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    <title>swimming on Ioannis Kosmidis</title>
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    <description>Recent content in swimming on Ioannis Kosmidis</description>
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      <title>trackeRapp: interface &amp; workflow for running, cycling and swimming data</title>
      <link>http://www.ikosmidis.com/post/news-trackeRapp-is-out/</link>
      <pubDate>Fri, 12 Apr 2019 00:00:00 +0000</pubDate>
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      <description>🏃‍♀️🚴‍♂️🏊‍♀️&#xA;The first version of our trackeRapp R package is out!&#xA;trackeRapp provides the first fully interactive data analysis workflow for your runs, rides and swims! It is completely open source and written in R. Its backend is based on the trackeR R package and the frontend has been developed using the shiny R package.&#xA;To launch the trackeRapp interface locally, launch R and then&#xA;install.packages(&amp;quot;trackeRapp&amp;quot;) trackeRapp::trackeRapp() Then, hit “Load” and “Upload sample data set” to see what {trackeRapp} can do!</description>
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      <title>trackeR v1.1 is on CRAN</title>
      <link>http://www.ikosmidis.com/post/tracker-v11/</link>
      <pubDate>Mon, 24 Sep 2018 00:00:00 +0000</pubDate>
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      <description>The trackeR R package v1.1 is on CRAN. Version 1.1 of the package introduces full support for multi-sport workouts, numerous new visualisations, vast under-the-hood enhancements, bug fixes and more.&#xA;See NEWS for complete lists of new functionality, enhancements and bug fixes.&#xA;The package vignette provides a quick tour on its functionality. More detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality can be found here, which is an updated version of</description>
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      <title>trackeR paper appears in JSS</title>
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      <pubDate>Tue, 12 Dec 2017 00:00:00 +0000</pubDate>
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      <description>trackeR: Infrastructure for running and cycling data from GPS-enabled tracking devices in R (joint work with Hannah Frick) appeared online in the Journal of Statistical Software.</description>
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