Export all data, including metadata, from a REDCap (Research
    Electronic Data Capture) Project via the REDCap API
    <https://projectredcap.org/wp-content/resources/REDCapTechnicalOverview.pdf>.
    The exported (meta)data will be processed and formatted into a stand alone R
    data package which can be installed and shared between researchers.  Several
    default reports are generated as vignettes in the resulting package.

Encapsulates functions to streamline calls from R to the REDCap
    API.  REDCap (Research Electronic Data CAPture) is a web application for
    building and managing online surveys and databases developed at Vanderbilt
    University.  The Application Programming Interface (API) offers an avenue
    to access and modify data programmatically, improving the capacity for
    literate and reproducible programming.

Convert 'REDCap' exports into tidy tables for easy handling of 'REDCap' repeat instruments and event arms.

Collect  your data on digital marketing campaigns from reddit Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

A collection of tools for extracting structured data from <https://www.reddit.com/>.

Applies quality control to daily precipitation observations; 
    reconstructs the original series by estimating precipitation in missing values; and 
    creates gridded datasets of daily precipitation.

Standard and extensible Eddy-Covariance data post-processing 
  (Wutzler et al. (2018) <doi:10.5194/bg-15-5015-2018>)
  includes  
  uStar-filtering, gap-filling, and flux-partitioning.
  The Eddy-Covariance (EC)  micrometeorological technique quantifies continuous 
  exchange fluxes of gases, energy, and momentum between an ecosystem and the atmosphere.
  It is important for understanding ecosystem dynamics and upscaling exchange fluxes.
  (Aubinet et al. (2012) <doi:10.1007/978-94-007-2351-1>).
  This package inputs pre-processed (half-)hourly data and supports further processing. 
  First, a quality-check and filtering is performed based on the relationship between 
  measured flux and friction
  velocity (uStar) to discard biased data 
  (Papale et al. (2006) <doi:10.5194/bg-3-571-2006>).
  Second, gaps in the data are filled based on information from environmental conditions
  (Reichstein et al. (2005) <doi:10.1111/j.1365-2486.2005.001002.x>).
  Third, the net flux of carbon dioxide is partitioned
  into its gross fluxes in and out of the ecosystem by night-time 
  based and day-time based approaches
  (Lasslop et al. (2010) <doi:10.1111/j.1365-2486.2009.02041.x>).