Leah leads the Earth Analytics Education Initiative at Earth Lab, which includes a professional program in earth analytics, an undergraduate internship, and an open education website (https://www.earthdatascience.org), which receives over 100,000 unique users per month. Leah’s is building the professional certificate and Master's programs in Earth analytics, developing infrastructure for cutting edge, data-intensive online learning, creating earth data science courses and tutorials, and organizing career development opportunities for students.

Leah developed and now teaches the Earth Analytics course in the Earth Data Analytics - Foundations Professional Certificate program. Leah is an open source, open education and open science advocate. Her most recent project is pyOpenSci - an organization devoted to the development of open source Python tools and resources for scientists.

Leah has a Ph.D. in Ecology and a Master’s in Landscape Architecture. She has nearly 20 years of experience teaching data intensive science. Previously, she was a senior scientist at NEON (National Ecological Observatory Network) where she developed and lead the Data Skills program. She also has a long standing partnership with the Carpentries and led the development of the Geospatial data lessons in R. Prior to NEON, Leah developed curriculum for and taught geospatial techniques including GIS and high accuracy GPS to land planners, faculty, staff and students in the Penn State Geospatial Technology program.

Leah is an outdoor mountain enthusiast and ultra runner. She spends her free time running and fastpacking in the mountains.

 

Our curriculum teaches skills at the intersection of environmental science and data science, combined with a knowledge of heterogeneous data types, open science approaches, and a suite of “soft” skills needed to communicate and collaborate in interdisciplinary teams. These in-demand skills prepare students and professionals for careers in data intensive science that address a variety of large scale environmental challenges.
Building Diverse Community Capacity to Contribute to Peer Reviewed Open Source Software
In alignment with our mission to support open, reproducible science, Earth Lab has developed a number of open source software tools and packages to allow users to help teachers and students use earth data in the classroom. These include abc-classroom, EarthPy, MatPlotCheck, and nbgrader as well as customized JupyterHub and Anaconda/Python environments.
Education should be open and available to anyone. The earthdatascience.org learning portal has over 300 free and open lessons that allow anyone to learn and teach earth data science skills and has tens of thousands of visitors each month.
Earth Lab’s evaluation efforts contribute to the larger field of data science education by identifying best practices surrounding earth data science education in online and in person environments and across diverse demographics.
Our innovative classrooms include an interdisciplinary mix of undergraduate, graduate, and returning professional students who participate in active, collaborative synchronous and asynchronous learning through options for in-person or online courses. This variety in available participation modes supports students by addressing geographic and time constraints that might otherwise limit their access to formal education in earth data science.