Welcome to the Earth Science Information Partners (ESIP) 2018 Summer Meeting! The 2018 theme is Realizing the Socioeconomic Value of Data. The theme is based on one of the goals in the 2015 - 2020 ESIP Strategic Plan, which provides a framework for ESIP’s activities over the next three years.

If you haven’t already, register here!

Room Block Update: Our block is full. We recommend the AC Hotel Tucson Downtown, which is about 5 minutes by car and is accessible via the Tucson Streetcar in about fifteen minutes.
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Tuesday, July 17 • 9:30am - 11:00am
Introduction to Jupyter technologies and how they are used in the ESIP community

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You’ve heard a lot about Jupyter. There are Notebooks and Hubs, but what are they? Do they make it easier for you to do or share your work?

Participants in this session will be given an overview on how ESIP members are using the Jupyter Project’s applications to accelerate their own research. This breakout session is intended as an introduction not only to Jupyter applications and their usage in ESIP member organizations. Workshops using the technologies via ESIPhub later in the Meeting will also be discussed. We will hold a ten minute discussion after the presentations on the topics brought up during the talks and how we as a community can use the ESIPhub resource.


Tyler Erickson, Google (15min)
Title: Jupyter and Google Earth Engine
Description: Google Earth Engine is a cloud-based geospatial analysis platform that supports analysis of multi-petabyte archives via JavaScript and Python APIs. For users of the JavaScript API. the Earth Engine team maintains an online GUI. For the Python API, we promote the use of Jupyter project tools (JupyterLab, JupyterHub, Jupyter Widgets) for accessing data and developing algorithms.

Keith Maull, NCAR Library (15min)

Thomas Huang, NASA JPL (15min)

John Readey, HDF Group (15min)
Title: HDF Kita Lab
Description: HDF Kita Lab is a Jupyter environment hosted on AWS that provides the ability to easily read and write large HDF datasets.  Users have the ability to utilize HDF Server to access data that would otherwise be too large to copy to the user disk volume.  Data used by HDF Server is stored in AWS S3, which is provides cost-effective and reliable storage.  HDF Kita Lab can be access at: https://hdflab.hdfgroup.org (HDFGroup registration is required).

Rich Signell, USGS (15min)
Title: Jupyter Success Stories from IOOS and USGS
Description: The Integrated Ocean Observing System and the US Geological Survey have been using Jupyter technologies since 2012 to help spread the use of effective and efficient tools across their communities.  These notebooks often demonstrate reproducible workflows based on catalog and data web services and come with reproducible environments made possible by the conda-forge project.  A series of notebooks will be demonstrated, from notebooks demonstrating catalog-driven workflows, to notebooks on binder that appear like web applications.

Discussion (10)

Learn more about Jupyter and attend the other workshops using ESIPhub:

* Directly after this session is the Metadata Improvement Lab where participants will learn how to translate their xml into JSON-LD using the schema.org vocabulary Google recommends for datasets.
* Wednesday afternoon is a workshop for cloud-based analysis.
* Thursday morning we'll learn about some custom widgets for earth science.

Speakers & Moderators
avatar for Sean Gordon

Sean Gordon

Metadata Developer, The HDF Group
Be sure to attend my workshop Tuesday morning, http://sched.co/Eypl. You'll only need a connected web browser to analyze xml for schema.org dataset concepts!Talk to me about the ESIP Labs project, ESIPhub a JupyterHub based shared computational environment for workshops at Meetings.My... Read More →
avatar for Thomas Huang

Thomas Huang

Technical Group Supervisor, JPL
avatar for Rich Signell

Rich Signell

Oceanographer, USGS
Ocean Modeling, Python, NetCDF, THREDDS, ERDDAP, UGRID, SGRID, CF-Conventions, Jupyter, JupyterHub, CSW, TerriaJS

Tuesday July 17, 2018 9:30am - 11:00am
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Attendees (28)