CEDAR email: Releasing InGeO-Resen: An open source software platform to create computationally reproducible results

[Asti Bhatt]

Dear colleagues,

We are pleased to announce the release of Reproducible Software 
Environment (Resen) version 2019.01. Resen is an open source software 
platform that allows the geospace scientists to use several Python 
libraries developed by the community, to access and analyze data from 
various data providers including Madrigal, and create reproducible 
results. For those new to using Python, you can do a test run on the 
online Resen system at 
https://ingeo.datatransport.org/home/resen/resen-online by signing up 
for an account. You will find tutorials available for basic Python 
usage, and specifically to use geospace software libraries. For 
experienced users, you can find installation instructions on 
https://resen.readthedocs.io/ and the download at 
https://github.com/EarthCubeInGeo/resen to run on your local machine.

Both online and offline, you are able to use JupyterLab to do your 
analysis using available Python libraries, or install your own libraries 
on the offline version if you need to.

*Create computationally reproducible results:* A key feature of Resen is 
the ability to containerize the code, data and the underlying system 
configuration for a research result you want to share for computational 
reproducibility - a figure for your paper for example. This feature is 
currently available only in the downloadable version. In Resen, you 
begin your analysis in a 'bucket', which can be exported with relevant 
code and data together as a .tar file, and uploaded to a site like 
Zenodo for sharing with a journal or other researchers. Resen buckets 
are different from simply uploading code and data to Zenodo, as it 
exports the entire containerized environment that includes software and 
data versions, and which allows the end user to run the code without 
concerning themselves with operating system or dependency challenges. 
Currently, only Python environment is supported in Resen, but we hope to 
include other open source languages in future based on community feedback.

*Available data and software:* You can find the list of current geospace 
software packages installed via Resen on the main InGeO website here - 
https://ingeo.datatransport.org/home/resen/packages. These include tools 
to access geospace data from SuperDARN, Madrigal, and MANGO. Besides 
these, you can use any other data for processing with Resen by copying 
it into the relevant bucket. If you are a data provider, and would like 
to include a software interface for users to access data seamlessly in 
Resen, please write to us. If you have developed a Python library for 
geospace applications, and would like to include in future Resen 
releases, please write to us.

Resen was developed under the NSF EarthCube and CSSI grants to create a 
platform for geospace scientists to enable better sharing of data and 
software.

Please feel free to write to us at ingeo at sri.com with any questions and 
feedback.

Sincerely,

The InGeO team

Asti Bhatt, Ashton Reimer, Todd Valentic, Leslie Lamarche, Pablo Reyes

SRI International

-- 
Asti Bhatt
Center for Geospace Studies
SRI International
333 Ravenswood Ave
Menlo Park, CA 94025
Phone # +1-650-859-3424

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