nasapower

[adamhsparks]

Summary

• What does this package do? (explain in 50 words or less):

nasapower automates downloading NASA-POWER agroclimatology data in your R
session as a tidy data frame for analysis, modelling or other purposes by interfacing with the NASA POWER API. POWER (Prediction Of Worldwide Energy Resource) data are freely available for download through a web interface at a resolution of 0.5˚ longitude by 0.5˚ latitude.

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

Package: nasapower
Type: Package
Title: NASA-POWER Data from R
Version: 1.0.0.9000
Authors@R: person(given = "Adam H.", family = "Sparks",
    role = c("aut", "cre"), email = "adamhsparks@gmail.com",
    comment = c(ORCID = "0000-0002-0061-8359"))
URL: https://github.com/adamhsparks/nasapower
BugReports: https://github.com/adamhsparks/nasapower/issues
Description: Download NASA-POWER global meteorology and surface solar energy
    climatology data and create a tidy data frame for 141 parameters.  nasapower
    provides an interface to the NASA - POWER API.  POWER (Prediction Of
    Worldwide Energy Resource) data are freely available for download with a
     resolution of 0.5 by 0.5 arc degree longitude and latitude and are funded
    through the NASA Earth Science Directorate Applied Science Program. For more
    on the data themselves, please see <https://power.larc.nasa.gov/>.
Depends:
    R (>= 3.2.0)
License: MIT + file LICENSE
Imports:
    crul,
    lubridate,
    jsonlite,
    readr,
    tibble
RoxygenNote: 6.0.1
Roxygen: list(markdown = TRUE)
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
LazyData: TRUE
ByteCompile: TRUE
Suggests:
    APSIM,
    covr,
    dplyr,
    ggplot2,
    knitr,
    raster,
    rmarkdown,
    testthat,
    vcr
VignetteBuilder: knitr
X-schema.org-applicationCategory: Tools
X-schema.org-keywords: NASA, meteorological-data, weather, global, weather, weather-data, meteorology, NASA-POWER, agroclimatology, earth-science, data-access

• URL for the package (the development repository, not a stylized html page):

https://github.com/adamhsparks/nasapower

• Please indicate which category or categories from our package fit policies this package falls under *and why(? (e.g., data retrieval, reproducibility. If you are unsure, we suggest you make a pre-submission inquiry.):

data retrieval and extraction, nasapower automates downloading and parsing
NASA - POWER data into a useful format in R using the POWER API.

• Who is the target audience?

Researchers who use NASA - POWER for modelling or other purposes though there may
be others that I'm not familiar with. This is the audience I know best since
I'm part of it and use these data for my own work.

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

Since the POWER API is brand new, no. This is the first R package to utilise it's capabilities.

Requirements

Confirm each of the following by checking the box. This package:

• does not violate the Terms of Service of any service it interacts with.
• has a CRAN and OSI accepted license.
• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions.
• contains a vignette with examples of its essential functions and uses.
• has a test suite.
• has continuous integration, including reporting of test coverage, using services such as Travis CI, Coeveralls and/or CodeCov.
• I agree to abide by ROpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

Publication options

• Do you intend for this package to go on CRAN?
• Do you wish to automatically submit to the Journal of Open Source Software? If so:
  • The package has an obvious research application according to JOSS's definition.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI:
  • (Do not submit your package separately to JOSS)

Detail

• Does R CMD check (or devtools::check()) succeed? Paste and describe any errors or warnings:

• Does the package conform to rOpenSci packaging guidelines? Please describe any exceptions:

• If possible, please provide recommendations of reviewers - those with experience with similar packages and/or likely users of your package - and their GitHub user names:

I've picked on everyone I can think of previously for other submissions.

[adamhsparks]

I was looking at the POWER website. The most, but not all, of the other POWER datasets have similar interfaces. It should be pretty simple add some of the Renewable Energy and Sustainable Buildings data to the package as well. I've just never used them for my work. It would be good if these were added, that someone with some knowledge of them could provide some assistance on what's useful.

Happy to get feedback on that.

[sckott]

Thanks @adamhsparks - Editors are discussing ...

[sckott]

Editor checks:

• Fit: The package meets criteria for fit and overlap
• Automated tests: Package has a testing suite and is tested via Travis-CI or another CI service.
• License: The package has a CRAN or OSI accepted license
• Repository: The repository link resolves correctly
• Archive (JOSS only, may be post-review): The repository DOI resolves correctly
• Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

---

Editor comments

Thanks for your submission @adamhsparks

Goodpractice output:

── 0 errors ✔ | 0 warnings ✔ | 0 notes ✔
♥ Aha! Astounding package! Keep up the best work!

Seeking reviewers now.

---

Reviewers: @alisonboyer @UniversalTourist
Due date: 2017-12-06

[sckott]

Reviewers are @alisonboyer and @UniversalTourist - due date is 2017-12-06

[UniversalTourist]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• A statement of need clearly stating problems the software is designed to solve and its target audience in README
• Installation instructions: for the development version of package and any non-standard dependencies in README
• Vignette(s) demonstrating major functionality that runs successfully locally
• Function Documentation: for all exported functions in R help
• Examples for all exported functions in R Help that run successfully locally
• Community guidelines including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

For packages co-submitting to JOSS

• The package has an obvious research application according to JOSS's definition

The package contains a paper.md matching JOSS's requirements with:

• A short summary describing the high-level functionality of the software
• Authors: A list of authors with their affiliations
• A statement of need clearly stating problems the software is designed to solve and its target audience.
• References: with DOIs for all those that have one (e.g. papers, datasets, software).

Functionality

• Installation: Installation succeeds as documented.
• Functionality: Any functional claims of the software been confirmed.
• Performance: Any performance claims of the software been confirmed.
• Automated tests: Unit tests cover essential functions of the package
  and a reasonable range of inputs and conditions. All tests pass on the local machine.
• Packaging guidelines: The package conforms to the rOpenSci packaging guidelines

Final approval (post-review)

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

Estimated hours spent reviewing: It took almost, totally, 4-5 hours to check everything. During that time I studied what is NASA-POWER, agroclimatology and read rOpenSci guidelines, learned about Travis-CI and running tests.

---

Review Comments

This is the first time I heard about NASA-POWER and it is a great data source for Earth scientists. These package provides a data frame output and it will make the data preparation process more easier than copy-pasting.
(I have tested functions for region of my country and already sent the package's Github link for my colleges :) )

• Installation:
  With MacOS:
  I used macOS Sierra, Verison 10.12 and I was able to install the package from Github without any problem by devtools.

• Code Overall:
  These package has two functions to get data for a cell or for a region. Both functions has nice structered, easy to follow and also nice explained with comments, I enjoyed reviewing this part especially. (I also learned about how httr works by running these codes step by step.)

• rOpenSci criteria:
  Package name is really nice. Function and variable naming is proper. Licence and Code of Conduct are available.

• Readme:
  Readme.rmd is clear and easy to follow steps for installations.

• Vignette:
  There are more details and examples about other function. Also the examples provide more information and help to illustrate the importance of the package.
  In the introduction part there is only one mistake, the "which will" words are written for two times: "both of which will which will download".
  I notified author about plots on vignette which seems different when I run on my system, and problem was resolved with a commit fastly when I contacted with the author.

• Errors and console messages:
  They are all clear.

• R CMD check:
  R CMD check passes without any warnings or any errors.

• 0 errors | 0 warnings | 0 notes
  :)

• Other comments
  NASA-POWER provides data at a resolution of 1˚ longitude by 1˚ latitude, which is good enough most of the time. Maybe you can also write about other data sources which provide higher resolutions in the package readme file for the people who come to this package repo for higher resolution.

p.s This is my first time at reviewing a package and I hope I can be helpful :)