A talk from the Cloud parallel session at RSECon2022.

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Abstract: Greenhouse gases are having an ever-greater impact on our world and our society, the open sharing of data and analyses is crucial to better understand the driving factors behind our changing climate.

OpenGHG is a cloud-based platform for performing analyses on greenhouse gas data measurements. The platform has been built with Python and utilises the serverless Fn framework to ensure the platform is cloud agnostic. We’ve worked with the community to build workflows using commonly used tools such as xarray and Dask. Using familiar tools, we hope to encourage participation from the wider community, allowing them to contribute and help grow the project.

Users can interact with the platform using Jupyter Notebooks, this ensures a familiar interface and aids accessibility. The interface enables them to perform analyses and retrieve data from repositories such as the National Oceanic and Atmospheric Administration (NOAA). Data providers can also upload data to OpenGHG. We then make sure it is standardised, versioned and stored with all the associated metadata.

The goal of the project is to make it easier for the Atmospheric Chemistry community to perform open science and to remove obstacles frequently experienced when acquiring data, performing analyses and publishing results.

This talk will try and cover:
• Hurdles encountered building an open, cloud-based, accessible data platform
• Benefits of outreach projects such as a live data dashboard for COP26
• Getting data providers on board with open sharing of data
• Building a community around a project
• Encouraging contributions from new users

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0:00 Talk
16:43 Q&A

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