Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[PRE REVIEW]: Metasyn: Transparent Generation of Synthetic Tabular Data with Privacy Guarantees #7093

Closed
editorialbot opened this issue Aug 9, 2024 · 25 comments
Assignees
Labels
Dockerfile pre-review Python Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning

Comments

@editorialbot
Copy link
Collaborator

editorialbot commented Aug 9, 2024

Submitting author: @vankesteren (Erik-Jan van Kesteren)
Repository: https://github.com/sodascience/metasyn
Branch with paper.md (empty if default branch):
Version: v1.0.2
Editor: @crvernon
Reviewers: @PetrKorab, @misken
Managing EiC: Chris Vernon

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/43fd4234e18bfd94b952aea35db8b883"><img src="https://joss.theoj.org/papers/43fd4234e18bfd94b952aea35db8b883/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/43fd4234e18bfd94b952aea35db8b883/status.svg)](https://joss.theoj.org/papers/43fd4234e18bfd94b952aea35db8b883)

Author instructions

Thanks for submitting your paper to JOSS @vankesteren. Currently, there isn't a JOSS editor assigned to your paper.

@vankesteren if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.

Editor instructions

The JOSS submission bot @editorialbot is here to help you find and assign reviewers and start the main review. To find out what @editorialbot can do for you type:

@editorialbot commands
@editorialbot editorialbot added pre-review Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning labels Aug 9, 2024
@editorialbot
Copy link
Collaborator Author

Hello human, 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
Copy link
Collaborator Author

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

OK DOIs

- 10.5281/zenodo.7697217 is OK
- 10.18637/jss.v059.i10 is OK

MISSING DOIs

- No DOI given, and none found for title: ONS methodology working paper series number 16—Syn...
- No DOI given, and none found for title: Differential privacy
- No DOI given, and none found for title: Statistical disclosure control
- No DOI given, and none found for title: k-anonymity: A model for protecting privacy
- No DOI given, and none found for title: Guidelines for Output Checking. Eurostat
- 10.29012/jpc.v1i2.570 may be a valid DOI for title: Differential privacy for statistics: What we know ...
- 10.1007/bf02985802 may be a valid DOI for title: The elements of statistical learning: data mining,...
- 10.1007/978-1-4612-0919-5_38 may be a valid DOI for title: Information theory and an extension of the maximum...
- 10.1002/wics.199 may be a valid DOI for title: The Bayesian information criterion: background, de...
- No DOI given, and none found for title: synthpop: Bespoke creation of synthetic data in R
- No DOI given, and none found for title: Simulation of synthetic complex data: The R packag...
- No DOI given, and none found for title: Datasynthesizer: Privacy-preserving synthetic data...
- No DOI given, and none found for title: To democratize research with sensitive data, we sh...

INVALID DOIs

- None

@editorialbot
Copy link
Collaborator Author

Software report:

github.com/AlDanial/cloc v 1.90  T=0.08 s (1246.2 files/s, 288667.2 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
CSV                              5              0              0          11376
Python                          40            931           1409           3146
JSON                             3              1              0            767
reStructuredText                28            746           1002            639
Markdown                         4            118              0            351
TOML                             5             48              3            243
TeX                              1             13              0            148
YAML                             5             20             23            144
SVG                              5              0              0             98
Jupyter Notebook                 1              0           1789             68
DOS Batch                        1              8              1             26
make                             1              6              7             11
Dockerfile                       1              6              7              8
-------------------------------------------------------------------------------
SUM:                           100           1897           4241          17025
-------------------------------------------------------------------------------

Commit count by author:

    95	qubixes
    34	Erik-Jan van Kesteren
    29	Samuwhale
    26	Samuel
    13	Raoul Schram

@editorialbot
Copy link
Collaborator Author

Paper file info:

📄 Wordcount for paper.md is 2230

✅ The paper includes a Statement of need section

@editorialbot
Copy link
Collaborator Author

License info:

✅ License found: MIT License (Valid open source OSI approved license)

@editorialbot
Copy link
Collaborator Author

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

@editorialbot
Copy link
Collaborator Author

Five most similar historical JOSS papers:

simstudy: Illuminating research methods through data generation
Submitting author: @assignUser
Handling editor: @mikldk (Retired)
Reviewers: @gagolews, @brunaw
Similarity score: 0.6500

Copulas.jl: A fully Distributions.jl-compliant copula package
Submitting author: @lrnv
Handling editor: @osorensen (Active)
Reviewers: @lucaferranti, @AnderGray
Similarity score: 0.6431

verdata: An R package for analyzing data from the Truth Commission in Colombia
Submitting author: @thegargiulian
Handling editor: @Nikoleta-v3 (Active)
Reviewers: @jamesmbaazam, @JosiahParry
Similarity score: 0.6322

PyNM: a Lightweight Python implementation of Normative Modeling
Submitting author: @harveyaa
Handling editor: @dfm (Active)
Reviewers: @smkia, @saigerutherford
Similarity score: 0.6316

Contextualized: Heterogeneous Modeling Toolbox
Submitting author: @cnellington
Handling editor: @fabian-s (Active)
Reviewers: @holl-, @pescap
Similarity score: 0.6288

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

@crvernon
Copy link

crvernon commented Aug 9, 2024

👋 @vankesteren - thanks for your submission to JOSS. While I find you a topic editor, please reduce the word count of your paper to at or under 1000 words. Thanks!

@vankesteren
Copy link

Ah sorry, in editing the paper further I forgot about the word count limit! I'll do my best to do this by next week.

@crvernon
Copy link

@editorialbot assign me as editor

I think I'll just manage this review myself. Let me get you two reviewers and we will kick things off.

@editorialbot
Copy link
Collaborator Author

Assigned! @crvernon is now the editor

@crvernon
Copy link

👋 @PetrKorab - Would you be willing to review this submission to JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

@crvernon
Copy link

👋 @KennethEnevoldsen - Would you be willing to review this submission to JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

@PetrKorab
Copy link

@crvernon Yes, sure👍

@crvernon
Copy link

@editorialbot add @PetrKorab as reviewer

Thanks @PetrKorab! I will kick this off once we confirm one more reviewer.

@editorialbot
Copy link
Collaborator Author

@PetrKorab added to the reviewers list!

@vankesteren
Copy link

In case you still need it, I looked up a few people on the JOSS reviewer list and these suggestions came up:

@KennethEnevoldsen
Copy link

@crvernon, sadly, I have a lot on my plate until mid-September, but after that, I am open to doing this review.

@crvernon
Copy link

Thanks for the fast notice @KennethEnevoldsen!

@crvernon
Copy link

👋 @misken - Would you be willing to review this submission to JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

@misken
Copy link

misken commented Aug 13, 2024

Yep, I can review this submission.

@crvernon
Copy link

@editorialbot add @misken as reviewer

Thanks @misken!

@editorialbot
Copy link
Collaborator Author

@misken added to the reviewers list!

@crvernon
Copy link

crvernon commented Aug 13, 2024

@editorialbot start review

👋 - Alright @vankesteren, @PetrKorab, and @misken - I am going to close this Pre-Review and kick off the full review which you should receive a notification for. Thanks!

@editorialbot
Copy link
Collaborator Author

OK, I've started the review over in #7099.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Dockerfile pre-review Python Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning
Projects
None yet
Development

No branches or pull requests

6 participants