[REVIEW]: graphlayouts: Layout algorithms for network visualizations in R

[editorialbot]

Submitting author: !--author-handle-->@schochastics<!--end-author-handle-- (David Schoch) Repository: https://github.com/schochastics/graphlayouts Branch with paper.md (empty if default branch): Version: v1.0.0 Editor: !--editor-->@crvernon<!--end-editor-- Reviewers: @bpbond, @ndjackso Archive: 10.5281/zenodo.7870213

Status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/662e3b0e187197f2f5625ea03d111b0f"><img src="https://joss.theoj.org/papers/662e3b0e187197f2f5625ea03d111b0f/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/662e3b0e187197f2f5625ea03d111b0f/status.svg)](https://joss.theoj.org/papers/662e3b0e187197f2f5625ea03d111b0f)

Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@bpbond & @ndjackso, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review. First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @crvernon know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @ndjackso

📝 Checklist for @bpbond

[editorialbot]

Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

@editorialbot commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@editorialbot generate pdf

[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.04 s (1164.7 files/s, 123888.3 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               23            196            570           1420
C++                              7             71             31            749
Markdown                         5            197              0            606
YAML                             4             20              9            129
Rmd                              1             71             97            126
TeX                              1              6              0             63
-------------------------------------------------------------------------------
SUM:                            41            561            707           3093
-------------------------------------------------------------------------------

gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1043

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1007/978-3-540-31843-9_25 is OK
- 10.7155/jgaa.00370 is OK
- 10.1007/978-3-642-11805-0_12 is OK
- 10.1007/978-3-319-50106-2_2 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[crvernon]

:wave: - @schochastics , @bpbond, and @ndjackso This is the review thread for the paper. All of our communications will happen here from now on.

Please read the "Reviewer instructions & questions" in the first comment above.

Both reviewers have checklists at the top of this thread (in that first comment) with the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. There are also links to the JOSS reviewer guidelines.

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention https://github.com/openjournals/joss-reviews/issues/5238 so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them instead of waiting until you've reviewed the entire package.

We aim for the review process to be completed within about 4-6 weeks but please make a start well ahead of this as JOSS reviews are by their nature iterative and any early feedback you may be able to provide to the author will be very helpful in meeting this schedule.

[crvernon]

💪 What an awesome team we have on this one!

[ndjackso]

Review checklist for @ndjackso

Conflict of interest

• [x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• [x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• [x] Repository: Is the source code for this software available at the https://github.com/schochastics/graphlayouts?
• [x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• [x] Contribution and authorship: Has the submitting author (@schochastics) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• [x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• [x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• [x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• [x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• [x] Installation: Does installation proceed as outlined in the documentation?
• [x] Functionality: Have the functional claims of the software been confirmed?
• [x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• [x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• [x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• [x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• [x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• [x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• [x] 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

Software paper

• [x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• [x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• [x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
• [x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• [x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[ndjackso]

@editorialbot generate pdf

[ndjackso]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1007/978-3-540-31843-9_25 is OK
- 10.7155/jgaa.00370 is OK
- 10.1007/978-3-642-11805-0_12 is OK
- 10.1007/978-3-319-50106-2_2 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[bpbond]

Review checklist for @bpbond

Conflict of interest

• [x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• [x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• [x] Repository: Is the source code for this software available at the https://github.com/schochastics/graphlayouts?
• [x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• [x] Contribution and authorship: Has the submitting author (@schochastics) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• [x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• [x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• [x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• [x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• [x] Installation: Does installation proceed as outlined in the documentation?
• [x] Functionality: Have the functional claims of the software been confirmed?
• [x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• [x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• [x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• [x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• [x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• [x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• [x] 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

Software paper

• [x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• [x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• [x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
• [x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• [x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[bpbond]

Hi @schochastics

This is an interesting package and nicely written but quite limited paper. I have and am continuing to open specific issues in the target repo, but here are some broader thoughts and suggestions:

• The paper currently doesn't say anything about how to install the software, or minimum version requirements, or dependencies. These are all important to specify. (This does appear in the online non-R documentation I see.)
• The relationship between ggraph, igraph, and graphlayouts is not always clear...I suspect that beginners will appreciate having this spelled out explicitly.
• More generally, a short paragraph about the necessity and utility of network graphs (kinds and volumes of data, etc) would be helpful to introduce readers to their role in data visualization.
• The package help pages are generally solid, thanks.
• The existing package tests are...somewhat minimal; most seem to be 'does it work under a single case'. Consider adding some edge/corner case testing, e.g. for empty lists - cf. https://github.com/schochastics/graphlayouts/issues/55

[schochastics]

Hi @bpbond I addressed/fixed most of the issues. the once still open need feedback from you, except the vignette, which I am still thinking about.

I will address your other points above later

[schochastics]

@bpbond

• Installation details were added. I did not include version numbers because there is no minimum requirement in this specific case. In the tutorial, it is only present because of the interplay of ggraph and ggforce.

• I tried to be more explicit in the paper what igraph and ggraph are and how they relate with graphlayouts. In my opinion, the plotting section serves the purpose of explaining the relation, i.e. that both can use the layout algorithms for plotting. Happy to add more explanations if you think it is needed.

• I wasnt exactly sure how to interpret your comment of adding a "short paragraph about the necessity and utility of network graphs"

• Thanks for calling out the tests. I added some more that also test edge/corner cases. Happy to add even more if you think it is necessary

[schochastics]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[bpbond]

@schochastics Thanks for your changes to the paper, vignette addition, new tests (great!), and other clarifications. Nice job!

@crvernon These changes fully address my feedback above and I have no further suggestions.

[crvernon]

🤝 thanks @bpbond!

[crvernon]

:mega: Mid-week Rally! :mega:

Looks like you guys are making great progress! I see that @bpbond and @schochastics have wrapped up that portion of the review! Nice work!

@ndjackso thanks for setting up your checklist as well! Please let me know if you have any questions as you progress through the process!

[crvernon]

:wave: @ndjackso could you post a quick update about your review status here? Let me know if you have any questions! Thanks!

[crvernon]

👋 @ndjackso just following up...could you post a quick update about your review status here? Let me know if you have any questions! Thanks!

[ndjackso]

Hi, @schochastics.

Thank you for leading the development of the graphlayouts package to support network visualization. Significant package documentation and working examples have been made available through Githab, CRAN, and a website. The package has had multiple releases and has been cited by others. As part of the review, I also tried using the cowplot package as an alternative to combining visualizations generated using graphlayouts (no issues) and other color palettes from the RColorBrewer and viridis packages as these are common packages for my data visualization workflow. The submitted paper provides succinct information related to the package. However, there were a few issues I encountered when replicating examples and reviewing the manuscript as well as package documentation. Some suggestions for your consideration:

• Beyond the “Summary”, the other sections in the software paper could use more detail.
  • The “Statement of Need” section makes reference to igragh and ggraph but there could be an expansion of content to situate graphlayouts relative to current static (e.g., network, sna, statnet, etc.) and dynamic (e.g., networkD3 and VizNetwork) network visualization packages in R.
  • The “Use for plotting” section may be redundant as the plotting capabilities are demonstrated in the subsequent sections and code. Consider removing this section or add additional content to distinguish it further from the other sections
  • The “Overview of algorithms” section shows some of the visualization functions but the descriptions are minimal. There is also unequal coverage of the algorithms presented in the Github repo. Consider adding more detail for all algorithms.
• There is a license available but the type is not specified. Consider adding this information to the LICENSE file
• Some packages are checked during the installation but others are not. When I installed the package using the dev version, I was prompted to update rlang, RccpArmadillo, and the igraph packages. I did not have oaqc installed, and I was not flagged for this until working through the provided examples. Consider adding all packages as part of the check when installing the dev version.
• I received a warning when re-creating the first ggraph example from the “Use for plotting” section:

“Warning: Using the size aesthetic in this geom was deprecated in ggplot2 3.4.0. Please use linewidth in the default_aes field and elsewhere instead.”

Consider reviewing functions to ensure deprecated features from dependent packages are not being used in the current package version

• I received a warning when changing color palettes in the Backbone layout example:

“Warning: n too large, allowed maximum for palette Dark2 is 8 Returning the palette you asked for with that many colors”.

I also encountered this warning with Set2, Pastel2, and Accent palettes in RColorBrewer. This issue appears to stem from the palette choice and not the graphlayouts package. One of the package’s strengths is being able to visualize very large networks. A couple of thoughts to overcome the warning:

• Consider adding a recommended of a color palette that works for large networks as part of the warning
• Considering including a default color palette that works for large n to override limited palettes

I'll create separate issues for these suggestions.

[schochastics]

Hi @ndjackso,

Thanks for the very detailed review. I addressed your concerns in the issues. Two issues remain open for you to check if you are satisfied with my answers. Apologies if I closed some issues too quickly and feel free to reopen if I did not address them right

[schochastics]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[ndjackso]

Hi, @schochastics.

Thanks for responding to the issues! The software paper additions look good, and I appreciate your thoughtful responses to the more open-ended issues.

[ndjackso]

Hi, @crvernon .

@schochastics has incorporated feedback where appropriate. No further issues on my end.

[crvernon]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1007/978-3-540-31843-9_25 is OK
- 10.7155/jgaa.00370 is OK
- 10.1007/978-3-642-11805-0_12 is OK
- 10.1007/978-3-319-50106-2_2 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[crvernon]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[crvernon]

:wave: @schochastics - we are almost there! Your paper and software are looking great! Please address the following item:

• [x] Add the DOI to the Handcock et al. 2008 citation. I believe this is it 10.18637/jss.v024.i01 but please double check.

Once this change has been made we will move to the final steps of setting up the archive for your new release.

We want to make sure the archival has the correct metadata that JOSS requires. This includes a title that matches the paper title and a correct author list.

So here is what we have left to do:

• [x] Conduct a GitHub release of the current reviewed version of the software you now have on the main and archive the reviewed software in Zenodo or a similar service (e.g., figshare, an institutional repository)

• [x] Check the archival deposit (e.g., in Zenodo) to ensure it has the correct metadata. This includes the title (should match the paper title) and author list (make sure the list is correct and people who only made a small fix are not on it). You may also add the authors' ORCID.

• [x] Please list the DOI of the archived version here

I can then move forward with accepting the submission.

[schochastics]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[schochastics]

@crvernon

I added the missing doi and here are the links:

• tagged release: v1.0.0 link
• Zenodo archive: https://zenodo.org/record/7870213
• DOI: https://doi.org/10.5281/zenodo.7870213

[crvernon]

@editorialbot set v1.0.0 as version

[editorialbot]

Done! version is now v1.0.0

[crvernon]

@editorialbot set 10.5281/zenodo.7870213 as archive

[editorialbot]

Done! archive is now 10.5281/zenodo.7870213

[crvernon]

@schochastics - thanks for putting together a really nice software product! Thanks to @bpbond and @ndjackso for a constructive and timely review!

I am recommending that your submission be accepted. An EIC will review this shortly and confirm final publication if all goes well.

[crvernon]

@editorialbot recommend-accept

[editorialbot]

Attempting dry run of processing paper acceptance...

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1007/978-3-540-31843-9_25 is OK
- 10.7155/jgaa.00370 is OK
- 10.1007/978-3-642-11805-0_12 is OK
- 10.1007/978-3-319-50106-2_2 is OK
- 10.18637/jss.v024.i01 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

:wave: @openjournals/csism-eics, this paper is ready to be accepted and published.

Check final proof :point_right::page_facing_up: Download article

If the paper PDF and the deposit XML files look good in https://github.com/openjournals/joss-papers/pull/4182, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

[arfon]

@schochastics – I found a tiny issue with the formatting of your paper. Could you please merge this PR: https://github.com/schochastics/graphlayouts/pull/68 ?

[schochastics]

@arfon thanks! merged now

[arfon]

@editorialbot recommend-accept

[editorialbot]

Attempting dry run of processing paper acceptance...