👑 [exercise] - Google Data Commons POC

[MichaelTiemannOSC]

Google Data Commons POC

• Module:

📝 Description

The Google Data Commons (https://datacommons.org/) has over 1 trillion datapoints of all kinds, organized in a knowledge graph and available via BigQuery. Some of this data is directly useful to climate and sustainable finance analysis, and some of this data could be useful when linked to corporate ownership (via entity matching).

Here are datasets federated by Google's Data Commons that relate to the topic Environment: https://docs.datacommons.org/datasets/Environment.html

Here is a narrowing of that data that relate to the topic Emissions within the US (based on EPA GHGRP): https://datacommons.org/tools/map#%26sv%3DAnnual_Emissions_CarbonDioxide_NonBiogenic%26pc%3D0%26denom%3DCount_Person%26pd%3Dcountry%2FUSA%26ept%3DState%26ppt%3DEpaReportingFacility

The goal of this exercise is to demonstrate our ability to federate a tiny but meaningful slice of Google's Data Commons data into the Data Mesh and to expose that data within OS-Climate's Data Exchange. The data should be chosen so that a meaningful "so what?" question can be answered, but the overall point of the exercise is to assess the ease with which the Data Mesh can enable data analysts to be maximally productive and effective in when asking and answering climate and sustainable finance questions.

🥤 Additional Info

Please feel free to flesh out and/or ask further questions.

✅ A/Cs

• Big Picture Updated (if applicable)
• Facilitator notes updated (if applicable)
• Exercise peer reviewed / tested with one other region member
• Addition of new exercise does not affect previous exercise (maintain modularity)

[MichaelTiemannOSC]

@caldeirav What else do I need to do to be able to assign this to the Data Mesh Pattern Backlog project? No projects are showing up for me.