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We’re building a graph of this same underlying data at https://alma.app (with a lot of enrichments) to help people discover and donate to nonprofits.

E.g. here’s Stanford: https://alma.app/charities/941156365-the-board-of-trustees-o...

Would love to know what types of analysis people would like to see about organizations and their relationships?



> Would love to know what types of analysis people would like to see about organizations and their relationships?

Related public records, e.g. court filings, municipal or other co-investments alongside the nonprofits, adjacent (time or geo) legislation/policy changes, rotating doors of nonprofit, gov, commercial.


Interesting thanks!


This is neat! I thought about extracting the grants (still might), but full-text seemed like good bang for the buck. Your tools sound like they might be very useful for reporters. Have you given any thought to that? We love mapping these sorts of connections.


Hey, first up really amazing work you’re doing, hugely inspiring for us! Thank you.

Whilst our focus has been delivering a consumer layer on top of all this data, yea, very open to exposing our underlying graph to others. Want to drop me a note at dan at alma.app?

As you mention elsewhere, half the battle is cleaning the data and getting quality.


Could you clarify what you mean by “building a graph”? Are you combining the 990 data plus other enrichments in a graph database?


Yep basically - looking at the network of grants (who funds who), people (who works where over their careers), social media and news (who’s referenced or cited alongside whom) and so on. You start to see interesting clusters of nonprofits that are funded by the same groups and work together extensively.


Neat. What technologies are you using to store and analyze the data? Are you using any graph algorithms, like PageRank, community detection, etc?


DGraph and elasticsearch with some redis caching.

Yea, a version of pagerank is coming soon! Love any other ideas...




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