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Data to Action: Increasing the Use and Value of Earth Science Data and InformationFor 20 years, ESIP meetings have brought together the most innovative thinkers and leaders around Earth observation data, thus forming a community dedicated to making Earth observations more discoverable, accessible and useful to researchers, practitioners, policymakers, and the public.

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Wednesday, July 17 • 1:30pm - 3:00pm
Getting Stuff Done with R, Python and Jupyter Notebooks

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Sometimes the hardest part of getting started with coding is to determine which is the best software to learn or use! The goal of this session is to provide a basic introduction to three commonly-used tools for data management and analysis and to provide examples of how they can be used for managing data, visualization, exploiting cloud resources, generating metadata, using or creating web services, manipulating XML documents, and facilitating reorganization of data.

A panel will provide brief overviews of R, Python, and Jupyter Notebooks, including examples of what they do best, drawn from real-world applications. Workshop attendees will be encouraged to participate in discussions of data challenges they have encountered and the relative merits of the different tools in meeting them. Participation in the session by coders experienced in one or more of the tools is encouraged, as is participation by those who have yet to use any of these very powerful tools.

NOTES: bit.ly/put_notes_here

Session recording is here.

Presenter: Colin Smith
Presentation Title: Getting Things Done with R
Slides: https://doi.org/10.6084/m9.figshare.9450371

Presenter: John Porter
Presentation Title: Introduction to Python

Presenter: Stace Beaulieu
Presentation Title: How we are using Jupyter Notebooks in the Northeast U.S. Shelf (NES) LTER
Slides: https://doi.org/10.6084/m9.figshare.9450875

Session Take-Aways
  1. Python is more widely used than R.
  2. The visualization features incorporated into Jupyter Notebooks are really valuable for scientists and outside users.
  3. Trying to run R through Jupyter Notebooks can be a challenge but potentially the Jupyter Lab approach could help.

avatar for Stace Beaulieu

Stace Beaulieu

ESIP rep for WHOI, Woods Hole Oceanographic Institution
I'm the Information Manager for the Northeast U.S. Shelf LTER (https://nes-lter.whoi.edu/) and Coordinator for WHOI's Ocean Informatics Working Group (https://www.whoi.edu/ocean-informatics). Come talk with me about data science training in the ocean sciences!
avatar for Colin Smith

Colin Smith

Data manager, Environmental Data Initiative (EDI)
I work on accelerating the archive and reuse of data in ecological science. My interests are in software development and data harmonization.

Chris Turner

Data Librarian, Axiom Data Science
avatar for M. Gastil-Buhl

M. Gastil-Buhl

Information Manager, Moorea Coral Reef Long Term Ecological Research
I curate datasets for an LTER site for reuse in future and current use by other research groups. I am interested in optimizing data usability and making the curation process more efficient. My favorite part of this work is the collegial spirit among LTER site information managers... Read More →

Wednesday July 17, 2019 1:30pm - 3:00pm PDT
Ballrm BC
  Ballrm BC, Panel
  • Area R, Python, Jupyter Notebooks
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