Some of our Giving What We Can volunteers and EA NYC worked on a prototype of an interactive table that pulls from GWWC member reported donations, EA Funds grants, EA Funds donations, and Open Philanthropy grants, GiveWell recommendations, ACE recommendations, Founders Pledge recommendations etc.

https://gwwc-data-table-datagrid.herokuapp.com/

It is a very rough draft and the dataset is just a snapshot from a few months ago.

Before any further work is done on this It'd be helpful to know if representing this data within an interface would be useful, if so what those use cases would be, and how you would want to interface with it.

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Interesting project mate. One use case - I am always interested to know what the total 'value' of the community's donation is. Indeed, I ended up doing a  back-of-an-envelope  version of this for a presentation in December, using publicly available donations data. The issue is that everyone reports data over different time periods/in different formats, and there's also a very real risk of double-counting quite a few donations, and so it's tricky to do. 

I'd be interested to keep track of a) total donations influenced by EA; and b) trends in giving over time.

Hey Luke, great work thus far! Props to you and the rest of the GWWC and EA NYC team for making this data available in a user-friendly format.

I know this is a big ask, but I would love to see this data visualized in something like a sankey diagram (broken down by core cause area, sub-case area, and finally individual charity, for example). One of the things I've always been curious about is how under/overfunded a given charity or philanthropic fund is relative to other entities  in the same core or sub- cause area (i.e. donor coordination problem), and I think visualizations like this could provide some really interesting insights to individual donors and fund managers alike.

Alternatively, providing a way to export this data to a CSV or creating an API for accessing the data could enable other people (e.g. me) to develop and share visualizations like the one described above.

Looking forward to seeing where this goes!