# References

## Papers
- [Ueckermann, M., Bieszczad, J., Entekhabi, D., Shapiro, M. L., Callender, D., Sullivan, D. and Milloy, J., "PODPAC: Open-Source Python Software for Enabling Harmonized, Plug-and-Play Processing of Disparate Earth Observation Data Sets and Seamless Transition Onto the Serverless Cloud by Earth Scientists," Earth Science Informatics, Vol. 13, No. 3, 2020, pp. 1507–1521.](https://dspace.mit.edu/handle/1721.1/131933)

## Presentations
- Scipy 2020: [Geospatial Analysis in the Cloud Using PODPAC and JupyterLab](https://www.youtube.com/watch?v=BXI6w9BECgs&t=959s)
- AMS 2020: [PODPAC: The Easy Way to Analyze Earth Science Data in the Cloud](https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/365046)
- AGU 2019: [Building Web Browser Apps for On-Demand Retrieval and Processing of Cloud-Optimized Earth Science Data using the Open-Source WebESD Toolkit](https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/505588)
- AMS 2018: [A RESTful API for Python-Based Server-Side Analysis of High-Resolution Soil Moisture Downscaling Data](https://ams.confex.com/ams/98Annual/webprogram/Paper332957.html)
- AGU 2018: [Use of the Open Source PODPAC Library for Remote, Cloud-Based Data Analysis, Visualization, and Collaboration in a Web Browser](https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/381197)
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## Posters
- AMS 2023: Open Source Serverless Architecture for Sharing Earth Science Data
- AGU 2021: [General Server for Rapid Publishing of OGC-Compliant Earth Science Data Products](https://agu.confex.com/agu/fm21/meetingapp.cgi/Paper/951494)
- AMS 2020: [PODPAC: The Easy Way to Analyze Earth Science Data in the Cloud](https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/365046)
- AMS 2019: [PODPAC: A Python Library for Automatic Geospatial Data Harmonization and Seamless Transition to Cloud-Based Processing](https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/352145)
- AGU 2018: [Seamless Transition of Data Analyses and Analytics from a Local Workstation to Scalable, Massively Distributed Processing on the Cloud Using the Open Source PODPAC Library](https://www.essoar.org/doi/abs/10.1002/essoar.10500684.1)