Jupyter Notebook in Science and Education at UCSD

TITLE: The UC San Diego Data Science & Machine Learning PlatformAdam Tilghman, Systems Architect; David Andersen, Systems Integration Engineer; Paul Jamason, Systems Integration Engineer, Educational Technology Services, ITS, UC San Diego
UC San Diego’s Data Science/Machine Learning Platform (DSMLP; https://datahub.ucsd.edu) provides undergraduate and graduate students with access to research-class CPU/GPU resources for coursework, formal independent study, and student projects. Built and operated by IT Services (ITS), with additional financial contributions from Cognitive Science and Jacobs School of Engineering, DSMLP leverages Qualcomm Institute’s current research into cost-effective machine-learning cyberinfrastructure, using Kubernetes and Docker container technologies.
TITLE: Data Science Support at the UC San Diego Library
Stephanie Labou, Data Science Librarian, UC San Diego
Like many campus-wide and departmental units at UC San Diego, the library has scaled up its data science capacity to better support the Halıcıoğlu Data Science Institute and the Data Science major. Traditional library services such as student and faculty consultations, resources and guidelines for best practices (including for Jupyter notebooks!), and hands-on training have been expanded to meet the computationally-intensive needs of data science education and research.
TITLE: The Human Cell Atlas Notebook Workspace
Michael Reich, Asst. Director of Bioinformatics, UC San Diego
Enabled by new genomics technologies, the Human Cell Atlas (HCA) aims to create a resource where investigators can query cellular states in multiple tissues to better understand biological mechanisms and disease processes at the resolution of a single cell. We have created a Human Cell Atlas Notebook workspace, http://hca.genepattern.org, built on the Jupyter Notebook environment and the GenePattern platform for integrative genomics, that hosts advanced analysis notebooks created by the HCA community, allows direct access to the HCA data from within a notebook, hosts compute-intensive analyses on the Amazon cloud, and provides many additional features allowing non-programming biologists and biomedical investigators to take advantage of this transformative resource.