trackeRapp: A shiny dashboard for the analysis of running, cycling and swimming data
trackeRapp builds on the extensive infrastructure provided by the trackeR R package to provide a user-friendly web-interface of an integrated workflow for the analysis of running, cycling and swimming data from GPS-enabled tracking devices. The interface offers a range of flexible interactive visualisations and data-analytic tools.
trackeRapp offers functionality to import, clean and organise data from raw activity files of popular formats (tcx, gpx, json and db3) in a structured R object, and finally to export that object so that it can be used for future analyses not only within trackeRapp but also for more advanced modelling in R.
Contest submission links
| RStudio Cloud | shinyapps.io | GitHub |
Authors
Robin Horňák, Rakuten, Japan
| GitHub | LinkedIn |
Ioannis Kosmidis, University of Warwick & The Alan Turing Institute, United Kingdom
| Homepage | Twitter | GitHub | LinkedIn |
Contact
For wishes, issues and 
s visit trackeRapp's GitHub page. Feel free to also watch/fork the project. You can also email us directly at trackerproject@outlook.com
Installation
The development version of trackeRapp can be installed directly from GitHub by doing
# install.packages("devtools")
devtools::install_github("trackerproject/trackeRapp", ref = "develop")
Launching the user-interface
The web-interface can be accessed remotely at trackerapp.com or on a local machine after installing the trackeRapp package:
# Load the package
library("trackeRapp")
# Open the interface in the browser
trackeRapp()
Then, you can just upload your own activity files or just hit Load to play with some sample activity data.
Getting started
See the tour de trackeRapp pages 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. The channel features video tutorials about trackeRapp and the workflow it provides.
Screenshots
Development notes and acknowledgements
trackeRapp has been designed and developed by Robin Horňák and Ioannis Kosmidis, while Robin Horňák 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 and University of Warwick. Robin Horňák 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 organisations is greatly acknowledged.