CEDAR email: SuperDARN Data and Software Resources

[Kathryn McWilliams]

On behalf of the SuperDARN community, I would like to bring your 
attention to some cite-able data and software resources that the 
SuperDARN collaboration has available for data users.

SuperDARN aimed for best practices in FAIR (Findable, Accessible, 
Interoperable and Reusable) data principles in creating these resources.


Importantly, the combination of SuperDARN's
     - DOI'd datasets
     - DOI'd software and
     - metadata listing any options you used during data processing
ensures reproducibility for scientific publications.



***DOI'd SuperDARN Data***

The historical SuperDARN dataset as been published at the following data 
repository:
https://www.frdr-dfdr.ca/repo/collection/superdarn

The SuperDARN RAWACF/DAT data are published by year, with each year 
having a unique DOI.  Each data publication contains a README file that 
we ask you to read carefully.  The README file contains rules of the 
road for using the data, as well as contact information for SuperDARN 
Principal Investigators with data in the publication for that year.  
When you are using SuperDARN data, we ask that you reach out to the PI 
whose data you are using, to check for any potential issues with the 
data and to offer collaboration.  PI teams can offer data interpretation 
and scientific collaboration, as well as assist with data processing. 
The one-year datasets are published on FRDR only after all data 
embargoes expire.  For data that are more recent than those published on 
FRDR, users can contact a SuperDARN PI directly.


***DOI'd Data Processing Software***

The Radar Software Toolkit (RST) is SuperDARN's software for data 
processing (e.g., RAWACF to FITACF to GRID to MAP).  RST is published 
with a DOI and is available here:
https://zenodo.org/record/7467337


***DOI'd Data Visualization Software***

In addition to the plotting tools in RST, SuperDARN has python-based 
data visualization software, pyDARN, which is published here:
https://zenodo.org/record/7767590



Thank you to those of you already using SuperDARN data, and we welcome 
new users to explore these resources.  We hope that these tools will 
help you with data access and make publication easier for you.

With kind regards,

Kathryn McWilliams
Chair, SuperDARN Principal Investigator Executive Council