AWS talk and blog post, XrVis, Lab-relevant AGU sessions, and Climata!

Highlights from your favorite Earth science virtual lab! 
July 10, 2019
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1. AGU Sessions of Interest
2. XrViz: An Interactive visualization interface for Xarrays
3. Climata: A Pythonic interface for loading and processing time series data

AGU Sessions of Interest

It's that time of year again! As you consider where to submit your AGU Fall meeting abstracts, consider the following ESIP Lab-relevant sessions:

• IN041 Recent Innovations in Open Science Platforms: Data and Algorithm Sharing Usher in a New Era of Earth Science 
• U009 Data Analytics and Machine Learning Innovation for Climate and Earth Surface Processes 
• NS003 A tour of open-source software packages for the geosciences 
• IN009 Applications of Free and Open-Source Technologies for Advancing Earth and Space Science 
• PA030 Issues in Data Policy: The Ethics of Using Open Data Sets and Open Software in Geophysical Research 
• IN002 Advanced Geospatial Cyberinfrastructure for Deep Learning 

XrViz: An interactive visualization interface for Xarrays

XrViz is an interactive, in-browser visualization interface for Xarrays backed by the full power of the Python ecosystem. It allows controlled data points selection, massive rendering, data display, custom interaction and selection of fields for plotting in the browser using Intake, Xarray, and PyViz(now HoloViz) collection of tools. It holds the promise of saving Earth Science and other researchers significant amounts of time since they can directly focus on visual data analysis and research rather than writing custom code to explore data.

XrViz is an ESIP Google Summer of Code project with the gifted student Harman Deep Singh. The project is being mentored by Rich Signell at USGS and Martin Durant from Anaconda, inc. 

Read more here. 

Climata: A Pythonic interface for loading and processing time series data. 

Lab Fellow Ben Roberts-Pierel highlights one of his favorite data exploration tools

Anybody who works with time series data will know there are myriad ways of acquiring, cleaning and analyzing those data. As the scientific community continues to work with these more temporally and spatially continuous datasets, streamlining workflows becomes likewise more important. There are numerous ways to do this but recently I have found the climata package (https://pypi.org/project/climata/) for Python a useful tool for pulling down data from the SNOTEL network. The package is setup to acquire time series data from a variety of climatological and hydrological sensor networks maintained by several government agencies. The tool can be run from the command line or embedded in a larger workflow. Although there are many such packages out there, this one has been easy to use, it is already setup to acquire domain specific data and has been (mostly) free of unexpected glitches. Anybody who is interested can check the github at: https://github.com/heigeo/climata

For those of you interested in the SNOTEL network and other applications of sensor network and remote sensing data, please consider attending the “Multi-sensor data integration for cryosphere and hydrosphere monitoring” session that I will be organizing at this year’s ESIP Summer Meeting. The session will feature presentations on applications of sensor network, remote sensing and modeled data by Dr. Jeff Deems of the National Snow and Ice Data Center (NSIDC), Dr. Eric Sproles of Montana State University and recipient of an ESIP Lab grant, Scott Oviatt from the Natural Resources Conservation Service (NRCS) and NOAA postdoc and ESIP Community Fellow, Dr. Yuhan Rao. The session will take place on Thursday, July 18^th at 10:30 AM. Please contact me at robertsb@oregonstate.edu with any questions!