trackeRapp (version 1.1)

trackeRapp: Launch the trackeRapp interface

Description

trackeRapp provides an integrated dashboard and workflow for the analysis of running, cycling and swimming data from GPS-enabled tracking devices through the trackeR R package. trackerRapp or trackeR_app launches the interface.

Usage

trackeRapp(quiet = TRUE)
trackeR_app(quiet = TRUE)

Arguments

quiet

If TRUE (default), then warnings and errors while using the interface are printed in standard output. If FALSE, then all warnings and errors are suppressed.

Getting started

Once the interface launches, you may experiment with the interface by hitting "Load" and then "Upload sample dataset".

See the "tour de trackeRapp" pages at https://trackerproject.github.io/trackeRapp/ for tutorial videos, explanation of the workflow and visualizations that trackeRapp offers, and to, generally, learn more about trackeRapp and all of its capabilities.

Video channel

trackeRapp has a dedicated YouTube channel at https://www.youtube.com/channel/UCY6y-pw8d1kek1WAIWiVhhw. The channel features video tutorials about trackeRapp and the workflow it provides.

Development notes and acknowledgements

trackeRapp has been designed and developed by Robin Hornak and Ioannis Kosmidis, while Robin Hornak was completing his undergraduate research project in the Department of Statistical Science, University College London under the supervision of Ioannis Kosmidis. Ioannis Kosmidis has been supported by the Alan Turing Institute under the EPSRC grant EP/N510129/1 (Turing award number TU/B/000082) and University of Warwick. Robin Hornak and Ioannis Kosmidis have also been supported by University of Warwick through a Warwick Impact Fund Award that runs from May 2018 to December 2019. The support of the aforementioned organizations is greatly acknowledged.

References

Frick, H., Kosmidis, I. (2017). trackeR: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices in R. Journal of Statistical Software, 82(7), 1--29. doi:10.18637/jss.v082.i07

Kosmidis, I., and Passfield, L. (2015). Linking the Performance of Endurance Runners to Training and Physiological Effects via Multi-Resolution Elastic Net. ArXiv e-print arXiv:1506.01388.

Examples

# NOT RUN {
if (interactive()) {
  trackeRapp(quiet = TRUE)
}

if (interactive()) {
  trackeR_app(quiet = FALSE)
}

# Experiment with the interface by hitting "Load" and then
# "Upload sample dataset".

# }