Presubmission inquiry - openalexR: interacts with OpenAlex API

trangdata commented 2 years ago

Submitting Author Name: Trang Le Submitting Author Github Handle: !--author1-->@trangdata@massimoaria<!--end-author-others-- Repository: https://github.com/massimoaria/openalexR Submission type: Pre-submission Language: en

Paste the full DESCRIPTION file inside a code block below:

Type: Package
Package: openalexR
Title: Getting Bibliographic Records from 'OpenAlex' Database Using 'DSL'
    API
Version: 1.0.1
Authors@R: c(
    person(given = "Massimo",
           family = "Aria",
           role = c("aut", "cre", "cph"),
           email = "aria@unina.it",
           comment = c(ORCID = "0000-0002-8517-9411")),
    person(given = "Corrado",
           family = "Cuccurullo",
           role = c("ctb"),
           email = "cuccurullocorrado@gmail.com",
           comment = c(ORCID = "0000-0002-7401-8575")),       
    person(given = "Trang",
           family = "Le",
           role = "aut",
           email = "grixor@gmail.com",
           comment = c(ORCID = "0000-0003-3737-6565"))
    )
Description: A set of tools to extract bibliographic content from
    'OpenAlex' database using API <https://docs.openalex.org/api/>.
License: MIT + file LICENSE
URL: https://github.com/massimoaria/openalexR,
    https://massimoaria.github.io/openalexR/
BugReports: https://github.com/massimoaria/openalexR/issues
Imports: 
    curl,
    httr,
    jsonlite,
    progress,
    tibble
Suggests: 
    testthat (>= 3.0.0),
    dplyr,
    knitr,
    rmarkdown,
    tidyr,
    purrr,
    ggplot2,
    covr
VignetteBuilder: 
    knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
Config/testthat/edition: 3
Depends: 
    R (>= 2.10)

Scope

Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):

Data Lifecycle Packages
- [x] data retrieval
- [ ] data extraction
- [ ] data munging
- [ ] data deposition
- [ ] data validation and testing
- [ ] workflow automation
- [ ] version control
- [ ] citation management and bibliometrics
- [ ] scientific software wrappers
- [ ] field and lab reproducibility tools
- [ ] database software bindings
- [ ] geospatial data
- [ ] text analysis
  
  Statistical Packages
- [ ] Bayesian and Monte Carlo Routines
- [ ] Dimensionality Reduction, Clustering, and Unsupervised Learning
- [ ] Machine Learning
- [ ] Regression and Supervised Learning
- [ ] Exploratory Data Analysis (EDA) and Summary Statistics
- [ ] Spatial Analyses
- [ ] Time Series Analyses
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of: The package interacts with the OpenAlex API. Similar packages in the same category are rcrossref and rotl.
If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package? N/A
Who is the target audience and what are scientific applications of this package?
Anyone who wants to work in R to interact with the OpenAlex API to acquire information on publications, authors, etc., including researchers in the field of bibliometrics, text mining, etc. We including some nice example analyses in our README.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category? There are a couple of packages that we're aware of: https://github.com/KTH-Library/openalex and https://github.com/ekmaloney/openalexR. We think our package strikes the balance of complexity/flexibility, follow best API package practices, and offer additional useful functionality such as snowball search.
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research? Yes.
Any other questions or issues we should be aware of?: None.

adamhsparks commented 2 years ago

Hi @trangdata, could you give us a more detailed comparison of the packages' overlap?

Here's an example of a previous inquiry for another package that had some overlap. https://github.com/ropensci/software-review/issues/199#issuecomment-375358362

trangdata commented 2 years ago

Hi @adamhsparks thank you so much for your time! 🙏🏽 The example comparison is very helpful!

Quick Q: is the overlap analysis for within the ropensci packages like in the case of scrubr and CoordinateCleaner (of which there is not one similar ropensci package that I'm aware of), or do you mean the overlap between what we have and KTH-Library/openalex and ekmaloney/openalexR?

adamhsparks commented 2 years ago

I mean the overlap between the packages that you cited as being similar.

trangdata commented 2 years ago

Thank you @adamhsparks for clarifying! 🌻

I'm showing a detailed table of comparison below. In short, our package shares some similarity with KTH-Library/openalex, but we offer additional functionalities such as snowball search. We also expose functions that are crucial for many use cases such as filtering for a particular set of works/authors/etc. and generally a more "canonical" and simpler way to construct the query (see example). Our package is actively maintained and well tested. We also have a lot fewer dependencies. Lastly, these other packages currently only live on GitHub and do not belong to any repository (RO, CRAN, or BioC).

We're confident we have satisfied three out of four criteria listed in the guideline's package overlap section. Let me know if there is anything you would like me to elaborate on. 🌈

Table of comparison

Type	Property	massimoaria/openalexR	KTH-Library/openalex	ekmaloney/openalexR
Metadata	last commit	11 days ago	8 months ago	9 months ago
Metadata	# vignettes	4	0	0
Metadata	# readme examples	10	1	4
Metadata	test coverage	89%	N/A	N/A
Metadata	# commits	198	7	20
Metadata	# pull requests	17	0	0
Metadata	# stars	26	8	7
Metadata	license	MIT	MIT	MIT
Metadata	Imports	curl, httr, jsonlite, progress, tibble	httr, magrittr, utils, dplyr, purrr, progress, jsonlite, tibble	magrittr, dplyr, httr, jsonlite, purrr, tidyr, stringr, tibble
Function	request data from query	oa_request	openalex_crawl	openalex_api
Function	enter polite pool	openalexR.mailto	openalex_polite
Function	generate a valid query	oa_query	openalex_query	construct_links
Function	converts the JSON object in classical bibliographic tibble	oa2df	openalex_flatten_long	clean_author_info, clean_venue_info, clean_works_info
Function	composes functions to ease data fetching	oa_fetch	N/A	find_work, find_author, find_institution, find_concept, find_venue
Function	display openalex attribution		openalex_attribution
Function	snowballing	oa_snowball
Function	convert works to bibliometrix object	oa2bibliometrix
Function	get random entity	oa_random
Function	simplify works result	show_works
Function	simplify authors result	show_authors
Function	available entities in the OpenAlex database	oa_entities
Function	get papers for a particular author	oa_fetch (see example)	openalex_flatten_long (see example)	get_authors_papers
Function	get coauthors for a particular author			get_coauthors
Function	other functions, unknown use case			get_links_for_each_page, get_number_of_pages, get_all_data_for_query
Data	list of countries and their alpha-2 and aplha-3 codes	countrycode
Data	0-level concepts and corresponding abbreviations	concept_abbrev

Example

Getting a dataframe of papers published in 2022 by a specific author.

Our way

oa_fetch(
  "works",  
  authors.orcid = "0000-0002-8517-9411", 
  publication_year = 2022
)

KTH-Library/openalex's way:

openalex_flatten_long(openalex_crawl(
  "works", 
  query = openalex:::openalex_query(
    filter = "authors.orcid:0000-0002-8517-9411,publication_year:2022"
  )
))

ekmaloney/openalexR's way:

Not available. The package doesn't allow for filtering by publication_year.

trangdata commented 2 years ago

Hi @adamhsparks — just wanted to float this up on your list. I'm excited to get the package to ropensci and start the review process. Let me know if there is anything else that you need from me, or if there is anything from the presubmission guide that I should highlight. Thank you again for your time! 🪴

annakrystalli commented 2 years ago

Hello @trangdata ! 👋🙂

I can confirm that the editorial team feel the package is eligible for submission 🎉

Feel free to open a full submission issue. Let me know if you have any further questions.

trangdata commented 2 years ago

That's great news! 🥳 Thank you so much @annakrystalli, @adamhsparks and team! Please feel free to close this issue when ready.

adamhsparks commented 2 years ago

Thanks, @trangdata and @annakrystalli. I'll hand everything over to @annakrystalli as the incoming EIC.

ropensci / software-review