[REVIEW]: Introduction to deep learning: Carpentries-style hands-on lesson material for introducing researchers to deep learning

[editorialbot]

Submitting author: @svenvanderburg (Sven A. van der Burg) Repository: https://github.com/carpentries-lab/deep-learning-intro Branch with paper.md (empty if default branch): Version: v1.2.2 Editor: @magsol Reviewers: @manideepikaa Archive: 10.5281/zenodo.8308391 Paper kind: learning module

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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

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The reviewer guidelines are available here: https://openjournals.readthedocs.io/en/jose/reviewer_guidelines.html. Any questions/concerns please let @magsol 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 @manideepikaa

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.98  T=0.05 s (1088.0 files/s, 276833.0 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Markdown                        25           1305             17           4265
SVG                              6             25             44           3246
CSV                              1              0              0           2001
YAML                            12             90             71            645
TeX                              1             62              0            244
Jupyter Notebook                 1              0            367             35
Python                           1             12              8             15
make                             1              4              0             11
Text                             1              0              0              1
-------------------------------------------------------------------------------
SUM:                            49           1498            507          10463
-------------------------------------------------------------------------------

Commit count by author:

   120	Sven van der Burg
    72	Dafne van Kuppevelt
    66	Colin Sauze
    66	Florian Huber
    65	Carsten Schnober
    60	Peter Steinbach
    44	svenvanderburg
    36	Berend Weel
    36	Djura Smits
    30	Toby Hodges
    16	Kjartan Thor Wikfeldt
    15	Chris Endemann
    12	Pranav Chandramouli
    12	Samantha Wittke
    12	florian-huber
    11	Giordano Lipari
    10	cpranav93
     9	Cunliang Geng
     8	Ashwin V. Mohanan
     5	Angel Daza
     4	Sarah Stevens
     4	YL Wang
     4	andy
     3	dsmits
     2	Anne Fouilloux
     2	Laura
     2	Maurice de Kleijn
     1	Djura
     1	FenneRiemslagh
     1	Kfir
     1	Lucas Esclapez
     1	Matt Graham
     1	Miguel Angel Magana
     1	Mike Laverick
     1	Renato Alves
     1	Yi Sun
     1	Zhian N. Kamvar
     1	k-dominik

[editorialbot]

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

✅ OK DOIs

- 10.1109/MCSE.2006.122 is OK
- 10.5281/zenodo.3960218 is OK
- 10.5281/ZENODO.4770936 is OK
- 10.1186/s13321-021-00558-4 is OK
- 10.5281/zenodo.10970014 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: The Carpentries Curriculum Development Handbook
- No DOI given, and none found for title: The Carpentries Workbench
- No DOI given, and none found for title: fast.ai - Practical Deep Learning for Coders
- No DOI given, and none found for title: Udemy - Basics of Deep Learning
- No DOI given, and none found for title: Udemy - Tensorflow 2.0 \textbar Recurrent Neural N...
- No DOI given, and none found for title: Udemy - Data Science: Intro To Deep Learning With ...
- No DOI given, and none found for title: Coursera - Deep Learning
- No DOI given, and none found for title: freeCodeCamp.org - Learn PyTorch for Deep Learning
- No DOI given, and none found for title: CSC- Practical Deep Learning
- No DOI given, and none found for title: Small Teaching: Everyday Lessons from the Science ...
- No DOI given, and none found for title: Software Carpentry: Programming with Python.
- No DOI given, and none found for title: scikit-learn course
- No DOI given, and none found for title: Introduction to artificial neural networks in Pyth...
- No DOI given, and none found for title: The Dollar Street Dataset: Images Representing the...
- No DOI given, and none found for title: CIFAR-10 and CIFAR-100 datasets

❌ 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:

[editorialbot]

Paper file info:

🚨 Wordcount for paper.md is 2258

✅ The paper includes a Statement of need section

[editorialbot]

License info:

🟡 License found: Other (Check here for OSI approval)

[manideepikaa]

Review checklist for @manideepikaa

Conflict of interest

• [x] As the reviewer I confirm that I have read the JOSE conflict of interest policy and that there are no conflicts of interest for me to review this work.

Code of Conduct

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

General checks

• [x] Repository: Is the source for this learning module available at the https://github.com/carpentries-lab/deep-learning-intro?
• [x] License: Does the repository contain a plain-text LICENSE file with the contents of a standard license? (OSI-approved for code, Creative Commons for content)
• [ ] Version: Does the release version given match the repository release?
• [x] Authorship: Has the submitting author (@svenvanderburg) made visible contributions to the module? Does the full list of authors seem appropriate and complete?

Documentation

• [x] A statement of need: Do the authors clearly state the need for this module and who the target audience is?
• [x] Installation instructions: Is there a clearly stated list of dependencies?
• [x] Usage: Does the documentation explain how someone would adopt the module, and include examples of how to use it?
• [x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the module 2) Report issues or problems with the module 3) Seek support

Pedagogy / Instructional design (Work-in-progress: reviewers, please comment!)

• [x] Learning objectives: Does the module make the learning objectives plainly clear? (We don't require explicitly written learning objectives; only that they be evident from content and design.)
• [x] Content scope and length: Is the content substantial for learning a given topic? Is the length of the module appropriate?
• [x] Pedagogy: Does the module seem easy to follow? Does it observe guidance on cognitive load? (working memory limits of 7 +/- 2 chunks of information)
• [x] Content quality: Is the writing of good quality, concise, engaging? Are the code components well crafted? Does the module seem complete?
• [x] Instructional design: Is the instructional design deliberate and apparent? For example, exploit worked-example effects; effective multi-media use; low extraneous cognitive load.

JOSE paper

• [x] Authors: Does the paper.md file include a list of authors with their affiliations?
• [x] A statement of need: Does the paper clearly state the need for this module and who the target audience is?
• [x] Description: Does the paper describe the learning materials and sequence?
• [x] Does it describe how it has been used in the classroom or other settings, and how someone might adopt it?
• [x] Could someone else teach with this module, given the right expertise?
• [ ] Does the paper tell the "story" of how the authors came to develop it, or what their expertise is?
• [x] References: Do all archival references that should have a DOI list one (e.g., papers, datasets, software)?

[manideepikaa]

Thanks @magsol for giving me the opportunity to review the paper, The topic was well articulated and documented . However, these were few of my recommendations while reviewing the paper.

1. A more stronger and straight-forward statement of need would be great.
2. For the requirements for the software submission, It's Ok , as package.json file was missing for a good Submission.
3. The Github version number was missing and the release version number in the code.
4. In terms of Authorship which involves the visible contributions made by the author to the module, Could you please elaborate on the contributions of Anne Fouilloux as i could see only 2 commits from the author towards the code.
5. The paper is missing a story on how the authors developed it and their expertise.

[carschno]

@manideepikaa thanks a lot for the quick review! FYI: as Sven has left the eScience Center a while ago, I will try to act as a contact person for the review (see https://github.com/openjournals/jose-reviews/issues/281#issuecomment-2853374567), and to address the issues you have found.

[carschno]

In terms of Authorship which involves the visible contributions made by the author to the module, Could you please elaborate on the contributions of Anne Fouilloux as i could see only 2 commits from the author towards the code.

That is a good point! I genuinely do not know some of the listed authors and what they contributed before I joined, so I find it hard to refine the author list. @ashwinvis should be added anyway, he has joined last year.

Regarding @annefou, I am a bit lost myself. She is listed with one commit of 347 lines in the contributors list, but there is no commit of hers in the commit history. Weirdly, exactly the same shows for @dafnevk, including the exact number of lines.

There are a couple of more people who seem to be missing, and I don't want to remove authors due to lack of my own knowledge. Before I go through the entire list, perhaps @tobyhodges do you have a good overview of active authors, and/or some practical guidelines for determining authorship. Also, what are the standards regarding co-author ordering?

[tobyhodges]

Hi, yes. @annefou was heavily involved in the early stages of discussion and design of the lesson. She is not represented in much of the commit history but is partially responsible for the conceptualisation of the lesson. (See this comment for some evidence of that, please let me know if you need more than that.)

@dafnevk coordinated the project for a while from the Netherlands eScience Center, leading coworking calls, contributing to discussions, and writing a lot of the content. I am not sure why that isn't represented in the contributions page, but a grep on the git log of main shows 136 commits:

(base) deep-learning-intro (main) » git log | grep -c 'Dafne van Kuppevelt'
136

If you take a look through the history of closed issues and PRs you will quickly discover plenty of evidence of Dafne's crucial contributions.

@manideepikaa thanks very much for checking. I really appreciate your diligence 🙌 Please let me know if I can provide any more information.

[manideepikaa]

@tobyhodges @carschno Thankyou so much for the detailed explanation. Would you guys consider reordering the co-authors or you were okay with the present ordering ? Just wanted to re-confirm your take on this.

[carschno]

Would you guys consider reordering the co-authors or you were okay with the present ordering ?

We would definitely consider that, along with adding other authors, at least @ashwinvis as suggested above.

Would you have a good guideline for which authors to list at all, and in which order?

[ashwinvis]

@carschno the guidelines for authorship are listed here: https://openjournals.readthedocs.io/en/jose/submitting.html#authorship

[ashwinvis]

Regarding authorship, thank you for considering including me. While the discussion is going on, I noticed that my colleague @wikfeldt was also listed with significant number of commits.

16      Kjartan Thor Wikfeldt

In addition to the commits, in 2022, he had also actively contributed in providing feedback to the lessons. See here:

https://github.com/carpentries-lab/deep-learning-intro/issues?q=is%3Aissue%20state%3Aclosed%20author%3Awikfeldt

Since the review has started, please consider him also to include amongst the authors.

[carschno]

@carschno the guidelines for authorship are listed here: https://openjournals.readthedocs.io/en/jose/submitting.html#authorship

I was not aware of that, thanks! However, it leaves two questions open:

1. Carpentries lessons have a special process (see this comment), so perhaps there are also special author policies regarding lesson authorship vs. JOSE article authorship
2. Which author ordering is recommended?

[magsol]

@carschno

Regarding 1, there are no special authorship considerations that I'm aware of in the context of Carpentries lessons being fast-tracked at JOSE (unless @labarba knows of any?). So I'd say, whatever order you determined and which was approved by Carpentries, should be sufficient for JOSE as well (as long as the single explicit guideline listed in JOSE's authorship document holds: that someone who only contributed financially or is simply in the same organization cannot be named an author).

Aside from that single stipulation, whatever you had for Carpentries should be sufficient here, though I see no reason why you couldn't also add people if you wanted.

[carschno]

@ashwinvis and @wikfeldt could you add yourselves to the author list in the paper, and create a PR? I think that would be the best way to ensure your affiliations etc. are correct, and to formally ensure your consent to being in the author list.

[wikfeldt]

thanks for the ping, i've now added myself and Ashwin in https://github.com/carpentries-lab/deep-learning-intro/pull/611

[carschno]

Would you guys consider reordering the co-authors or you were okay with the present ordering ?

Done, the authors list should now be finalized.

[manideepikaa]

@carschno , Could you please address the rest of the issues that were pointed out so that we can move further.

[carschno]

EDIT: I had missed your updated checklist above, I will work on that.

[carschno]

@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:

[carschno]

@editorialbot set <v1.2.2> as version

[editorialbot]

I'm sorry @carschno, I'm afraid I can't do that. That's something only editors are allowed to do.

[carschno]

@manideepikaa I have updated the paper, hopefully addressing the points you indicated in your checklist.

Regarding the versioning, I have created a new release (v1.2.2) of the lesson. Apparently, you as an editor have to trigger the update with this command:

@editorialbot set <v1.2.2> as version

[carschno]

Also, I have re-ordered the author list alphabetically (apart from Sven being the first author).

[carschno]

@manideepikaa please let me know when you have checked the changes, and whether they satisfy your concerns regarding the open issues from your checklist. Thanks!

[manideepikaa]

@editorialbot set <v1.2.2> as version