• 1. What does this package do? This page wraps the Tabula Java library, which can (very accurately) extract tables from PDF documents. It also implements some lower level utilities for working with PDF documents (metadata and text extraction, image conversion, split/merge). It should be useful for extracting scientific data, especially tabular data, from PDFs, such as from scientific articles or agency reports.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: tabulizer
Type: Package
Title: Bindings for Tabula PDF Table Extractor Library
Version: 0.1.11
Date: 2016-05-07
Authors@R: c(person("Thomas J.", "Leeper", role = c("aut", "cre"),
                    email = "[email protected]"))
Maintainer: Thomas J. Leeper <[email protected]>
Description: Bindings for the Tabula <http://tabula.technology/> java library, which can extract tables from PDF documents.
License: MIT + file LICENSE
URL: https://github.com/leeper/tabulizer
BugReports: https://github.com/leeper/tabulizer/issues
Imports:
    graphics,
    grDevices,
    utils,
    tools,
    tabulizerjars,
    rJava,
    png
Suggests:
    testthat,
    knitr
RoxygenNote: 5.0.1

• 3. URL for the package (the development repository, not a stylized html page) https://github.com/leeper/tabulizer
• 4. What data source(s) does it work with (if applicable)? n/a
• 5. Who is the target audience? Data scientists stuck with other peoples' data
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours? The closest thing will be pdftools, which is a libpoppler wrapper. tabulizer has some overlap but the core functionality - table extraction - is not supported by pdftools.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • [] Are there any package dependencies not on CRAN? The package has some files in a dependent package, which can be put on CRAN once everything is ready to release.
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

Who has/will contribute to this package?

Do we really need a will contribute part at this stage? Why does this matter now?

Are you willing to follow the rOpenSci policies (link), including transferring your repo to the rOpenSci GitHub organization account?

Can we list concrete things to check off here?

Are you willing to follow the [rOpenSci packaging guidelines](https://github.com/ropensci/packaging_guide? If you have disagreements with them, explain.

This seems like a rather big question for a binary answer. I'm not even sure most current rOpenSci packages can safely answer yes to those. Should we break those down here?

https://twitter.com/JennyBryan/status/584243412682944512

or perhaps the style guide?

following slack discussion...

to add to https://github.com/ropensci/onboarding/blob/master/packaging_guide.md

• 1. What does this package do? (explain in 50 words or less)
     This package brings together a number of tools that enable transport modelling and planning and R, with an emphasis on analyses needed for sustainability (e.g. planning new bicycle paths).
• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: stplanr
Type: Package
Title: Sustainable Transport Planning with R
Version: 0.0.1.1
Date: 2015-10-18
Authors@R: c(
    person("Robin", "Lovelace", email = "[email protected]", role = c("aut", "cre")),
    person("Richard", "Ellison", role = c("aut"), comment = "Author of various functions"),
    person("Barry", "Rowlingson", role = c("aut"), comment = "Author of overline"),
    person("Nick", "Bearman", role = c("aut"), comment = "Co-author of gclip")
    )
Description: Functionality and data access tools for transport planning, including origin-destination analysis, route allocation and modelling travel patterns.
License: MIT + file LICENSE
BugReports: https://github.com/robinlovelace/stplanr/issues
LazyData: yes
Depends:
    sp, R (>= 3.0)
Imports:
    jsonlite,
    maptools,
    raster,
    rgdal,
    rgeos,
    dplyr,
    RgoogleMaps,
    openxlsx,
    leaflet,
    httr
Suggests:
    testthat,
    knitr,
    tmap
VignetteBuilder: knitr
URL: https://github.com/Robinlovelace/stplanr

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/Robinlovelace/stplanr
• 4. What data source(s) does it work with (if applicable)?
     Example data on route allocation and travel flows (included - more planned), geographical boundaries, transport networks, example travel survey data (to be added subsequently)
• 5. Who is the target audience?
     Transport researchers and modellers from academic, public and private sectors. University students studying transport geography, transport modelling and related disciplines.
• 6. Check the box next to each policy below, confirming that you agree. These are mandatory.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• 7. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Are there any packages that your package depends on that are not on CRAN?
• Do you intend for this package to go on CRAN?
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
• 1. Please add explanations below for any exceptions to the above:
     This is work in progress and I am learning how to build R packages as I progress. These issues will be fixed, probably during a course on R package development I will attend.
• 9. If this is a resubmission following rejection, please explain the change in cirucmstances.

https://github.com/ropensci/onboarding/blame/5f4644d4a048c5fa7b3e42f74cd655ea35d5b405/packaging_guide.md#L54-Lundefined

• See devtools::use_readme_rmd() to get a template for a README.Rmd file in your package.
• Consider setting up pre-commit hooks to ensure that README.md is always newer than README.Rmd (see devtools::use_git_hook)

The second bullet might be unnecessary and is possibly confusing. devtools::use_readme_rmd() adds the necessary pre-commit hook.

• 1. What does this package do? (explain in 50 words or less)
     It provides an interface to the OpenAQ API. OpenAQ provides open air quality data for many locations around the world, whose number is growing. The R package allows to check data availability and to download measurements from R as a dplyr data.table.
• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: Ropenaq
Type: Package
Title: The Package is a R Interface to the openaq API
Version: 0.1
Date: 2015-12-30
Author: Maëlle Salmon
Maintainer: Who to complain to <[email protected]>
Description: See https://docs.openaq.org/
License: GPL (version 2 or later)
LazyData: TRUE
RoxygenNote: 5.0.1
URL: http://github.com/masalmon/Ropenaq
BugReports: http://github.com/masalmon/Ropenaq/issues
Suggests: knitr,
    rmarkdown
VignetteBuilder: knitr
Depends: httr, lubridate, dplyr, testthat, XML

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/masalmon/Ropenaq
• 4. What data source(s) does it work with (if applicable)?
     Open AQ https://openaq.org/#/
• 5. Who is the target audience?
     People that need air quality data for their studies and do not know how to access the API, or want to do the analysis in R anyway. They could be e.g. epidemiologists. I think that if the R package has users, the Open AQ platform will also get more attention and thus get even more data sources.
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     No, this is the first and only R package for accessing the OpenAQ API (I first asked one of the OpenAQ co-founders)
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
• [x ] This package does not violate the Terms of Service of any service it interacts with.
• [ x] The repository has continuous integration with Travis and/or another service
• [ x] The package contains a vignette
• [ x] The package contains a reasonably complete readme with devtools install instructions
• [x ] The package contains unit tests
• [ x] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
     Yes, as much as I can.
• Are there any package dependencies not on CRAN?
• [ x] Do you intend for this package to go on CRAN?
  When it is more developped, yes, it could be usefool.
• [ x] Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in cirucmstances.

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

  The data package of the DoOR project. The data package provides all published odor responses recorded from olfactory sensory neurons of the fruit fly Drosophila.

• 1. Paste the full DESCRIPTION file inside a code block below.

Package: DoOR.data
Type: Package
Title: Integrating Heterogeneous Odorant Response Data into a Common Response
    Model: A DoOR to the Complete Olfactome
Version: 2.0.0
Date: 2016-02-25
Authors@R: c(
    person("Daniel", "Münch", email = "[email protected]", role = c("aut", "cre")),
    person("C. Giovanni", "Galizia", email = "[email protected]", role = "aut"),
    person("Shouwen", "Ma", role = "aut"),
    person("Martin", "Strauch", role = "aut"),
    person("Anja", "Nissler", role = "aut"))
URL: http://neuro.uni-konstanz.de/DoOR
BugReports: https://github.com/Dahaniel/DoOR.data/issues
Description: This is a data package providing Drosophila odorant response data for
    DoOR.functions. See http://dx.doi.org/10.1093/chemse/bjq042 for the original
    publication and http://dx.doi.org/10.1038/srep21841 regarding version 2.0.
License: CC BY-SA 4.0
Encoding: UTF-8
Imports:
    utils
Depends:
    R (>= 3.2.0)
Suggests:
    DoOR.functions (>= 2.0.0)
Remotes:
    Dahaniel/[email protected]
RoxygenNote: 5.0.1

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

https://github.com/Dahaniel/DoOR.data

• 4. What data source(s) does it work with (if applicable)?

The package itself provides the data either extracted from publications or provided by the publication authors.

• 5. Who is the target audience?

Scientists working on olfactory coding, modelers and physiologists.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

No, to our knowledge DoOR is the only project providing this kind of data and using this approach to integrate heterogeneous data.

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN? - no
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below. - no
• 1. Please add explanations below for any exceptions to the above:
  • The package does not contain a vignette as it only provides data. All the functionality is comprehensively explained in the vignettes in the corresponding data package (see other onboarding).
  • I think unit tests do not make much sense here as the package solely provides data.
  • Travis has problems as the DoOR.data package suggests the DoOR.functions package. Adding DoOR.functions to "Remotes:" did not help as it depends on DoOR.data...
• 1. If this is a resubmission following rejection, please explain the change in circumstances.

• 1. What does this package do? (explain in 50 words or less)
     This package allows to get METAR reports (weather reports) through the Iowa Environment Mesonet https://mesonet.agron.iastate.edu/request/download.phtml?network=IN__ASOS
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: riem
Type: Package
Title: Accesses Data from the Iowa Environment Mesonet
Version: 0.1.0
Authors@R: person("Maëlle", "Salmon", email = "[email protected]", role =
    c("aut", "cre"))
Description: Allows to get weather data from ASOS stations (airports) in the
    whole world thanks to the Iowa Environment Mesonet website.
License: GPL (>= 2)
LazyData: TRUE
Imports:
    httr,
    lubridate,
    dplyr,
    jsonlite,
    readr,
    lazyeval
RoxygenNote: 5.0.1
Suggests: testthat,
    knitr,
    rmarkdown
VignetteBuilder: knitr

• 3. URL for the package (the development repository, not a stylized html page)
  https://github.com/masalmon/riem
• 4. What data source(s) does it work with (if applicable)?
     Iowa Environment Mesonet https://mesonet.agron.iastate.edu/request/download.phtml?network=IN__ASOS
• 5. Who is the target audience?
     Anyone needing weather data
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     The R package wunderground allows to access weather data including ASOS stations but the API only allows a linited number of calls per day/minute.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [x ] This package does not violate the Terms of Service of any service it interacts with.
  • [ x] The repository has continuous integration with Travis CI and/or another service
  • [ x] The package contains a vignette
  • [ x] The package contains a reasonably complete README with devtools install instructions
  • [ x] The package contains unit tests
  • [ x] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • [x ] Do you intend for this package to go on CRAN?
  • [ x] Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

• 1. What does this package do? (explain in 50 words or less)
     Parses GenBank and GenPept files into a useful datastructure which integrates with the Bioconductor ecosystem.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: genbankr
Version: 1.1.3
Title: Parsing GenBank files into semantically useful objects
Description: Reads Genbank files.
Authors@R: as.person(c(
      "Gabriel Becker <[email protected]> [aut, cre]",
      "Michael Lawrence <[email protected]> [aut]"))
Copyright: Genentech, Inc.
Depends:
    methods
Imports:
    BiocGenerics,
    IRanges,
    GenomicRanges(>= 1.23.24),
    GenomicFeatures,
    Biostrings,
    VariantAnnotation,
    rtracklayer,
    S4Vectors,
    GenomeInfoDb,
    Biobase
Suggests:
    RUnit,
    rentrez,
    knitr
Maintainer: Gabriel Becker <[email protected]>
VignetteBuilder: knitr
License: Artistic-2.0
RoxygenNote: 5.0.1.9000
biocViews: Infrastructure, DataImport
NeedsCompilation: no

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/gmbecker/genbankr
• 4. What data source(s) does it work with (if applicable)?
     NCBI Nucleotide and Protein databases (GenBank and GenPeptfiles)
• 5. Who is the target audience?
     Scientists working on microbial genomics/bioinformatics, on organisms for which NCBI and GenBank are the source of record for annotations.
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     The rentrez package offers low level querying facilities for all NCBI databases, but does not parse the results into a semantically useful datastructure in the GenBank/GenPept case. I view genbankr as working with rentrez rather than replacing it. In fact, when users give an accession rather than an already downloaded file, rentrez is used to retrieve the raw data, which is then parsed by genbankr machinery.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
     This package is part of the Bioconductor package platform and depends on Bioconductor packages as well as CRAN packages. All dependencies are published in either CRAN or Bioconductor.

This package will not go on CRAN, as it is and will continue to be published as a Bioconductor package (with ROpenSci co-branding, pending success of this submission).

• 10. If this is a resubmission following rejection, please explain the change in circumstances.

• 1. What does this package do? (explain in 50 words or less)
     The assertr package supplies a suite of functions designed to verify assumptions about data early in an analysis pipeline to protect against common data errors and instances of bad data.
• 1. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: assertr
Type: Package
Title: Assertive Programming for R Analysis Pipelines
Version: 1.0.0
Authors@R: person("Tony", "Fischetti", email="[email protected]",
  role = c("aut", "cre"))
Maintainer: Tony Fischetti <[email protected]>
Description: Provides functionality to assert conditions
    that have to be met so that errors in data used in
    analysis pipelines can fail quickly. Similar to
    'stopifnot()' but more powerful, friendly, and easier
    for use in pipelines.
URL: https://github.com/tonyfischetti/assertr
BugReports: https://github.com/tonyfischetti/assertr/issues
License: MIT + file LICENSE
LazyData: TRUE
Imports:
    dplyr,
    MASS,
    lazyeval
Suggests:
    knitr,
    testthat,
    magrittr
VignetteBuilder: knitr

• 1. URL for the package (the development repository, not a stylized html page)
     https://github.com/tonyfischetti/assertr
• 1. What data source(s) does it work with (if applicable)?
     Any. Mostly in the form of data.frames
• 1. Who is the target audience?
     Anyone who has ever struggled with bad data
• 1. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     The ensurer package attempts to solve the very same problem. To a certain extent, the assertive package also offer some similar capabilities. The difference between assertr and these other packages is the grammar of usage and the way that assertions of different types can be easily combined to express arbitrarily complex assertions in a very readable way.
• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
     Yes. All the user-facing functions are in snake case, but the internal functions sometimes use dots (.) as separators. I'm open to changing that. Also, the package doesn't have a code of conduct yet but I think it's a good idea to include.
• Are there any package dependencies not on CRAN?
  No
• Do you intend for this package to go on CRAN?
  It already is
• Does the package have a CRAN accepted license?
  You bet
• Did devtools::check() produce any errors or warnings? If so paste them below.
  No warnings
• 1. Please add explanations below for any exceptions to the above:
• 1. If this is a resubmission following rejection, please explain the change in cirucmstances.

via https://discuss.ropensci.org/t/ropensci-onboarding-package-fit/391/2

add note to instructions for submitters that they can open an issue if they are not sure if their pkg is a good fit

• 1. What does this package do? (explain in 50 words or less)
     This package is an interface to the opencage API (free account: 2500 calls/day). It allows forward geocoding (from placename to lat/lon) and reverse geocoding (vice versa). The API has many data sources.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: opencage
Type: Package
Title: Interface To The OpenCage API
Version: 0.1.0
Authors@R: person("Maëlle", "Salmon", email = "[email protected]", role = c("aut", "cre"))
Description: This packages accesses the OpenCage API which provides Forward
    geocoding (from placename to longitude and latitude) and Reverse geocoding (from
    longitude and latitude to placename)
License: GPL (>= 2)
LazyData: TRUE
URL: http://github.com/masalmon/opencage
BugReports: http://github.com/masalmon/opencage/issues
Imports:
    httr,
    jsonlite,
    dplyr,
    lubridate,
    memoise
RoxygenNote: 5.0.1
Suggests: testthat, lintr

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/masalmon/opencage
• 4. What data source(s) does it work with (if applicable)?
     opencage website states "open geospatial data including OpenStreetMap, Yahoo! GeoPlanet, Natural Earth Data, Thematic Mapping, Ordnance Survey OpenSpace, Statistics New Zealand, Zillow, MaxMind, GeoNames, the US Census Bureau and Flickr's shapefiles plus a whole lot more besides."
• 5. Who is the target audience?
     People that need to geocode.
• 1. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     I know no function for reverse geocoding but for forward geocoding there's the geocode function in ggmap. "Geocodes a location (find latitude and longitude) using either (1) the Data Science Toolkit (http://www.datasciencetoolkit.org/about) or (2) Google Maps." However it has either Google Maps or Data Science Toolkit. opencage actually builds on other geocoders including Data Science Toolkit ("There's Nominatim, Data Science Toolkit and the Two Fishes geocoders." )
• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [ x] This package does not violate the Terms of Service of any service it interacts with.
  • [ x] The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • [ x] The package contains a reasonably complete README with devtools install instructions
  • [ x] The package contains unit tests
  • [ x] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • [ x] Do you intend for this package to go on CRAN?
  • [ x] Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:

The package does not have a vignette yet but it only has two functions with nearly the same arguments. However I agree that it might be good to show use cases, but since I don't geocode a lot in R, I need a bit of feedback about what applications are for users that really geocode.

• 10. If this is a resubmission following rejection, please explain the change in circumstances.

• Data on mergers, splits, and other changes of Swiss municipalities since 1960

Encoding: UTF-8
Package: SwissHistMunData
Title: Historicized Swiss Municipalities
Version: 0.0-1
Date: 2016-03-31
Authors@R: c(
    person("Kirill", "Müller", , "[email protected]", c("aut", "cre")),
    person("Swiss Federal Statistical Office (SFSO), Swiss Statistics Web site", role = "cph")
    )
Description: Contains historicized municipality data for Switzerland from 1960
    onwards, from the "Historisiertes Gemeindeverzeichnis" of the Swiss
    Federal Statistical Office.
Depends: R (>= 2.10)
Imports: tibble
Suggests:
    testthat,
    logging
License: GPL-3
LazyData: true
RoxygenNote: 5.0.1

• https://github.com/krlmlr/SwissHistMunData
• Downloads data from a fixed URL as part of its testing procedure (which also checks that data is up to date)
• Data required for the SwissCommunes package, whose purpose is to compute mappings between municipality codes for arbitrary points in time.
• No other packages AFAIK.
• Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• My first onboarding, I'd like to verify first that this package is a fit for rOpenSci.

• 1. What does this package do? (explain in 50 words or less)
     mregions is a wrapper to REST API methods from http://www.marineregions.org/ - with purpose of fetching marine regions in geojson/shp/wkt format for use downstream.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: mregions
Title: Marine Regions Data from Marineregions.org
Description: Tools to get marine regions data from Marineregions.org.
    Includes tools to get region metadata, as well as data in GeoJSON
    format, as well as Shape files.
Version: 0.0.9.9400
License: MIT + file LICENSE
Authors@R: c(
    person("Scott", "Chamberlain", role = c("aut", "cre"), email = "[email protected]"),
    person("Pieter", "Provoost", role = "aut")
    )
URL: https://github.com/ropenscilabs/mregions
BugReports: https://github.com/ropenscilabs/mregions/issues
Imports:
    httr (>= 1.1.0),
    jsonlite (>= 0.9.20),
    xml2,
    wellknown,
    rappdirs
Suggests:
    testthat,
    geojsonio,
    rgdal,
    rgeos,
    knitr
Enhances: leaflet
VignetteBuilder: knitr
RoxygenNote: 5.0.1

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/ropenscilabs/mregions
• 4. What data source(s) does it work with (if applicable)?
     REST API from http://www.marineregions.org/ and a geoserver API from a related service http://geo.vliz.be/geoserver/ows
• 5. Who is the target audience?
     Biologists/oceanographers/ecologists and anyone else wanting to overlay data, or clip data to, various defined marine regions
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     Not that I know of
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with instructions for installing the development version.
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN? No
  • Do you intend for this package to go on CRAN? Yes
  • Does the package have a CRAN accepted license? Yes
  • Did R CMD check (or devtools::check()) produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

• 1. What does this package do? (explain in 50 words or less)
     This package provides an interface to "rlite" - a standalone, zero-configuration port of the Redis interface (rlite is to Redis what sqlite is to MySQL).
• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: rrlite
Title: R bindings to rlite
Version: 0.1.0
Description: R bindings to rlite.  rlite is a "self-contained,
  serverless, zero-configuration, transactional redis-compatible
  database engine. rlite is to Redis what SQLite is to SQL.".
Depends: R (>= 3.1.2)
License: BSD_2_clause + file LICENSE
LazyData: true
Author: Rich FitzJohn
Maintainer: Rich FitzJohn <[email protected]>
Suggests: testthat,
    knitr,
    RcppRedis
Imports: R6, Rcpp
LinkingTo: Rcpp
VignetteBuilder: knitr
SystemRequirements: GNU make

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/richfitz/rrlite
• 4. What data source(s) does it work with (if applicable)?
     User-supplied, but arbitrary. Special support for data.frames. No direct support for existing remote data sources.
• 5. Who is the target audience?
     Package developers, technically minded users who need to process large data or scale analyses. This is a low-level package.
• 6. Check the box next to each policy below, confirming that you agree. These are mandatory.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• 7. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Are there any packages that your package depends on that are not on CRAN?
• Do you intend for this package to go on CRAN?
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.

* checking for executable files ... WARNING
Found the following executable files:
  src/rlite/deps/lua/src/lua
  src/rlite/deps/lua/src/luac

(this can be fixed by uncommenting the cleanup script but that slows down local development and I've not worked out a good workflow there. Rbuildignore has proved difficult to use for this).

• 8. Please add explanations below for any exceptions to the above:
     Not covered in the requested information, but in it's current state, the package is highly unlikely to work under Windows. I'm holding off attempting with R this until the upstream rlite is confirmed to work. Once that's done, this package would definitely want appveyor support to ensure continued Windows compatibility.

• 1. What does this package do? (explain in 50 words or less)
     This package is an interface to the geoparser.io API that identifies places mentioned in text, disambiguates those places, and returns data about the places found in the text.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: geoparser
Type: Package
Title: Interface to the Geoparser.io API
Version: 0.1.0
Authors@R: person("Maëlle", "Salmon", email = "[email protected]", role = c("aut", "cre"))
Description: This packages accesses the Geoparser.io API which is a web service
    that identifies places mentioned in text, disambiguates those places, and
    returns detailed data about the places found in the text.
License: GPL (>= 2)
LazyData: TRUE
URL: http://github.com/masalmon/geoparser
BugReports: http://github.com/masalmon/geoparser/issues
Encoding: UTF-8
RoxygenNote: 5.0.1
Suggests: testthat,
    knitr,
    rmarkdown
Depends: dplyr, httr, jsonlite, lazyeval, tidyr
VignetteBuilder: knitr

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/masalmon/geoparser
• 4. What data source(s) does it work with (if applicable)?
     The geoparser.io API which is version beta. They said "We expect it to remain largely the same for the immediate future. We'd try to make any changes backwards compatible, and support older versions of the API for an extended period of time to allow users to migrate at their convenience. However, the most likely things to change are:
  5. The possible values for Feature.properties.type in the GeoJSON response data
  6. How we calculate values for Feature.properties.confidence in the GeoJSON response data
  7. The endpoint URI for the API itself"
• 5. Who is the target audience?
     People interested in Natural Language Processing, or anyone with text where they would like to identify geographical information.
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     I don't think so. Named Entity Recognition (including placenames) in R is currently offered by the openNLP package that requires Java but then the results are not geolocated.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [x ] This package does not violate the Terms of Service of any service it interacts with.
  • [ x] The repository has continuous integration with Travis CI and/or another service
  • [ x] The package contains a vignette
  • [ x] The package contains a reasonably complete README with devtools install instructions
  • [ x] The package contains unit tests
  • [ x] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • [ x] Do you intend for this package to go on CRAN?
  • [ x] Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

so I don't lose track of these (pkgs of people interested in submitting here when we're ready):

stplanr, FredR, driver, rsdmx, rusda

Summary

• What does this package do? (explain in 50 words or less):
• Paste the full DESCRIPTION file inside a code block below:

• URL for the package (the development repository, not a stylized html page):
• Who is the target audience?
• Are there other R packages that accomplish the same thing? If so, what is different about yours?

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.
• only exports functions to the NAMESPACE that are intended for end users
• has a test suite
• has continuous integration with Travis CI and/or another service
• contains a vignette with examples of its essential functions and uses
• contains a README with instructions for installing the development version.
• has a CRAN and OSI accepted license.

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?
  • The package contains a paper.md with a high-level description.
  • The package is deposited in a long-term repository with the DOI:

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 this is a resubmission following rejection, please explain the change in circumstances:

• 1. What does this package do?

Allows for automated geospatial querying and downloading of raw data from several federated databases.

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: FedData
Type: Package
Title: Functions to Automate Downloading Geospatial Data Available from Several Federated Data Sources
Version: 1.1.0
Date: 2015-05-06
Author: R. Kyle Bocinsky <[email protected]>
    Dylan Beaudette <[email protected]>
Maintainer: R. Kyle Bocinsky <[email protected]>
Description: Functions to automate downloading geospatial data available from several federated data sources (mainly sources maintained by the US Federal government). Currently, the package allows for retrieval of five datasets: The National Elevation Dataset digital elevation models (1 and 1/3 arc-second; USGS); The National Hydrography Dataset (USGS); The Soil Survey Geographic (SSURGO) database from the National Cooperative Soil Survey (NCSS), which is led by the Natural Resources Conservation Service (NRCS) under the USDA; the Global Historical Climatology Network (GHCN), coordinated by National Climatic Data Center at NOAA; and the International Tree Ring Data Bank. Additional data sources are in the works, including global DEM resources (ETOPO1, ETOPO5, ETOPO30, SRTM), global soils (HWSD), MODIS satellite data products, the National Atlas (US), Natural Earth, PRISM, and WorldClim.
License: GPL-3
Depends: R (>= 3.1.0), sp, rgdal, raster, RCurl
Imports: rgeos, igraph, data.table, devtools, soilDB
Suggests: SSOAP, XMLSchema
Repository: CRAN
Additional_repositories: http://www.omegahat.org/R
NeedsCompilation: no

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

https://github.com/bocinsky/FedData

• 4. What data source(s) does it work with (if applicable)?

The National Elevation Dataset (USGS), National Hydrography Dataset (USGS), SSURGO soils database (USGS), Global Historical Climatology Network (NOAA), and the International Tree Ring Databank (NOAA).

• 5. Who is the target audience?

Researchers, government employees/land-managers, and anyone else interested in accessing these databases.

• 6. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• [?] The repository has continuous integration with Travis and/or another service
• [?] The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• [?] The package contains unit tests
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• [...] Are there any package dependencies not on CRAN?
  Two not on CRAN, but available from http://www.omegahat.org/R.
• [YES] Do you intend for this package to go on CRAN?
• [YES] Does the package have a CRAN accepted license?
• [NO] Did devtools::check() produce any errors or warnings? If so paste them below.
• 1. Please add explanations below for any exceptions to the above:

I'm a fairly novice programmer, so [as far as I know] I don't use Travis CI or unit tests. I've not yet written a vignette (it's on my to-do list).

• 9. If this is a resubmission following rejection, please explain the change in cirucmstances.

I think others have suggested FedData to rOpenSci, but the latest version is far more stable and platform-agnostic.

@sckott @richfitz
Tell me if this idea is too complicated. Instead of a user coming over to the repo, then copying a block of text into a new issue and editing in place, how about we do this programmatically? We can write a really lightweight package that wraps the CLI for GitHub issues. Then from the working directory of a package (or passing the path) to something akin to devtools::release, a user does ropensci_contribute() (or something like that).

The function will read the description, extract author information, license, Travis integration, coveralls integration, vignette info etc. The remaining questions will be a wizard, just like devtools::release. At the end, all the information is formatted and an issue is programmatically pushed to the repo.

Perhaps too much (I am starting to think so) but just wanted to throw this ide out (perhaps for a later time).

```

• 1. What does this package do?
     An interface to the web service methods provided by the
     United States Department of Agriculture (USDA). The
     Agricultural Research Service (ARS) provides a large
     set of databases. The current version of the package
     holds interfaces to the Systematic Botany and Mycology
     Laboratory (SMML), which consists of four databases:
     Fungus-Host Distributions, Specimens, Literature and
     the Nomenclature database. It provides functions for
     querying these databases. The main function is
     \code{associations}, which allows searching for fungus-
     host combinations.
• 1. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: rusda
Type: Package
Title: Interface to USDA databases
Version: 1.0
Date: 2015-06-25
Author: Franz-Sebastian Krah
Maintainer: Franz-Sebastian Krah <[email protected]>
Imports: XML, httr, plyr, foreach, stringr
Description: An interface to the web service methods 
provided by the United States Department of Agriculture 
(USDA). The Agricultural Research Service (ARS) 
provides a large set of databases. The current version 
of the package holds interfaces to the Systematic 
Botany and Mycology Laboratory (SMML), which consists 
of four databases: Fungus-Host Distributions, 
Specimens, Literature and the Nomenclature database. It 
provides functions for querying these databases. The 
main function is \code{associations}, which allows 
searching for fungus-host combinations. 
License: GPL (>= 2)
URL: http://www.usda.gov/wps/portal/usda/usdahome, 
http://nt.ars-grin.gov/fungaldatabases/index.cfm

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/FranzKrah/rusda
• 4. What data source(s) does it work with (if applicable)?
     species vector (class: character)defined in R
• 5. Who is the target audience?
     Botanists; Mycologists; Plant pathologists; Plant protection; People interested in fungus-host interactions or associations;
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     No.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete readme with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
    Yes.
  • Does the package have a CRAN accepted license? No. First rOpenSci
  • Did devtools::check() produce any errors or warnings? If so paste them below.
    Updating rusda documentation
    Loading rusda
    First time using roxygen2 4.0. Upgrading automatically...
    '/Library/Frameworks/R.framework/Resources/bin/R' --no-site-file --no-environ --no-save --no-restore CMD
    build '/Users/test/Documents/R/pkgs/rusda' --no-resave-data --no-manual
• checking for file ‘/Users/test/Documents/R/pkgs/rusda/DESCRIPTION’ ... OK
• preparing ‘rusda’:
• checking DESCRIPTION meta-information ... OK
• checking for LF line-endings in source and make files
• checking for empty or unneeded directories
• building ‘rusda_1.0.tar.gz’

'/Library/Frameworks/R.framework/Resources/bin/R' --no-site-file --no-environ --no-save --no-restore CMD
check '/var/folders/js/s5k7qtzd1kz2pt9t2p11z7600000gn/T//RtmpopOjFp/rusda_1.0.tar.gz' --timings

• using log directory ‘/private/var/folders/js/s5k7qtzd1kz2pt9t2p11z7600000gn/T/RtmpopOjFp/rusda.Rcheck’
• using R version 3.2.0 (2015-04-16)
• using platform: x86_64-apple-darwin13.4.0 (64-bit)
• using session charset: UTF-8
• checking for file ‘rusda/DESCRIPTION’ ... OK
• checking extension type ... Package
• this is package ‘rusda’ version ‘1.0’
• checking package namespace information ... OK
• checking package dependencies ... OK
• checking if this is a source package ... OK
• checking if there is a namespace ... OK
• checking for executable files ... OK
• checking for hidden files and directories ... OK
• checking for portable file names ... OK
• checking for sufficient/correct file permissions ... OK
• checking whether package ‘rusda’ can be installed ... OK
• checking installed package size ... OK
• checking package directory ... OK
• checking DESCRIPTION meta-information ... OK
• checking top-level files ... NOTE
  Non-standard files/directories found at top level:
  ‘Readme.Rmd’ ‘Readme.html’
• checking for left-over files ... OK
• checking index information ... OK
• checking package subdirectories ... OK
• checking R files for non-ASCII characters ... OK
• checking R files for syntax errors ... OK
• checking whether the package can be loaded ... OK
• checking whether the package can be loaded with stated dependencies ... OK
• checking whether the package can be unloaded cleanly ... OK
• checking whether the namespace can be loaded with stated dependencies ... OK
• checking whether the namespace can be unloaded cleanly ... OK
• checking use of S3 registration ... OK
• checking dependencies in R code ... OK
• checking S3 generic/method consistency ... OK
• checking replacement functions ... OK
• checking foreign function calls ... OK
• checking R code for possible problems ... OK
• checking Rd files ... OK
• checking Rd metadata ... OK
• checking Rd line widths ... OK
• checking Rd cross-references ... OK
• checking for missing documentation entries ... OK
• checking for code/documentation mismatches ... OK
• checking Rd \usage sections ... OK
• checking Rd contents ... OK
• checking for unstated dependencies in examples ... OK
• checking examples ... OK
• checking PDF version of manual ... OK
• DONE

Status: 1 NOTE

• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in cirucmstances.

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

This package detects document similarity, and implements the minhash/lsh algorithms.

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: textreuse
Type: Package
Title: Detect Text Reuse and Document Similarity
Version: 0.0.1.9001
Date: 2015-09-17
Authors@R: c(person("Lincoln", "Mullen", role = c("aut", "cre"),
    email = "[email protected]"))
Description: Tools for measuring similarity among documents and detecting
    passages which have been reused. Implements shingled n-gram, skip n-gram,
    and other tokenizers; similarity/dissimilarity functions; pairwise
    comparisons; and minhash and locality sensitive hashing algorithms.
License: MIT + file LICENSE
LazyData: TRUE
URL: https://github.com/lmullen/textreuse
BugReports: https://github.com/lmullen/textreuse/issues
VignetteBuilder: knitr
Depends: R (>= 3.1.2)
Imports: assertthat (>= 0.1),
    digest(>= 0.6.8),
    hash (>= 2.2.6),
    NLP (>= 0.1.8),
    Rcpp (>= 0.12.0),
    stringr (>= 1.0.0)
Suggests: testthat (>= 0.10.0),
    knitr (>= 1.11),
    rmarkdown (>= 0.8)
LinkingTo: Rcpp,
    BH

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

https://github.com/lmullen/textreuse/

• 4. What data source(s) does it work with (if applicable)?

This package anticipates that the user has documents in plain text. Future versions could provide, for example, XML readers as the tm package does, but I think that probably does not belong in this package.

• 5. Who is the target audience?

Detecting document similarity is a common problem when working the natural language, so I anticipate that this package will be broadly useful for anyone working in NLP.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

No, there are no other R packages that implement minhash/locality-sensitive hashing. The tm package does implement some document similarity measures, but these are similarity in terms of content rather than in terms of actual borrowing of text. In other words, it would mark two documents that both talked about football as being similar, even if they had no shared text.

That said, this package extends classes from the NLP and tm packages, so it is intended to play nice with other R NLP packages.

• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.

Yes, I comply with all those guidelines. The exception is that I have named classes, for example, TextReuseTextDocument bowing to the precedent set by the NLP package. I don't like the name any better than you, but that's just how they do it with those packages.

• Are there any package dependencies not on CRAN?
• Do you intend for this package to go on CRAN?
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
• 1. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in cirucmstances.

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

This R package acts as a wrapper for the read-only features of the Goodreads API. The
package has various features so as to search and retrieve information on books, authors,
users, reviews, etc. based on their ISBN, titles, ids, etc. in order to analyze them as R objects.

• 2. Paste the full DESCRIPTION file inside a code block below.

Package: rgoodreads
Type: Package
Title: Client for the Goodreads API
Version: 0.1
Date: 2016-02-23
Author: Sagun Pai
Maintainer: <[email protected]>
Description: This R package acts as a wrapper for the read-only features of the Goodreads API with the ability to retrieve information on books, authors, users, reviews, etc. so that they can be analyzed in R.
License: MIT
Depends:
    R (>= 3.1.1)
Imports:
    httr,
    XML,
    RCurl
LazyData: TRUE
URL: http://github.com/famguy/rgoodreads
BugReports: http://github.com/famguy/rgoodreads/issues
RoxygenNote: 5.0.1

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

https://github.com/Famguy/rgoodreads

• 4. What data source(s) does it work with (if applicable)?

It works on the Goodreads API. Check out the documentation here

• 5. Who is the target audience?

Book enthusiasts, people who want to use books data for their analysis

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

None that I know of

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

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

Web scraping allows to gather information of scientific value - mainly social science related in my experience. While scraping web pages one should respect permissions declared in robots.txt files.
The package provides functions to retrieve and parse robots.txt files. The core functionality is to check a bots/users permission for one or more resources (paths) for a given domain. To ease checking all functions have been bundled with relevant data into an R6 robotstxt class but everything works functional or object oriented depending on the users preferences.

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: robotstxt
Type: Package
Title: A 'robots.txt' Parser and Webbot/Webspider/Webcrawler Permissions Checker
Version: 0.1.0
Author: Peter Meissner
Maintainer: Peter Meissner <[email protected]>
Description: Class ('R6') and accompanying methods to
    parse and check 'robots.txt' files. Data fields are provided as
    data frames and vectors. Permissions can be checked by providing
    path character vectors and optional bot names.
License: MIT + file LICENSE
LazyData: TRUE
BugReports: https://github.com/petermeissner/robotstxt/issues
URL: https://github.com/petermeissner/robotstxt
Imports:
    R6 (>= 2.1.1),
    stringr (>= 1.0.0),
    httr (>= 1.0.0)
Suggests:
    knitr,
    rmarkdown,
    dplyr,
    testthat
Depends:
    R (>= 3.0.0)
VignetteBuilder: knitr
RoxygenNote: 5.0.1

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

https://github.com/petermeissner/robotstxt

• 4. What data source(s) does it work with (if applicable)?

robots.txt files like:

• https://en.wikipedia.org/robots.txt
• https://github.com/robots.txt
• 5. Who is the target audience?

Package developers and users that want an easy way to be nice while gathering data from the web.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

None that I know of.

• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with
• The repository has continuous integration with Travis and/or another service: https://travis-ci.org/petermeissner/robotstxt
• The package contains a vignette:
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the [rOpenSci packaging guidelines]

Yes, good guidelines!

• Are there any package dependencies not on CRAN?

No.

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

With or without ropensci.

• Does the package have a CRAN accepted license?

yes, MIT

• Did devtools::check() produce any errors or warnings? If so paste them below.

no:

* DONE
Status: OK

R CMD check succeeded

• 9. Please add explanations below for any exceptions to the above:

Does not apply.

• 10. If this is a resubmission following rejection, please explain the change in cirucmstances.

No, no resubmit.

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

rsdmx is a package to parse/read SDMX data and metadata documents in R. It provides a set of classes and methods to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework. The package currently focuses on the SDMX XML standard format (SDMX-ML). It is part of the Web Technologies CRAN Task View. More details.

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: rsdmx
Version: 0.4-7
Date: 2015-06-01
Title: Tools for Reading SDMX Data and Metadata
Authors@R: c(
  person("Emmanuel", "Blondel", role = c("aut", "cre"), email = "[email protected]"),
  person("Matthieu", "Stigler", role = c("ctb")))
Maintainer: Emmanuel Blondel <[email protected]>
Depends: R (>= 2.15)
Imports: methods, XML (>= 3.96-1.1), RCurl, plyr
Suggests: testthat
Description: Set of classes and methods to read data and metadata documents
  exchanged through the Statistical Data and Metadata Exchange (SDMX) framework,
  currently focusing on the SDMX XML standard format (SDMX-ML).
License: GPL (>= 2)
URL: https://github.com/opensdmx/rsdmx, http://www.sdmx.org
BugReports: https://github.com/opensdmx/rsdmx/issues
LazyLoad: yes
Collate:
  Class-SDMXSchema.R Class-SDMXType.R Class-SDMXStructureType.R
  Class-SDMXHeader.R Class-SDMXFooterMessage.R Class-SDMXFooter.R
  Class-SDMX.R Class-SDMXGenericData.R Class-SDMXCompactData.R Class-SDMXUtilityData.R
  Class-SDMXMessageGroup.R Class-SDMXConcept.R Class-SDMXConceptScheme.R Class-SDMXConcepts.R
  Class-SDMXCode.R Class-SDMXCodelist.R Class-SDMXCodelists.R Class-SDMXDimension.R
  Class-SDMXTimeDimension.R Class-SDMXPrimaryMeasure.R Class-SDMXAttribute.R Class-SDMXComponents.R
  Class-SDMXDataStructure.R Class-SDMXDataStructures.R Class-SDMXDataStructureDefinition.R
  SDMXSchema-methods.R SDMXType-methods.R SDMXStructureType-methods.R SDMXHeader-methods.R
  SDMXFooterMessage-methods.R SDMXFooter-methods.R SDMX-methods.R
  SDMXGenericData-methods.R SDMXCompactData-methods.R SDMXUtilityData-methods.R SDMXMessageGroup-methods.R
  SDMXConcept-methods.R SDMXConceptScheme-methods.R SDMXConcepts-methods.R SDMXCode-methods.R
  SDMXCodelist-methods.R SDMXCodelists-methods.R SDMXDimension-methods.R SDMXTimeDimension-methods.R
  SDMXPrimaryMeasure-methods.R SDMXAttribute-methods.R SDMXComponents-methods.R
  SDMXDataStructure-methods.R SDMXDataStructures-methods.R SDMXDataStructureDefinition-methods.R
  readSDMX.R

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

https://github.com/opensdmx/rsdmx

• 4. What data source(s) does it work with (if applicable)?

All SDMX-ML standard compliant data sources, supporting SDMX-ML format version 1.0, 2.0 and 2.1. Notice that a development strategy of rsdmx is to follow a low-level approach which intends to focus on the SDMX format specification, rather than the SDMX web-service specifications. rsdmx is then not restricted to the web (SDMX local files can be read) and for the web, it is not restricted to data sources disseminated with web-services compliant with the SDMX web-service specifications.

• 5. Who is the target audience?

Universities, Research scientists, statisticians, public institutions & companies that need to extract statistical data in R from institutions that disseminate data and metadata in the Statistical Data and Metadata eXchange format (SDMX).

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

As known active package, RJSDMX provides an interface to read SDMX data in R. AFAIK, the main differences i've identified are: (1) the core technology to read SDMX documents (rsdmx is writen in R and relies on the XML package, RJSDMX builds on a Java statistical software connector.), (2) RJSDMX restrains to SDMX data exchanged with known web-services strictly complying with the SDMX web-service standards, while rsdmx starts from a lower level flexible approach, focusing only on the SDMX format specification (See above point 4.). As consequence, rsdmx does not bring (at now) helpers to "build" the SDMX web requests, but allows to read both local and remote SDMX data (from standard web-service architectures or not) and makes abstraction of the data providers and the data domain.

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette (An online documentation is available and continuously updated. And i've added a quickstart vignette based on it.)
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Are there any package dependencies not on CRAN?
• Do you intend for this package to go on CRAN? (yet on CRAN)
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in cirucmstances.

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

rebi gives access to Europe PubMed Central, an indexing service for life-
science publications that is provided by the European Bioinformatics Institute
(EBI). This client can be used to search metadata and full-texts, retrieve
reference sections, citations, text-mined terms, and links to other EBI
databases or external sources like the Wikipedia.

• 2. Paste the full DESCRIPTION file inside a code block below.

Package: rebi
Version: 0.0.999
Maintainer: 'Najko Jahn' <[email protected]>
Author: Najko Jahn
License: GPL-3
Title: rebi -- R Interface for Europe PMC RESTful Web Service
URL: http://github.com/njahn82/rebi/
BugReports: http://github.com/njahn82/rebi/issues
Description: R Interface to Europe PMC RESTful Web Service. Europe PMC covers
    life science literature and it gives access to open access full texts.
    Coverage is not only restricted to Europe, but articles and abstracts are
    indexed from all over the world. As a partner in the PMC International
    (PMCi), Europe PMC ingests all PubMed content and extends its index with
    other sources, including Agricola, a bibliographic database of citations to
    the agricultural literature, or Biological Patents. In addition to
    bibliographic data, rebi gives automated access to citations and references
    that were indexed by Europe PMC. Links between life-science literature and
    other EBI databases, including ENA, PDB or ChEMBL are also accessible.
    External links provide a mechanism to link out to external providers such as
    Wikipedia or research data repositories.
LazyLoad: yes
LazyData: yes
VignetteBuilder: knitr
Depends:
  R (>= 3.00)
Imports:
    httr,
    jsonlite,
    plyr,
    xml2
RoxygenNote: 5.0.1
Suggests:
    testthat,
    knitr,
    rmarkdown

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

https://github.com/njahn82/rebi

• 4. What data source(s) does it work with (if applicable)?

It only works with Europe PMC's Articles RESTful API.
https://europepmc.org/RestfulWebService

• 5. Who is the target audience?

Life-science researchers and students, scholars that study the life sciences,
librarians.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

To my knowledge, this is the only package that implements Europe PMC's
Articles RESTful API. Since there is a considerable overlap with PubMed/PubMed
Central, the rentrez package could be used as well to fetch bibliographic
information. fulltext package gives access to supplementary material
deposited in Europe PMC. oai package could be used to retrieve metadata from
Europe PMC via its OAI-PMH interface.

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

This package has been available through rOpenSci since summer 2013. Because I
made major upgrades in the last days that reflect the rOpenSci guidance on how
to write packages, I thought it might be helpful to re-submit this package.

See also the discussion in the forum:
https://discuss.ropensci.org/t/major-package-update-of-rebi-and-question-regarding-re-submission/333/

1. What does this package do? (explain in 50 words or less)

   Currently, the package facilitates the import of GTFS data (from url or local path) to create gtfs objects, validates file structure of gtfs objects, and provides functions to easily plot stops, routes, or networks.

   Future versions will build validation and modeling capabilities, and options to layer other data.

2. Paste the full DESCRIPTION file inside a code block below.

Package: gtfsr
Type: Package
Title: Working with GTFS (General Transit Feed Specification) feeds in R
Version: 0.1.0
Authors@R: as.person(c(
    "Elaine McVey <[email protected]> [aut, cre]",
    "Danton Noriega-Goodwin <[email protected]> [aut]"
  ))
Description: Provides API wrappers for popular public GTFS feed sharing sites, reads feed data into a gtfs data object, validates data quality, provides convenience functions for common tasks.
License: GPL
LazyData: TRUE
Imports:
    dplyr,
    readr,
    httr,
    magrittr,
    stringr,
    assertthat,
    leaflet,
    sp,
    rgeos,
    scales
Suggests:
    testthat,
    knitr,
    rmarkdown
RoxygenNote: 5.0.1
VignetteBuilder: knitr

1. URL for the package (the development repository, not a stylized html page)

   https://github.com/ropenscilabs/gtfsr

2. What data source(s) does it work with (if applicable)?

   It is designed to work with any text files following the GTFS format. It does not come with any accompanying data.

3. Who is the target audience?

   Transportation Economists, Transportation Consultants and Researchers, Urban Planners, Open Data Enthusiasts

4. Are there other R packages that accomplish the same thing? If so, what is different about yours?

   None

5. Check the box next to each policy below, confirming that you agree. These are mandatory.

   • This package does not violate the Terms of Service of any service it interacts with.
   • The repository has continuous integration with Travis CI and/or another service
   • The package contains a vignette
   • The package contains a reasonably complete README with instructions for installing the development version.
   • The package contains unit tests
   • The package only exports functions to the NAMESPACE that are intended for end users

6. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.

   • [NO] Are there any package dependencies not on CRAN?
   • [YES] Do you intend for this package to go on CRAN?
   • [NO] Does the package have a CRAN accepted license?
   • [YES] Did R CMD check (or devtools::check()) produce any errors or warnings? If so paste them below.

R CMD check results
0 errors | 0 warnings | 1 note 
checking R code for possible problems ... NOTE
map_gtfs_agency_routes: warning in get_agency_stops(gtfs_obj, agency_id
  = agency): partial argument match of 'agency_id' to 'agency_ids'
map_gtfs_route_shape: warning in get_agency_stops(gtfs_obj, agency_id =
  agencies): partial argument match of 'agency_id' to 'agency_ids'
filter_feedlist: no visible binding for global variable ‘.’
get_agency_stops: no visible binding for global variable ‘agency_id’
get_agency_stops: no visible binding for global variable ‘route_id’
get_agency_stops: no visible binding for global variable ‘trip_id’
get_agency_stops: no visible binding for global variable ‘stop_id’
... 62 lines ...
  ‘file_provided_status’
validate_vars_provided: no visible binding for global variable
  ‘field_provided_status’
validate_vars_provided: no visible binding for global variable
  ‘validation_status’
Undefined global functions or variables:
  . agency_id color field field_provided_status field_spec
  file_provided_status file_spec n opacity popups prob_subset route_id
  route_short_name service_id shape_id shape_pt_lat shape_pt_lon
  shape_pt_sequence spec stop_id stop_lat stop_lon stop_name trip_id
  validation_details validation_status

1. Please add explanations below for any exceptions to the above: NA
2. If this is a resubmission following rejection, please explain the change in circumstances. NA

• lintr - check that pkg has (available linters: https://github.com/jimhester/lintr#available-linters)
  • tests
  • vignette
  • etc....other built in checks
  • style checks for things like use httr instead of RCurl, unless good reason otherwise, etc.
• is looking at travis logs good enough? or should we make a prettier presentation somehow
• when travis checks done, post hook to ping back to issue or PR with a summary? or somehow in the travis logs make it easy to find the important bits (e.g., things that don't pass)
• should we move to PR system, or stick with issue based system?
• there was some discussion of limiting review lengths, e.g,. a strategy could be to only look at internals of one function if there are many similar ones, etc. - Others have brought up limiting to a certain number of lines of code...
• others ...

cc/ @noamross

This convo I started made me think we should have some clarity in our standard outreach on when we expect people to respond to review requests. We should probably say we expect a response in a week.

To facilitate this, I'm planning on adding a review request e-mail template to the repo. Here's one recent one I'll base it off of.

Hi, this is Noam Ross. I'm writing to ask if you would be willing to review a package for rOpenSci. As you probably know, rOpenSci conducts peer review of R packages contributed to our collection in a manner similar to journals.

The package, ezknitr by Dean Attali, provides some convenience utilities for using knitr documents. You can find it on GitHub here: https://github.com/daattali/ezknitr. We conduct our open review process via GitHub as well, here: #56

If you accept, note that we ask reviewers to complete reviews in three weeks. (We’ve found it takes a similar amount of time to review a package as an academic paper.) Our [reviewers guide] details what we look for in a package review, and includes links to example reviews. Our standards are detailed in our [packaging guide]. If you have questions or feedback, feel free to ask me or post to the [rOpenSci forum].

Are you able to review? If you can not, suggestions for alternate reviewers are always helpful. Thank you for your time.

Sincerely,

Noam
@noamross everywhere
Associate Editor, rOpenSci
Disease Ecologist, EcoHealth Alliance

• 1. What does this package do? (explain in 50 words or less)
     This package provides access to the existing modules of the monkeylearn API, allowing for instance Named Entity Recognition, language detection, attribution of topics to texts.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: monkeylearn
Type: Package
Title: Access to the Monkeylearn API for text classifiers and extractors
Version: 0.1.0
Authors@R: person("Maëlle", "Salmon", email = "[email protected]", role = c("aut", "cre"))
Description: The package allows using some services of Monkeylearn which is
    a Machine Learning platform on the cloud that allows software companies and
    developers to easily extract actionable data from text.
License: GPL (>= 2)
LazyData: TRUE
URL: http://github.com/masalmon/monkeylearn
BugReports: http://github.com/masalmon/monkeylearn/issues
Encoding: UTF-8
RoxygenNote: 5.0.1
Suggests: testthat,
    knitr,
    rmarkdown
Imports: jsonlite, dplyr, httr
VignetteBuilder: knitr

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/masalmon/monkeylearn
• 4. What data source(s) does it work with (if applicable)?
     It works with monkeylearn API
     http://monkeylearn.com/
     Note that one can register using one's Github account.
• 5. Who is the target audience?
     Anyone that wants to use Natural Language Processing methods without e.g. first installing Java, or someone that already uses monkeylearn and wants to integrate it in a R workflow (but only for text processing, not for module development)
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     Yes the openNLP package provides several Natural Language Processing methods such as Named Entity Recognition but has a Java dependency that makes its installation difficult for some users.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [ x] This package does not violate the Terms of Service of any service it interacts with.
  • [ x] The repository has continuous integration with Travis CI and/or another service
  • [ x] The package contains a vignette
  • [x ] The package contains a reasonably complete README with devtools install instructions
  • [ x] The package contains unit tests
  • [ x] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • [ x] Do you intend for this package to go on CRAN?
  • [ x] Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
     It's not an explanation to any exception but I wanted to underline I'm not sure I've chosen the best solution for dealing with the throttle limit (I retry 5 times if there is a 429 API error which is throttle limit), so I'd very much appreciate feedback on this (and on anything else, obviously!).
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

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

It interacts with the Open Tree of Life API (http://opentreeoflife.org/)

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: rotl
Title: Interface to the Open Tree of Life API
Version: 0.1
Authors@R: c(
  person("Francois", "Michonneau", role=c("aut", "cre"),
         email="[email protected]"),
  person("Joseph", "Brown", role="aut"),
  person("David", "Winter", role="aut"))
Description: An interface to the Open Tree of Life API to retrieve phylogenetic
   trees, information about studies used to assemble the synthetic tree, and
   utilities to match taxonomic names to Open Tree identifiers. The Open Tree of
   Life aims at assembling a comprehensive phylogenetic tree for all named
   species.
URL: https://github.com/fmichonneau/rotl
BugReports: https://github.com/fmichonneau/rotl/issues
Depends:
    R (>= 3.1.1)
Imports:
    httr,
    jsonlite,
    rncl,
    ape
License: BSD_2_clause + file LICENSE
Suggests:
    knitr,
    rmarkdown,
    testthat,
    RNeXML
VignetteBuilder: knitr
LazyData: true

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

https://github.com/fmichonneau/rotl

• 4. What data source(s) does it work with (if applicable)?

http://api.opentreeoflife.org/

• 5. Who is the target audience?

Scientists who want to use phylogenies

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

No.

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Are there any package dependencies not on CRAN?
• Do you intend for this package to go on CRAN?
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in cirucmstances.

• 1. gutenbergr offers tools to download and process public domain works in the Project Gutenberg collection. Includes metadata for all Project Gutenberg works, so that they can be searched and retrieved.
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: gutenbergr
Type: Package
Title: Download and Process Public Domain Works from Project Gutenberg
Version: 0.1
Date: 2016-05-02
Authors@R: person("David", "Robinson", email = "[email protected]", role = c("aut", "cre"))
Description: Download and process public domain works in the Project
    Gutenberg collection. Includes metadata for all Project Gutenberg works,
    so that they can be searched and retrieved.
License: MIT + file LICENSE
LazyData: TRUE
Maintainer: David Robinson <[email protected]>
VignetteBuilder: knitr
Depends: R (>= 2.10)
Imports:
    dplyr,
    readr,
    purrr,
    urltools,
    rvest,
    xml2,
    stringr
RoxygenNote: 5.0.1
Suggests: knitr,
    rmarkdown,
    testthat,
    tidytext,
    ggplot2,
    tidyr

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

https://github.com/dgrtwo/gutenbergr

• 4. What data source(s) does it work with (if applicable)?

Project Gutenberg

• 5. Who is the target audience?

People interested in text mining and analysis. Especially interesting to those analyzing historical and literary works, but this can also serve as example datasets for text mining problems.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

No.

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [x ] This package does not violate the Terms of Service of any service it interacts with.
  • [x ] The repository has continuous integration with Travis CI and/or another service
  • [x ] The package contains a vignette
  • [x ] The package contains a reasonably complete README with devtools install instructions
  • [x ] The package contains unit tests
  • [x ] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • [x ] Do you intend for this package to go on CRAN?
  • [x ] Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

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

Allows you to use 'knitr' with complex directory structures and gives you more control over where inputs/outputs/figures/scripts live when knitting documents. Real research projects often don't have a flat directory structure, which can make using 'knitr' on such projects very cumbersome.

• 2. Paste the full DESCRIPTION file inside a code block below.

Package: ezknitr
Title: Avoid the Typical Working Directory Pain When Using 'knitr'
Version: 0.4
Authors@R: person("Dean", "Attali", email = "[email protected]",
    role = c("aut", "cre"))
Description: An extension of 'knitr' that adds flexibility in several
    ways. One common source of frustration with 'knitr' is that it assumes
    the directory where the source file lives should be the working directory,
    which is often not true. 'ezknitr' addresses this problem by giving you
    complete control over where all the inputs and outputs are, and adds several
    other convenient features to make rendering markdown/HTML documents easier.
URL: https://github.com/daattali/ezknitr
BugReports: https://github.com/daattali/ezknitr/issues
Depends: 
    R (>= 3.0.2)
Imports: 
    knitr (>= 1.7),
    markdown (>= 0.7),
    R.utils (>= 1.34.0)
Suggests: 
    testthat (>= 0.9.1),
    rmarkdown
License: MIT + file LICENSE
SystemRequirements: pandoc with https support
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 5.0.1

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

https://github.com/daattali/ezknitr

• 4. What data source(s) does it work with (if applicable)?

N/A

• 5. Who is the target audience?

Any researcher or grad student who wants to better automate and organize their research using knitr but find it annoying/impossible to deal with directories in a sane way

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
  • rmarkdown has support for parameters in Rmd documents. One of the features that ezknitr offers is the ability to pass parameters to Rmd files. There is a difference between the two: rmarkdown assumes that the parameters are defined in the Rmd YAML, while ezknitr lets you change any arbitrary variable. This difference is not too significant, but the main reason ezknitr has this feature is to support older Rmd files that don't have YAML because the introduction of parameterized Rmd files is fairly new
  • rprojroot provides a very different solution to a related problem. rprojroot helps you find a specific file in relation to a project's root directory, while ezknitr is specifically for dealing with knitting documents in complex directory structures
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with instructions for installing the development version.
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did R CMD check (or devtools::check()) produce any errors or warnings? If so paste them below.

Yes, I will follow those guidelines. The package is already on CRAN.

• 9. Please add explanations below for any exceptions to the above:

N/A

• 10. If this is a resubmission following rejection, please explain the change in circumstances.

N/A

• UPDATE 11. JOSS publication
• Do you wish to automatically submit to the Journal of Open Source Software? If so:

  • The package contains a paper.md with a high-level description.

    yes, I included paper.md under /inst/joss/

  • The package is deposited in a long-term repository with the DOI:

    figshare 10.6084/m9.figshare.3545363

Describe the package

Contents of DESCRIPTION:

Package: rrlite
Title: R bindings to rlite
Version: 0.1.0
Description: R bindings to rlite.  rlite is a "self-contained,
  serverless, zero-configuration, transactional redis-compatible
  database engine. rlite is to Redis what SQLite is to SQL.".
Depends: R (>= 3.1.2)
License: BSD_2_clause + file LICENSE
LazyData: true
Author: Rich FitzJohn
Maintainer: Rich FitzJohn <[email protected]>
Suggests: testthat
Imports: R6

url: https://github.com/richfitz/rrlite

What data source(s) does it work with (if applicable)?

Key/value data

Who is the target audience?

Package authors, data users. Probably will appeal to more technically inclined people than most ropensci packages but could be an ingredient in other ropensci packages.

Who has/will contribute to this package?

I am currently the only contributor, but @sckott plans on contributing

Are you willing to follow the rOpenSci policies (link), including transferring your repo to the rOpenSci GitHub organization account? [yes/no]

yes

Are you willing to follow the rOpenSci packaging guidelines? If you disagree with any, explain.

yes

• 1. What does this package do? (explain in 50 words or less)
     Create laboratory note and report for helpful reproducible research.
• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: lab.note
Type: Package
Title: Create Laboratory Note and Presentation Using R Markdown
Version: 0.7.0
Date: 2015-05-21
Authors@R: person("Shinya", "Uryu", email = "[email protected]", role = c("aut", "cre"))
Imports:
  knitr,
  rmarkdown
Suggests: 
  broom,
  dplyr, 
  ggplot2,
  ggvis,
  knitcitations,
  magrittr,
  shiny,
  tidyr,
  xtable
VignetteBuilder: knitr
URL: https://github.com/uribo/lab.note
BugReports: https://github.com/uribo/lab.note/issues
Description: Make it can reproducible R Markdown report and other format such as presentation and RPubs published files. Contains built-in useful package using R and LaTeX. These packages usages to see vignettes and wiki more information.
License: MIT + file LICENSE

• 3. URL for the package (the development repository, not a stylized html page)
  • https://github.com/uribo/lab.note
• 4. What data source(s) does it work with (if applicable)?
  • none.
• 5. Who is the target audience?
  • academic student and researcher.
• 6. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• 7. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Are there any package dependencies not on CRAN?
• Do you intend for this package to go on CRAN?
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
  • no
• 8. Please add explanations below for any exceptions to the above:
• 9. If this is a resubmission following rejection, please explain the change in cirucmstances.

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

oai is an R client to work with OAI-PMH services, used by many libraries and other content distributors (e.g. Dryad, Datacite, etc.). The data is metadata for an object (book, video, digital files, etc.)

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: oai
Type: Package
Title: General Purpose 'Oai-PMH' Services Client
Description: A general purpose client to work with any 'OAI-PMH'
    service. The 'OAI-PMH' protocol is described at
    http://www.openarchives.org/OAI/openarchivesprotocol.html.
    Functions are provided to work with the 'OAI-PMH' verbs: 'GetRecord',
    'Identify', 'ListIdentifiers', 'ListMetadataFormats', 'ListRecords', and
    'ListSets'.
Version: 0.0.5.9000
License: MIT + file LICENSE
Authors@R: c(person("Scott", "Chamberlain", role = c("aut", "cre"),
    email = "[email protected]"))
URL: https://github.com/sckott/oai
BugReports: https://github.com/sckott/oai/issues
Imports:
    methods,
    stats,
    utils,
    xml2,
    httr
Suggests:
    testthat

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

https://github.com/sckott/oai

• 4. What data source(s) does it work with (if applicable)?

Any OAI-PMH service

• 5. Who is the target audience?

Primarily other R clients - I have a number of R clients I work on that could use this. In addition, some users may want to use this to interact with OAI-PMH services themselves.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

There is an OAI-PMH client (https://cran.rstudio.com/web/packages/OAIHarvester/) on CRAN but it's built on XML and RCurl, packages basically replaced now by xml2 and httr/curl, respectively. oai is built on xml2 and httr. In addition, I give back tidy dplyr like data.frame's to make data comprehension, manipulation, and visualization easier, whereas OAIHarvester gives back arrays/matrices

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Are there any package dependencies not on CRAN?
• Do you intend for this package to go on CRAN?
• Does the package have a CRAN accepted license?
• Did devtools::check() produce any errors or warnings? If so paste them below.
• 1. Please add explanations below for any exceptions to the above:
• 1. If this is a resubmission following rejection, please explain the change in circumstances.

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

Package containing the functions for the DoOR project. DoOR provides a framework to merge heterogeneous response data into a single consensus database, thus creating a comprehensive view on olfactory coding.

• 2. Paste the full DESCRIPTION file inside a code block below.

Package: DoOR.functions
Type: Package
Title: Integrating Heterogeneous Odorant Response Data into a Common Response
    Model: A DoOR to the Complete Olfactome
Version: 2.0.0
Date: 2016-02-25
Authors@R: c(
    person("Daniel", "Münch", email = "[email protected]", role = c("aut", "cre")),
    person("C. Giovanni", "Galizia", email = "[email protected]", role = "aut"),
    person("Shouwen", "Ma", role = "aut"),
    person("Martin", "Strauch", role = "aut"),
    person("Anja", "Nissler", role = "aut"),
    person("Wolf", "Huetteroth", role = "ctb"))
URL: http://neuro.uni.kn/DoOR
BugReports: https://github.com/Dahaniel/DoOR.data/issues
Description: This is a function package providing functions to perform data
    manipulations and visualizations for DoOR.data. See http://dx.doi.org/10.1093/chemse/bjq042 for the original publication and http://dx.doi.org/10.1038/srep21841
    regarding version 2.0.
License: GPL-3
Encoding: UTF-8
Imports:
    utils
Depends:
    DoOR.data (>= 2.0.0),
    R (>= 3.2.0)
Remotes: Dahaniel/[email protected]
Suggests:
    ggplot2,
    grid,
    gridExtra (>= 2.0.0),
    knitr,
    class,
    rmarkdown
VignetteBuilder: knitr
RoxygenNote: 5.0.1

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

https://github.com/Dahaniel/DoOR.functions

• 4. What data source(s) does it work with (if applicable)?

It provides its own data via the DoOR.data package (see corresponding onboarding issue).

• 5. Who is the target audience?

Scientists working on olfactory coding, modelers and physiologists.

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

No, to our knowledge DoOR is the only project providing this kind of data and using this approach to integrate heterogeneous data.

• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN? - no
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below. - no
• 9. Please add explanations below for any exceptions to the above:
  • Not sure how to implement unit tests but am willing to learn, might need some help.
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

• 1. What does this package do? (explain in 50 words or less)
     It allows users to assess the geospatial quality of biodiversity data by providing native access to the methods of the Geospatial Quality API (http://bit.ly/gqapi_doc_gh)
• 2. Paste the full DESCRIPTION file inside a code block below.

Package: rgeospatialquality
Type: Package
Title: R Wrapper for the Geospatial Data Quality REST API
Version: 0.2.2
Date: 2016-02-22
Authors@R: person("Javier", "Otegui", email="[email protected]",
    role=c("aut", "cre"))
Description: This package provides native wrappers for the functions available
    via de spatial quality REST API. More information on the API can be found
    here: http://bit.ly/bioinformatics_btw057.
License: file LICENSE
LazyData: TRUE
Imports:
    httr (>= 1.0.0),
    jsonlite (>= 0.9.19),
    rgbif (>= 0.9.2)
RoxygenNote: 5.0.1
Suggests: knitr,
    roxygen2,
    rmarkdown,
    testthat
VignetteBuilder: knitr
URL: https://github.com/jotegui/rgeospatialquality
BugReports: https://github.com/jotegui/rgeospatialquality/issues

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/jotegui/rgeospatialquality
• 4. What data source(s) does it work with (if applicable)?
     None
• 5. Who is the target audience?
     Biodiversity community: collection managers, researchers
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     There are no other packages, as far as I know
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN? No
  • Do you intend for this package to go on CRAN? Yes
  • Does the package have a CRAN accepted license? Yes
  • Did devtools::check() produce any errors or warnings? If so paste them below. No error or warning
• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.

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

Provides a CRAN-like repository for serving our R packages. See https://github.com/cboettig/packages readme for details.

• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

N/A

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

https://github.com/cboettig/packages

• 4. What data source(s) does it work with (if applicable)?

R packages from https://github.com/ropensci

• 5. Who is the target audience?

Anyone wanting to install our R packages.

• 6. Check the box next to each policy below, confirming that you agree. These are mandatory.

N/A

• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests

N/A

• 7. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.

I agree.

• Are there any packages that your package depends on that are not on CRAN?

N/A

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

N/A

• Does the package have a CRAN accepted license?

N/A

• Did devtools::check() produce any errors or warnings? If so paste them below.

N/A

• 8. Please add explanations below for any exceptions to the above:

N/A

• 9. If this is a resubmission following rejection, please explain the change in cirucmstances.

Documentation related to onboarding is currently fragmented across:

• README in this repository
• Reviewers' guide in this repository's wiki, along with other various stubs in the wiki.
• README in the policies repo
• README and NEWS sample in the packaging guide repo

Fragmentation can lead to various parts being difficult to track, and parts getting out of sync. I propose consolidating this documentation all into this repository and eliminating the wiki. This would include an expanded README with "Why submit?" and "Why review?" and then gets to "How", where we link to other files such as packaging guide, reviewers guide, policies, etc.

We may want an an even shorter version of the README this on the rOpenSci website, perhaps as a top-level page linked to from https://ropensci.org/packages/, or just second paragraph on that page?

For users submitting packages on CRAN, should we fastrack those (assuming the fit is good)? or still put it through all the checks and such?
I suppose it is likely that a package with no tests/CI will come to us (but be fine for CRAN).

• 1. What does this package do? (explain in 50 words or less)
     Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod
     tempor incididunt ut labore
• 2. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: rglobi
Type: Package
Title: R Interface to Global Biotic Interactions
Description: A programmatic interface to the web service methods
    provided by Global Biotic Interactions (GloBI). GloBI provides 
    access to spatial-temporal species interaction records from 
    sources all over the world. rglobi provides methods to search 
    species interactions by location, interaction type, and 
    taxonomic name. In addition, it supports Cypher, a graph query
    language, to allow for executing custom queries on the GloBI 
    aggregate species interaction dataset.
Version: 0.2.6
Date: 2015-03-17
Authors@R: c(person("Jorrit", "Poelen", role = c("aut", "cre"),
    email = "[email protected]"),
    person("Stephen", "Gosnell", role = "aut",
    email = "[email protected]"),
    person("Sergey", "Slyusarev", role = "aut",
    email = "[email protected]"))
URL: https://github.com/ropensci/rglobi
BugReports: https://github.com/ropensci/rglobi/issues
VignetteBuilder: knitr
Depends:
    R (>= 3.0.1)
License: MIT + file LICENSE
Imports:
    rjson (>= 0.2.13), 
    RCurl
Suggests:
    testthat,
    knitr

• 3. URL for the package (the development repository, not a stylized html page): https://github.com/ropensci/rglobi
• 4. What data source(s) does it work with (if applicable)? None
• 5. Who is the target audience? Your doge
• 6. Check the box next to each policy below, confirming that you agree. These are mandatory.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a complete readme with devtools install instructions
• The package contains unit tests
• 7. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• Does the package have a CRAN accepted license?
• Are there any packages that your package depends on that are not on CRAN?
• Do you intend for this package to go on CRAN?
• 8. Please add explanations below for any exceptions to the above:

Nothing further to add. Thanks for considering!

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

Provides tokenizers for natural language.

• 2. Paste the full DESCRIPTION file inside a code block below.

Package: tokenizers
Type: Package
Title: Tokenize Text
Version: 0.1.1
Date: 2016-04-03
Description: Convert natural language text into tokens. The tokenizers have a
    consistent interface and are compatible with Unicode, thanks to being built
    on the 'stringi' package. Includes tokenizers for shingled n-grams, skip
    n-grams, words, word stems, sentences, paragraphs, characters, lines, and
    regular expressions.
License: MIT + file LICENSE
LazyData: yes
Authors@R: c(person("Lincoln", "Mullen", role = c("aut", "cre"),
        email = "[email protected]"),
        person("Dmitriy", "Selivanov", role = c("ctb"),
        email = "[email protected]"))
URL: https://github.com/lmullen/tokenizers
BugReports: https://github.com/lmullen/tokenizers/issues
RoxygenNote: 5.0.1
Depends:
  R (>= 3.1.3)
Imports:
  stringi (>= 1.0.1),
  Rcpp (>= 0.12.3),
  SnowballC (>= 0.5.1)
LinkingTo: Rcpp
Suggests: testthat

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

https://github.com/lmullen/tokenizers

• 4. What data source(s) does it work with (if applicable)?

Natural language text

• 5. Who is the target audience?

Users of R packages for NLP

• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?

Virtually every R package for NLP implements a couple of tokenizers. The point of this package is to collect all the tokenizers that one could conceivably want to use in a single package, and make sure that all the packages have a consistent interface. The package also aims to have fast and correct tokenizers implemented on top of stringi and Rcpp.

• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • The package contains a reasonably complete README with devtools install instructions
  • The package contains unit tests
  • The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • Are there any package dependencies not on CRAN?
  • Do you intend for this package to go on CRAN?
  • Does the package have a CRAN accepted license?
  • Did devtools::check() produce any errors or warnings? If so paste them below.
• 1. Please add explanations below for any exceptions to the above:

The package does not contain a vignette, but it does contain an extensive README. Since all the tokenizers work in the same basic way, a vignette seems unnecessary. But if rOpenSci wants one, I can easily adapt the README into a standalone vignette.

This package is already on CRAN.

• 10. If this is a resubmission following rejection, please explain the change in circumstances.

• 1. What does this package do? (explain in 50 words or less)
     rnaturalearth provides :
• a pre-downloaded subset of Natural Earth vectors commonly used in world mapping.
• functions to download other Natural Earth vectors.
• an open, reproducible workflow from www.naturalearthdata.com enabling updating as new versions become available.
• flexibility to get maps classified by countries, sovereign states and map-units.
• 1. Paste the full DESCRIPTION file inside a code block (bounded by ``` on either end).

Package: rnaturalearth
Title: World Vector Map Data from Natural Earth
Version: 0.0.0.9000
Authors@R: person("Andy", "South", , "[email protected]", role = c("aut", "cre"))
Description: Facilitates mapping by making natural earth map data from http://
    www.naturalearthdata.com/ more easily available to R users. Focuses on vector
    data.
License: CC0
LazyData: true
LazyDataCompression: xz
URL: https://github.com/AndySouth/rnaturalearth
BugReports: https://github.com/AndySouth/rnaturalearth/issues
Depends:
    R (>= 3.1.1)
Imports:
    sp (>= 1.0.15),
    rgdal
Suggests:
    knitr,
    testthat (>= 0.9.1),
    httr
VignetteBuilder: knitr
RoxygenNote: 5.0.1

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/AndySouth/rnaturalearth
• 4. What data source(s) does it work with (if applicable)?
     www.naturalearthdata.com
• 5. Who is the target audience?
     Anyone who wants to use Natural Earth vector data to make a map or perform other geographical analyses.
• 1. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     More limited subsets of Natural Earth data are available in at least the following CRAN packages rworldmap, rworldxtra, choroplethr, maps, oce, tmap. rnaturalearth is different in that it provides a comprehensive reproducible solution for access to Natural Earth vector map data either pre-downloaded or by facilitating download. By separating data access from visualisation this package provides a resource that can be used by other visualisation packages.
• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
• This package does not violate the Terms of Service of any service it interacts with.
• The repository has continuous integration with Travis and/or another service
• The package contains a vignette
• The package contains a reasonably complete readme with devtools install instructions
• The package contains unit tests
• The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
• [no] Are there any package dependencies not on CRAN?
• [yes] Do you intend for this package to go on CRAN?
• [yes] Does the package have a CRAN accepted license?
• [no] Did devtools::check() produce any errors or warnings? If so paste them below.
  One NOTE
• checking installed package size ... NOTE
  installed size is 26.0Mb
  sub-directories of 1Mb or more:
  data 25.8Mb
• 1. Please add explanations below for any exceptions to the above:
     The package is currently too big because of the fine scale (10m) data. Hadley suggested :
     "I think you need to keep the data under five meg. I'd suggest that you put the fine level data a separate package - you can then make that available via a drat repo (perhaps the ROpenSci one?), or just via github."
     I don't know anything about drat repos. I'm happy to take advice and modify the package(s) as recommended.

Hi all! In an effort to gather what we've learned from the past year of the ROpenSci package review process, I've put together a short survey. I hope you take a few minutes to fill it out: https://docs.google.com/forms/d/1spF-qQH7ec0dcS9hwpedeKhElo-Z3fYmgOUYiCxu9Xs/viewform

We will post a summary of results on the blog (with a link to the raw data, of course).

@richfitz
@karthik
@sckott
@jennybc
@Robinlovelace
@jooolia
@bocinsky
@eblondel
@jeroenooms
@fmichonneau
@dwinter
@FranzKrah
@lmullen
@andysouth
@tonyfischetti
@jennybc
@masalmon
@ateucher
@aammd
@petermeissner
@Ironholds
@layamane

• 1. What does this package do? (explain in 50 words or less)
     Provides extensive unit conversion in R, also includes RStudio add-in to assist the user in picking units.
• 1. Paste the full DESCRIPTION file inside a code block below.

Package: convertr
Type: Package
Title: Convert Between Units
Version: 0.1
Date: 2015-06-24
Authors@R: person("Gordon", "Shotwell", email = "[email protected]",
                  role = c("aut", "cre"))
Description: Provides conversion functionality between a broad range of
    scientific, historical, and industrial unit types.
Depends:
    R (>= 3.1.0)
Imports: shiny(>=   0.13.2),
    miniUI(>= 0.1.1),
    DT(>= 0.1),
    rstudioapi(>=   0.5)
License: CC0
LazyData: TRUE
BugReports: https://github.com/GShotwell/convertr/issues
Suggests:
    testthat
RoxygenNote: 5.0.1

• 3. URL for the package (the development repository, not a stylized html page)
     https://github.com/GShotwell/convertr
• 4. What data source(s) does it work with (if applicable)?
     None
• 5. Who is the target audience?
     Anyone with units to convert, mostly scientists and commodities analysts.
• 6. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     datamart provides unit conversion, but with fewer units and a less extensible framework. (It's hard to add units to datamart). convertr has more units.
     udunits2 Provides the same or greater space of units as convertr, but requires access to an external API. Also udunits2 doesn't have an RStudio add-in. Convertr is based around a built-in conversion table so can be used without an API, it also has an RStudio add-in to assist the user in searching through available units.
• 7. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [x ] This package does not violate the Terms of Service of any service it interacts with.
  • The repository has continuous integration with Travis CI and/or another service
  • The package contains a vignette
  • [x ] The package contains a reasonably complete README with devtools install instructions
  • [x ] The package contains unit tests
  • [x ] The package only exports functions to the NAMESPACE that are intended for end users
• 8. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.

I agree, so long as I can figure out how to use Travis.

* [ ] Are there any package dependencies not on CRAN? 

No
* [] Do you intend for this package to go on CRAN?
Yes
* [ ] Does the package have a CRAN accepted license?
Yes
* [ ] Did devtools::check() produce any errors or warnings? If so paste them below.
No errors

• 9. Please add explanations below for any exceptions to the above:
• 10. If this is a resubmission following rejection, please explain the change in circumstances.
      Not a resubmission

@mbjones points out that we should probably make a more visible link to the ropensci packaging_guide, it's kinda buried in the contributing.md document. Maybe it should also be linked from the README?

• Some general guidelines
• General advice (be kind, an order of magnitude kinder than CRAN when giving feedback etc?)

• 1. What does this package do? (explain in 50 words or less)
     Produces visually impressive customisable images from OpenStreetMap data
• 1. Paste the full DESCRIPTION file inside a code block below.

Produces customisable images of OpenStreetMap data.  Extracts OpenStreetMap data for specified key-value pairs (e.g.  key="building") using the overpass API. Different OSM objects can be plotted in different colours using the function add_osm_objects().  The function group_osm_objects() enables customised highlighting of selected regions using different graphical schemes designed to contrast with surrounding backgrounds.

[added by @richfitz:

Package: osmplotr
Title: Customisable Images of OpenStreetMap Data
Version: 0.1-2
Date: 2016-03-01
Authors@R: person("Mark", "Padgham", email = "[email protected]", role = c("aut", "cre"))
Description: Produces customisable images of OpenStreetMap data.  Extracts OpenStreetMap data for specified key-value pairs (e.g.  key="building") using the overpass API. Different OSM objects can be plotted in different colours using the function add_osm_objects().  The function group_osm_objects() enables customised highlighting of selected regions using different graphical schemes designed to contrast with surrounding backgrounds.
Depends: R (>= 3.2.3)
Imports: 
    ggm,
    igraph,
    httr,
    methods,
    osmar, 
    rgeos,
    sp, 
    spatstat, 
    XML,
Suggests: knitr,
    roxygen2,
    rmarkdown,
    devtools,
    maptools,
    RColorBrewer
License: GPL-3
URL: https://github.com/mpadge/osmplotr
LazyData: true
VignetteBuilder: knitr

]

• 1. URL for the package (the development repository, not a stylized html page)
     github
• 1. What data source(s) does it work with (if applicable)?
     OpenStreetMap
• 1. Who is the target audience?
     Anyone working in the built environment wanting to improve data visualisation
• 1. Are there other R packages that accomplish the same thing? If so, what is different about yours?
     No there are not. "openstreetmap" merely pulls straight raster images that are definitely not customisable at all. "osmar"---on which "osmplotr" depends---does provide plot methods, but these are very restricted and not able to be customised any further. "tmap" provides customisable spatial visualisations, but only uses OSM data directly from the "OpenStreetMap" package, which yields a direct OSM-style raster file that is not customisable. (tmap is also not on git nor any other open repo.)

In short: This is the only package that allows OpenStreetMap data to be presented in a visually customisable way.

• 1. Check the box next to each policy below, confirming that you agree. These are mandatory.
  • [y] This package does not violate the Terms of Service of any service it interacts with.
  • [y] The repository has continuous integration with Travis CI and/or another service
  • [y] The package contains a vignette
  • [y] The package contains a reasonably complete README with devtools install instructions
  • [n] The package contains unit tests
  • [y] The package only exports functions to the NAMESPACE that are intended for end users
• 1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
  • [n] Are there any package dependencies not on CRAN?
  • [y] Do you intend for this package to go on CRAN? It already is
  • [y] Does the package have a CRAN accepted license?
  • [n] Did devtools::check() produce any errors or warnings?
• 1. Please add explanations below for any exceptions to the above:
     Most package functionality is already tested in the vignettes, and thus there are currently no unit tests. The most important way to test the package is to use it to extract strange kinds of OpenStreetMap data -- not something that can be performed with any inbuilt tests. I plan to incorporate tests once I hear of strange behaviour, but can not pre-empt what this might be.
• 1. If this is a resubmission following rejection, please explain the change in circumstances.