Brian Rose
University at Albany, NY·Earth & Environmental Science
Modern geoscience runs on huge public datasets: climate model output, ocean measurements, satellite records. Turning that raw data into a scientific result often takes specialized coding skills and computing resources that many researchers and students lack.
- Fields
Earth & Environmental Science
Computer Science
Education Research
- Topics
Project Pythia
Pangeo
Python
- Grants
- 1 known grant, through Dec 2027
What they work on
- Develop science-driven example Cookbooks, collections of runnable Jupyter notebook recipes, that show scalable cloud versions of common analyses on high-value geoscience datasets.
- Cover Cookbook content across atmospheric science, physical oceanography, hydrology, glaciology, climate science and machine learning, chosen to raise community awareness and participation.
- Deploy infrastructure for writing, testing and running Cookbooks close to the data on commercial and NSF-funded cloud platforms, with automated health checks that fight notebook obsolescence.
- Grow the community of Cookbook users, contributors and maintainers through annual workshops, outreach and classroom use, with recruitment aimed at under-served communities.
More about the research
Analysis code shared as notebooks also tends to stop working as software changes. This project aims to lower those barriers by building shared, reusable examples of how to analyze geoscience data in the cloud.
Why it matters
Many geoscientists, especially students and those at less-resourced institutions, struggle to analyze large climate, ocean and ice datasets. Open, cloud-based Cookbooks that keep working could let more people do reproducible data analysis without building their own computing setups. This could speed research across atmospheric science, oceanography, hydrology and glaciology, and give instructors ready-made teaching materials.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Justin Cappos
New York University, NY·Computer Science
Build a command-line framework that automatically records software artifacts, environments, dependencies and actions during experiments, so computational studies can be rebuilt and rerun in the cloud for independent verification.
Douglas Thain
University of Notre Dame, IN·Computer Science
Develop NBFlow, a toolkit that records notebook executions and converts them into workflows that schedule tasks concurrently on high performance clusters or clouds.
Wael Kessentini
DePaul University, IL·Computer Science
Curate a public repository of software refactoring datasets, cleaned and checked for coverage and diversity, to serve as benchmarks for validating new refactoring tools and for empirical studies.
The school
University at Albany: 15 labs on PI Pages, $472M a year on research, 144 research doctorates a year.
Reach out
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