Inspiration
Each year every nation diligently submits their Emissions and Climate report files to the United Nations Climate Change Convention, encompassing crucial information pertaining to their respective approaches in addressing emissions and striving towards emission reduction targets. However, the realm of climate data is known for its intricacies, and the process of data engineering can be financially demanding. One significant challenge faced by the United Nations Climate Change Convention is the absence of a universal standard for submitting these crucial reports.
What it does
This lack of uniformity poses difficulties in accurately interpreting the data and holding nations accountable for their commitments.formatting Therefore, the integration of artificial intelligence (AI) holds the promise of automating the ingestion of such data on a global scale, streamlining operations and enhancing efficiency.
How we built it
We used Open AI for categorizing data, generating python script that will convert the CSV file into a standardized format and automatically fix any errors the python encounters.
Challenges we ran into
Data is in various formats that can be easily transformed. For example it can be pivoted.
Accomplishments that we're proud of
We were able to work with various different input data and standradize it with automatic generation of code.
What we learned
That a human in the loop is still important to see if the data fits into the bigger picture.
What's next for Open Climate Foundation Data Harmonization
Built With
- openai
- python
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