We are living in an age of “big data.” Insights from big data touch almost every part of our lives—from the way we navigate in our cars to the way we shop. Big data has also arrived in biodiversity research due to rapid change in the types and volume of data that researchers can use to ask and answer their scientific questions. The Data Science Lab works with Smithsonian researchers to use big data techniques, such as deep machine learning, to generate insights from their data, whether they are derived from genome sequencing, ecological sensors, or mass digitization of museum objects. These techniques require computational expertise in hardware and software to both build new algorithms and to implement the emerging tools that are developed outside the Smithsonian.
The Data Science Lab is housed in the Office of Research Computing in the Smithsonian Office of the Chief Information Officer.
- Sign up for a GitHub account (if you have not already), and get added to the SI Data Science Lab GitHub organization.
- Get added to the SI Data Science Lab Slack workspace.
- Share your profile photo, a couple-sentence biography, and any relevant links (GitHub, LinkedIn, Twitter) for inclusion on the Data Science Lab People page.
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Smithsonian Hydra High-Performance Compute (HPC) Cluster
Only available to users with a Smithsonian account
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Data Science Lab JupyterHub
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Experimental RedHat JupyterHub
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Version Control
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Python
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R
Before you end your internship, you should make sure that all of your code is organized and posted to a repository on this organization. If you have any novel datasets too big for GitHub, you should post them to the Smithsonian FigShare.