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presubmission request for R package RAQSAPI v2.0.5 #712

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@mccroweyclinton-EPA

Description

@mccroweyclinton-EPA

Submitting Author Name: Clinton Mccrowey
Submitting Author Github Handle: @mccroweyclinton-EPA
Version submitted: 2.0.5
Repository: https://github.com/USEPA/RAQSAPI
Submission type: submission
Language: en


Retrieve air monitoring data and associated metadata from the US
Environmental Protection Agency's Air Quality System service using functions.
See https://aqs.epa.gov/aqsweb/documents/data_api.html for details about
the US EPA Data Mart API.


Scope

  • Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check one or more appropriate boxes below):

    Data Lifecycle Packages

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

    Statistical Packages

    • Bayesian and Monte Carlo Routines
    • Dimensionality Reduction, Clustering, and Unsupervised Learning
    • Machine Learning
    • Regression and Supervised Learning
    • Exploratory Data Analysis (EDA) and Summary Statistics
    • Spatial Analyses
    • Time Series Analyses
    • Probability Distributions
  • Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
    RAQSAPI is a R package that was designed specifically as a simple interface to the US Environmental Protection Agency Air Quality System Data Mart API which is a data store of ambient air pollution data collected by EPA, state, local, and tribal air pollution control agencies from over thousands of monitors. AQS also contains meteorological data, descriptive information about each monitoring station (including its geographic location and its operator), and data quality assurance/quality control information.

  • If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?

  • Who is the target audience and what are scientific applications of this package?
    Environmental scientists and data scientist

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

aqsr, RAQSAPI is still under active development and will be updated reflecting future changes to the AQS Data MART API. RAQSAPI is developed by EPA staff. RAQSAPI allow for multi year data pulls. Also RAQSAPI is the only package that I am aware of that is available from CRAN.

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