agreements
Data storytelling and narration
Other data innovation

Submission process

All submissions should be made via the GitHub repository. Included with all submissions should be a visual presentation that describes your work. Some examples of the form this visual presentation can take is: a slide deck, video, written description, or website. To submit your project, please

Fork a copy of the datathon repository
Navigate to the folder of the prompt you wish to provide a submission for
Create a subfolder under the Submissions/<Prompt Theme>/<Prompt folder> with the format “TeamName_PromptTitle”
Include/Embed relevant documentation and/or presentations in the README file
Include any relevant code snippets and/or datasets
Submit a pull request to the repository

If you have significant amounts of code (for e.g., if you have built a web tool/app) or if you have created a GitHub page for your submission, you can also make use of GitHub’s Submodule system to include a submodule to your own GitHub repository within your submission.

Communications

Discord

Join the datathon Discord channel here!

Team-matching

If you are participating in the datathon individually, check out the Discord Team Matching channel to find your dream team!

Resources

Compiled Datasets

** Crowd-sourced and compiled datasets** Crowd-sourced datasets via our google form are available on this Google Drive folder

DDL-OEF-CAD 2.0 Data model

The DDL-OEF-CAD 2.0 Data model is an attempt led by DDL and OEF (and supported by the CAD 2.0 community) to create a data model that would allow climate data from disparate sources to be harmonized for use in a Digitally-enabled Independent Global Stocktake.

Participants are encouraged to transform their data into the format of the data model (accessible here when submitting any datasets, and to leave any comments they have on the data model as an issue within the same GitHub Repository linked above.