Welcome to the OpenDataSoft Leadership Podcast Series, “Open Data Discussions”. Each month, Jason Hare, our Open Data Evangelist, features a different…
Weekly Open Data: are SNCF’s TGV trains always late?
We have the pleasure to present you our brand new series « Weekly Open Data». At OpenDataSoft, we love to roam the Internet to find the best datasets there are. We have decided to launch this on-going series with an infographic about TGV trains lateness, based on SNCF (French National Railway Company) regularity barometer published earlier this month.
SNCF made its first move towards Open Data and Open Innovation during 2011. Its Open Data portal data.sncf.com has been powered by OpenDataSoft since 2012 and has allowed the company to share up to 45 datasets.
Today’s story began when our mascot and customer Bruce complained at lunch about high-speed TGV trains being constantly late. Discussion raged in our office for a few minutes. Only listening to our courage, we braced ourselves and decided to investigate the matter. Thanks to the analysis features of our SaaS solution and the open data available at ressources.sncf.com, we have been able to cast some light on this mystery. So, are TGV trains always late?
<div style="clear:both"><a href="https://www.opendatasoft.com/2014/09/24/weekly-open-data-sncf-tgv-trains-late/><img src="http://www.opendatasoft.com/wp-content/uploads/sites/13/2014/09/OPENDATASOFT_REGULARITE_SNCF_EN.png" title="sncf open data" alt="Infographic by OpenDataSoft about SNCF Open Data" border="0" /></a></div ><div style="text-align: center";>Courtesy of: <a href="https://opendatasoft.com/">OpenDataSoft</a></div>
We first looked at the dataset “TGV trains monthly regularity” which compiles possible delays on every TGV. To get a contextual picture of the situation, we compared trains in circulation against those being late for July 2014. This first axis revealed strong differences between trains to and fro the East and the South of France.
Then, we focused on the Lille-Marseille line. A mere click on the « Départ » facet quickly showed that the line incurs more delays than the Lille-Paris or the Lille-Lyon ones.
As Bruce also takes the TGV to go and visit his parents in La Rochelle, we explored this line as well. Looking at the embedded visualization, you’ll see that Bruce will be more subject to delays than travellers going to Poitiers or Angoulême which both are on the same line. A quick search on Google will give us an explanation : SNCF is currently extending the high-speed line from Tours to Bordeaux which causes delays. However, when the high-speed line will be finished, Bruce will save a magnificent 25 minutes on his journey*. Lucky Bruce!
And this is the story of how we proved Bruce that TGV trains are not always late.
Thanks to OpenDataSoft’s analytics features, users can understand complex datasets through interactive visualizations that can easily be embedded in any web page. Maps and graphs will automatically be updated every time the dataset will be modified.
With OpenDataSoft, data speak for themselves…