Increasing accessibility of data (e.g. satellite data) & cloud technologies to a broad scientific community through easy-to-follow Python tutorials
Marisol is developing an online tutorial with comprehensive examples, that teaches how to easily access data increasingly available in the cloud (e.g. earth sciences satellite data), and analyze and visualize the data using cloud computing resources. The tutorial provides foundations in Python programming and reproducible research using Jupyter Notebooks, Git, software citations, and cloud computing. Even with recent advances in technology and accessibility, the gap between students and scientists who can use these data keeps growing, as it requires expertise in computer sciences or to overcome a steep learning curve. This tutorial aims to lower the barrier to entry and broaden the community of scientists and students that have access to and can use satellite data and cloud computing resources. The tutorial is designed for those whose expertise is not satellite imagery or those that lack the necessary programming proficiency to use these data.
Marisol is a Principal Scientist at the Farallon Institute, a nonprofit scientific organization dedicated to the understanding and preservation of healthy marine ecosystems. Marisol has a background in physics and atmospheric sciences, but she's an oceanographer at heart. Her research focuses on the relationships between ocean conditions and marine ecosystems, and how they are impacted by climate. Marisol is committed to increasing equity and diversity in science and education by improving access to computational technology and increasing broadening participation. She is interested in providing and improving code that scientists in other fields (and other users) with limited coding skills, experience, or even time, can use to access and analyze satellite data, like climate and ocean data, to improve their research or knowledge.
Selected resources
Tutorial: Timeseries of Satellite Data using Python HPC Best Practices Webinar: Acquisition and Analysis of Times Series of Satellite Data in the Cloud – Lessons from the Field Navigating the Transition of (Climate) Science to the Cloud
