 |
|
| node: | Bahnmining |
| template: | 4 |
| parent: | .::Berlin::. |
| owner: | blba zena |
| viewed by: | |
| created: | 14.03.2021 - 08:55:30 |
|
cwbe coordinatez: 101 63564 63566 1669122 8852740 ABSOLUT KYBERIA |
| permissions | |
| you: | r, |
| system: | public |
| net: | yes |
total descendants::0
total children::0
1 ❤️
https://media.ccc.de/v/36c3-10652-bahnmining_-_punktlichkeit_ist_eine_zier#t=0
https://www.dkriesel.com/blog/2019/1229_video_und_folien_meines_36c3-vortrags_bahnmining
Since the beginning of 2019, David has systematically saved every single stop of every single train journey at every single long-distance train station throughout Germany. Including delays and all the trimmings. And we'll explore them in a colorful lecture and finally have some fun with data again.
Legal notice: Deutsche Bahn has given written permission to aggregate the raw data it has retrieved and use it for presentations. Agreements on content or even conditions do not exist.
The railway indicates its delays in "percent of punctual trains per month". This is summarized so radically that of course you can't read anything interesting from it. Now imagine if you could take a closer look.
It turns out: It works! David's dataset includes nearly 25 million stops - more than 50,000 per day. We have the raw data and are completely free in our consideration.
The lecture has several common threads again.
1) We measure an almost complete year of long-distance transport for German railways. Here is some expectation management: Sense is by no means rail bashing or sensationalism - anyone who expects a hate speech against the railways is wrong in this event. But we will use the data to get to know the railway a little. The train is a huge machine with millions of moving parts. How many train journeys are there anyway? What are the largest train stations? We will of course also address the unpleasant topics that many are currently interested in: Is the problem with train delays really as bad as everyone says? Are there places and times that are particularly poor? And where do trains simply drop out?
2) There are again several views outside the box , as with David's previous lectures. You will automatically get a generally understandable insight into today's data analysis. (A popular conspiracy theory says that inspiring you to analyze public data would even be the main purpose of David's lectures. :-)) The world needs reasoned people who find analysis more important than screeching. And that is why davod also describes how to approach such a complex hobby project technically, avoid beginners' mistakes, and act responsibly.
https://www.dkriesel.com/blog/2019/1229_video_und_folien_meines_36c3-vortrags_bahnmining
Since the beginning of 2019, David has systematically saved every single stop of every single train journey at every single long-distance train station throughout Germany. Including delays and all the trimmings. And we'll explore them in a colorful lecture and finally have some fun with data again.
Legal notice: Deutsche Bahn has given written permission to aggregate the raw data it has retrieved and use it for presentations. Agreements on content or even conditions do not exist.
The railway indicates its delays in "percent of punctual trains per month". This is summarized so radically that of course you can't read anything interesting from it. Now imagine if you could take a closer look.
It turns out: It works! David's dataset includes nearly 25 million stops - more than 50,000 per day. We have the raw data and are completely free in our consideration.
The lecture has several common threads again.
1) We measure an almost complete year of long-distance transport for German railways. Here is some expectation management: Sense is by no means rail bashing or sensationalism - anyone who expects a hate speech against the railways is wrong in this event. But we will use the data to get to know the railway a little. The train is a huge machine with millions of moving parts. How many train journeys are there anyway? What are the largest train stations? We will of course also address the unpleasant topics that many are currently interested in: Is the problem with train delays really as bad as everyone says? Are there places and times that are particularly poor? And where do trains simply drop out?
2) There are again several views outside the box , as with David's previous lectures. You will automatically get a generally understandable insight into today's data analysis. (A popular conspiracy theory says that inspiring you to analyze public data would even be the main purpose of David's lectures. :-)) The world needs reasoned people who find analysis more important than screeching. And that is why davod also describes how to approach such a complex hobby project technically, avoid beginners' mistakes, and act responsibly.