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[REVIEW]: ICAT: The Interactive Corpus Analysis Tool #6873

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editorialbot opened this issue Jun 11, 2024 · 20 comments
Open

[REVIEW]: ICAT: The Interactive Corpus Analysis Tool #6873

editorialbot opened this issue Jun 11, 2024 · 20 comments
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review Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning

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editorialbot commented Jun 11, 2024

Submitting author: @WarmCyan (Nathan Martindale)
Repository: https://github.com/ORNL/icat
Branch with paper.md (empty if default branch):
Version: v0.7.2
Editor: @JBorrow
Reviewers: @SamHames, @jhagerer
Archive: Pending

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/0528d60ff4f251069d15456fdb83bd0f"><img src="https://joss.theoj.org/papers/0528d60ff4f251069d15456fdb83bd0f/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/0528d60ff4f251069d15456fdb83bd0f/status.svg)](https://joss.theoj.org/papers/0528d60ff4f251069d15456fdb83bd0f)

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

@SamHames & @jhagerer, 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 @JBorrow 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 @SamHames

@editorialbot
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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

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Software report:

github.com/AlDanial/cloc v 1.90  T=0.14 s (1023.5 files/s, 314809.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
HTML                            37           6489            182          18202
SVG                              6              6              6           4476
Python                          22           1051           1446           3640
Jupyter Notebook                14              0           3223            951
CSS                              6            185             42            842
JavaScript                       8            123            183            778
reStructuredText                34            485            943            276
Markdown                         5            102              0            183
YAML                             5              9             12            139
TeX                              1             12              0            138
make                             2             16              9             54
DOS Batch                        1              8              1             26
Bourne Shell                     1              8             10             20
JSON                             1              0              0              8
TOML                             1              1              0              8
-------------------------------------------------------------------------------
SUM:                           144           8495           6057          29741
-------------------------------------------------------------------------------

Commit count by author:

   136	Martindale, Nathan
     2	Nathan Martindale

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Paper file info:

📄 Wordcount for paper.md is 1543

✅ The paper includes a Statement of need section

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

OK DOIs

- 10.1145/3185517 is OK
- 10.1145/3593013.3594087 is OK
- 10.1609/aimag.v35i4.2513 is OK
- 10.1109/TAMD.2010.2051030 is OK
- 10.1145/3241379 is OK
- 10.1145/604045.604056 is OK

MISSING DOIs

- No DOI given, and none found for title: Machine Teaching: A New Paradigm for Building Mach...
- No DOI given, and none found for title: Panel: The powerful data exploration & web app fra...
- No DOI given, and none found for title: ipyvuetify: Jupyter widgets based on vuetify UI co...
- No DOI given, and none found for title: Scikit-learn: Machine Learning in Python

INVALID DOIs

- None

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License info:

✅ License found: BSD 3-Clause "New" or "Revised" License (Valid open source OSI approved license)

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👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

@JBorrow
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JBorrow commented Jun 11, 2024

Hi @WarmCyan! Would you please be able to address the missing DOIs in the references?

@SamHames
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SamHames commented Jun 15, 2024

Review checklist for @SamHames

Conflict of interest

  • 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

General checks

  • Repository: Is the source code for this software available at the https://github.com/ORNL/icat?
  • License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@WarmCyan) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
  • Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
  • 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.
  • Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
  • 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

  • Installation: Does installation proceed as outlined in the documentation?
  • Functionality: Have the functional claims of the software been confirmed?
  • 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

  • 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

Software paper

  • Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
  • 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?
  • State of the field: Do the authors describe how this software compares to other commonly-used packages?
  • Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
  • 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?

@WarmCyan
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Hello @JBorrow! I've added DOIs for all except ipyvuetify, I couldn't find anything for that one

@WarmCyan
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@SamHames thanks for agreeing to review this! Just so you're aware if you start playing with the software soon, there's a couple weird issues going on right now with dependencies that I'm still trying to resolve, if you run into problems during setup I'm tracking them over here: ORNL/icat#44

@jhrinv
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jhrinv commented Jun 22, 2024

Hi all, I am in contact with the authors. They have been actively working to fix some issues in the repository (broken package dependencies die to updates). I'll investigate the fixes and latest end of next week. I provide my checklist here then too. Thanks for your patience.

@jhagerer
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jhagerer commented Jul 7, 2024

Review checklist for @jhagerer (-> still in process!!!)

Conflict of interest

  • 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

General checks

  • Repository: Is the source code for this software available at the https://github.com/ORNL/icat?
  • License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@WarmCyan) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
  • Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
  • 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.
  • Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
  • 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

  • Installation: Does installation proceed as outlined in the documentation?
  • Functionality: Have the functional claims of the software been confirmed?
  • 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

  • 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

Software paper

  • Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
  • 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?
  • State of the field: Do the authors describe how this software compares to other commonly-used packages?
  • Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
  • 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?

@jhagerer
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jhagerer commented Jul 7, 2024

This review is still in process. Issues with the code repository still have to be analyzed and fixed, see ORNL/icat#44.

@JBorrow
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JBorrow commented Aug 14, 2024

Hi all, just checking in that the responses to the review items are progressing?

@WarmCyan
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Hey @JBorrow! We've determined in ORNL/icat#44 that ICAT doesn't run in vscode (which is somewhat expected/outside of what I'm trying to support.) I'm not sure if @jhagerer has had a chance to take a look at it since, but I'm waiting to see if it runs correctly for him in Jupyter Lab.

@jhagerer
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jhagerer commented Aug 20, 2024

@WarmCyan I got icat running successfully. However, it looks honestly not fully usable, since I cannot recognize the text on the right, and also the illustration could be improved:

image

As you see, I used Jupyter Notebook and Jupyter Lab. Both look not ideal, even though both are recommended in the official documentation. What is your comment on that with regards to usability and correct display?

Further, I think it would be good to give a hint somewhere in the documentation that Visual Studio Jupyter code cells should not be used. Last but not least, I would recommend an advanced example that does not require transformers with a CUDA/NVIDIA hardware, but maybe something more lightweight but still reasonable and computationally efficient, e.g., word2vec.

I am giving this advice, since I would really like to use and understand this tool, but I would be afraid that users might experience unnecessarily difficult entry barriers, which would undermine the efforts already made by the authors.

@WarmCyan
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@jhagerer yeah this is a good point, I didn't do due diligence in making sure it looks right in light mode as well, and that certainly has a huge impact on usability. The jarring mismatch of colors and inability to read the text should be fixable by checking for light/dark theme and adjusting interface coloring accordingly. To address the scrolling/crampedness of the jupyter notebook cells, I'll add a check for notebook vs lab and auto-scale components to make sure they fit.

I've opened an issue to track this here: ORNL/icat#45 and will try to make both of these changes within the next week or two.

@WarmCyan
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That's also a good point about an additional example notebook that doesn't need transformers to run, I've opened an issue for it here: ORNL/icat#46

@jhagerer
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jhagerer commented Oct 6, 2024

I can confirm that the authors addressed my feedback. Now it is my job to try out the tools and go through its documentation in order to finish the peer review.

@JBorrow
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JBorrow commented Oct 6, 2024

Excellent! Let me know if there is anything else any of you need, or if there are any further questions.

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