'nuts': Convert European Regional Data

[AAoritz]

Date accepted: 2024-03-14 Submitting Author Name: Moritz Hennicke Submitting Author Github Handle: !--author1-->@AAoritz<!--end-author1-- Other Package Authors Github handles: !--author-others-->@krausewe<!--end-author-others-- Repository: https://github.com/AAoritz/nuts/ Version submitted: 0.0.0.9000 Submission type: Standard Editor: !--editor-->@maelle<!--end-editor-- Reviewers: @nolwenn, @jospueyo

Archive: TBD Version accepted: TBD Language: en

---

• Paste the full DESCRIPTION file inside a code block below:

Package: nuts
Title: 'nuts': Convert European Regional Data
Version: 0.0.0.9000
Authors@R: c(person("Moritz", "Hennicke", email = "AAoritz@posteo.de", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-6811-1821")),
         person("Werner", "Krause", email = "werner.krause@uni-potsdam.de", role = c("aut"),
           comment = c(ORCID = "0000-0002-5069-7964")))
Description: Motivated by changing administrative boundaries over time, the 'nuts' package can convert European regional data with NUTS codes between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1, NUTS 2 and NUTS 3). The package uses spatial interpolation based on granular (100mx100m) population and land use data provided by the European Commission's Joint Research Center.  
URL: https://AAoritz.github.io/nuts/
BugReports: https://github.com/AAoritz/nuts/
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
Suggests: 
    distill,
    eurostat,
    formatR,
    ggalluvial,
    ggfittext,
    ggplot2,
    ggpubr,
    ggrepel,
    gridExtra,
    kableExtra,
    knitr,
    raster,
    RColorBrewer,
    readr,
    rmarkdown,
    sf,
    terra,
    testthat,
    tidyr
Config/testthat/edition: 3
VignetteBuilder: knitr
Imports:
    crayon,
    dplyr,
    stringr
Depends: 
    R (>= 3.5.0)
LazyData: true

Scope

• Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):

  • [ ] data retrieval
  • [ ] data extraction
  • [X] data munging
  • [ ] data deposition
  • [X] data validation and testing
  • [ ] workflow automation
  • [ ] version control
  • [ ] citation management and bibliometrics
  • [ ] scientific software wrappers
  • [ ] field and lab reproducibility tools
  • [ ] database software bindings
  • [X] geospatial data
  • [ ] text analysis

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

Data munging: Linking regional data from different sources at the level of NUTS codes is often complicated by the usage of different versions or varying levels of geographical granularity across sources. The package can be used to harmonize NUTS versions and levels across different data sources using spatial interpolation.

Data validation and testing: The package includes routine tasks to test for the validity and completeness of NUTS codes.

Geospatial data: NUTS codes are the dominant format for European regional data.

• Who is the target audience and what are scientific applications of this package?

The target audience are academics, journalists and data scientists interested in European regional data. Users who want to exploit changes within NUTS regions over time face the challenge that administrative boundaries are redrawn over time. The package enables the construction of consistent panel data across NUTS regions and over time through the harmonization of NUTS regions to one common version or level of granularity.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

To our knowledge there is currently no package that is targeted at the conversion of NUTS versions using spatial interpolation.

The regions package allows for re-coding of NUTS codes from version to version without spatial interpolation. The package offers some code validation routines, but not an automated detection of the NUTS version used.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Yes

• If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

• Explain reasons for any pkgcheck items which your package is unable to pass.

Technical checks

Confirm each of the following by checking the box.

• [X] I have read the rOpenSci packaging guide.
• [X] I have read the author guide and I expect to maintain this package for at least 2 years or to find a replacement.

This package:

• [X] does not violate the Terms of Service of any service it interacts with.
• [X] has a CRAN and OSI accepted license.
• [X] contains a README with instructions for installing the development version.
• [X] includes documentation with examples for all functions, created with roxygen2.
• [X] contains a vignette with examples of its essential functions and uses.
• [X] has a test suite.
• [X] has continuous integration, including reporting of test coverage.

Publication options

• [X] Do you intend for this package to go on CRAN?

Code of conduct

• [X] I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

[maelle]

@nolwenn could you please read the response of the authors and respond?

[nolwenn]

Reviewer Response

I enjoyed reviewing your package and was happy you found my comments valuable. Sorry for the late replies to your answers.

About the remaining points of discussion:

1. I have no longer the namespace error message. All seems working out well.

2. r nuts_convert_version()

   • including an option in r nuts_convert_version() that could return e.g. a column in the converted dataset containing more details on the conversion could indeed be an interesting way of doing implementing it.
   • an example in the vignette on how to extracted, by sub-setting and transforming the tibble data(cross_walks) is also nice

3. Missing regions : weights missing due to missing regions by changing the r missing_rm option to a threshold at which the users feel confident to assume 0 for the missing regions is a good idea to implement.

Final approval (post-review)

• [ x] The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 1 hour

[AAoritz]

Many thanks @nolwenn and @jospueyo for both of your enthusiastic and speedy reviews and your final approval. Based on your last comments we made the following edits:

• We introduced an option to compute the share of missing weights enabling the users to convert regions approximately where missing values are negligible. https://github.com/AAoritz/nuts/commit/5af7b8f77b86852cf20782b82bcfbc9e97850df9
• We elaborate in the vignette on accessing and sub-setting the internal conversion tables. https://github.com/AAoritz/nuts/commit/89c84e3028d552363995808698a355b8be3d38ca

Your comments made a big difference for this package! Thank you for your time and efforts!

[AAoritz]

One question on verbosity control @maelle. We thought that our current implementation using rlang::local_options() based on your recommendations would set verbosity as a default. However, verbosity has to be switched on to function. Do you understand why?

[maelle]

In https://github.com/AAoritz/nuts/blob/cf42cce8e522d4bd9ae1e8506024620dd964cebe/R/nuts_convert_version.R#L299

is_verbose_mode <- (getOption("nuts.verbose", "quiet") == "verbose")

The default is "quiet", not "verbose".

Change the line to:

is_verbose_mode <- (getOption("nuts.verbose", "verbose") == "verbose")

[maelle]

Thanks @jospueyo & @nolwenn for your work as reviewers!

Thanks @AAoritz @krausewe for your work on your package!

[maelle]

@ropensci-review-bot approve nuts

[ropensci-review-bot]

Approved! Thanks @AAoritz for submitting and @nolwenn, @jospueyo for your reviews! :grin:

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[AAoritz]

Makes sense... we set the default to verbose. Thank you @maelle for this, your super helpful comments and your work as the editor during the review process! @krausewe and I learned a lot!

[AAoritz]

@nolwenn and @jospueyo, many thanks again! Please let us know if we can add you in the meta description as reviewers of the package. @maelle can we include you as well?!

[ropensci-review-bot]

I'm sorry human, I don't understand that. You can see what commands I support by typing:

@ropensci-review-bot help

[AAoritz]

@ropensci-review-bot finalize transfer of nuts

[ropensci-review-bot]

Transfer completed. The nuts team is now owner of the repository and the author has been invited to the team

[maelle]

@maelle can we include you as well?!

Thanks for asking, but there's no need to list editors. Your participation in this process is thanks enough :smile_cat:

[nolwenn]

@nolwenn and @jospueyo, many thanks again! Please let us know if we can add you in the meta description as reviewers of the package. @maelle can we include you as well?!

Thanks for proposing. I do not know the convention but do as you like. As @maelle I am already happy to know that I helped.

[jospueyo]

@nolwenn and @jospueyo, many thanks again! Please let us know if we can add you in the meta description as reviewers of the package. @maelle can we include you as well?!

Thanks for proposing. I do not know the convention but do as you like. As @maelle I am already happy to know that I helped.

I'd be honoured to be recognized for my tiny contribution to your so useful package.

[AAoritz]

Should you want to acknowledge your reviewers in your package DESCRIPTION, you can do so by making them "rev"-type contributors in the Authors@R field (with their consent).

Including referees into the DESCRIPTION field is encouraged as you can see and we believe that it's a great idea in this context! Thanks a lot everybody!