Presented at the Women in Data Science (WiDS) @ Stanford Earth event: https://earth.stanford.edu/events/women-data-science-stanford-earth#gs.f6efqj
Abstract
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Today’s most critical questions in the geosciences, from climate studies to the management of natural resources, require that we integrate knowledge and methods across domains. With the widespread availability of large-scale computational resources, and the unprecedented quality and quantity of scientific data being collected today, we have opportunities to ask in-depth questions and perform analyses that would have been impossible only years ago. These cross-cutting questions also require that we bridge across technical and social barriers that exist between disciplines. Furthermore, these topics involve a complex spectrum of stakeholders, from individual researchers to policy makers and the general public. The adoption of open-source tools, such as those in the Python ecosystem, is one mechanism for fostering communities and making progress on these challenges.
Within geophysics, I have been a part of one of the teams leading a transition towards open-science practices. In 2013, we started the SimPEG project, an open-source software package that integrates multiple methods (e.g. gravity, magnetics, electromagnetics, fluid flow) into a common framework. SimPEG offers both an architecture that fosters technical interoperability of algorithms, and a community approach that encourages multidisciplinary collaboration. Growing these collaborations to include geologists, hydrologists, geochemists, engineers and others motivates the need for educational resources that provide context for how geophysical techniques fit into the broader goal of answering a question about the subsurface. SimPEG is the research foundation atop which we’ve built the Geosci.xyz, a collection of open educational resources for geosciences. SimPEG and GeoSci.xyz exist within a broad ecosystem of open tools that are now transforming the practices of research, education and scientific communication. We use (and contribute to) Project Jupyter, and we now participate in the Pangeo initiative. Pangeo helps geoscientists explore petabyte-scale datasets and simulations interactively on modern computational environments (from HPC centers to the cloud).
In this talk I will outline my own trajectory in our efforts to develop an open, collaborative, and reproducible model that we think is needed for geoscience to tackle the scientific and social challenges that lie ahead.