CausalR Publications Criteria Check

[policybot2020]

Software is online:
https://isomemoapp.com/app/causalr

• The software must be open source as per the OSI definition.
• The software must be hosted at a location where users can open issues and propose code changes without manual approval of (or payment for) accounts.
• The software must have an obvious research application.
• You must be a major contributor to the software you are submitting, and have a GitHub account to participate in the review process.
• Your paper must not focus on new research results accomplished with the software.
• Your paper (paper.md and BibTeX files, plus any figures) must be hosted in a Git-based repository together with your software.
• The paper may be in a short-lived branch which is never merged with the default, although if you do this, make sure this branch is created from the default so that it also includes the source code of your submission.

In addition, the software associated with your submission must:

• Be stored in a repository that can be cloned without registration.
• Be stored in a repository that is browsable online without registration.
• Have an issue tracker that is readable without registration. (issue tracker will be on the README.md page)
• Permit individuals to create issues/file tickets against your repository.

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?

• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.

Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).

• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?

• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?

• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

• Make the intro paragraph for submission page

FINAL PAPER SUBMISSION:

• https://joss.theoj.org/papers/new

[isomemo]

@policybot2020 set permissions to allow users to create issues/file tickets and you can upload the paper as a pdf after we go through the submission process.

[policybot2020]

• NEED TO MAKE THE PAPER.md

example:

• https://github.com/sidiwang/snSMART
• https://joss.readthedocs.io/en/latest/example_paper.html

Status check ex: openjournals/joss-reviews#7289

[policybot2020]

Final Check on the requirements:

openjournals/joss-reviews#6678 (comment)

[policybot2020]

Paper.md Not compiling

! error:  (file /tmp/tex2pdf.-6e072cf870f2375b/d205cbd6783332a212c5ae92d73c77178
c2d2f28.png) (readpng): internal error
!  ==> Fatal error occurred, no output PDF file produced!

![The proposed workflow of CausalR.\label{fig:workflow}](causalr_workflow.png){ width=80% }
![An example of CausalR's interface.\label{fig:interface}](causalr_interface.png){ width=80% }

[policybot2020]

R-shiny dashboard: causalR can imitate: https://joss.theoj.org/papers/10.21105/joss.03467

[policybot2020]

Cover Letter

CausalR is a R-Shiny Dashboard that allows users to use counterfactual bayesian methods to model and visualize causal impact of an intervention. It features rapid data retrieval from existing archeological data sources, causal bayesian modeling flexibility, and highly customizable graphical outputs.