Professional Motorsport Data Analysis: Conventions
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Conventions
05.03
| 00:00 | - Dealing with large amounts of data can become unnecessarily complicated and cumbersome which is the last thing we need when we're on a time crunch during a race weekend. |
| 00:10 | To help with this, conventions are used to keep things consistent, speeding up our work and allowing us to always speak the same language. |
| 00:18 | Simply put, we can think of conventions as small rules we follow when we're building up and working on our data analysis project. |
| 00:27 | At first, some of these conventions may seem a little over the top or unnecessary but I promise you that if you make an effort to stick to them now, in time you'll be thankful you did. |
| 00:38 | Especially once the analysis becomes more sophisticated. |
| 00:42 | A lot of these conventions will already be set up before we even get to analysing the data but others you'll need to set up as you go. |
| 00:50 | Ultimately as a data engineer, you're free to use whatever conventions you like but the real key here is that they just need to be consistent. |
| 01:00 | Without establishing that consistency from the outset, you're going to find yourself with a problem sooner rather than later. |
| 01:07 | In this module we're going to go over some of the most widely followed conventions in the motorsport industry. |
| 01:13 | Which is going to give you a good understanding of the basics. |
| 01:16 | Before we start though, let's take a look at the conventions cheat sheet which you can download from the related resources area underneath this video. |
| 01:25 | This is a handy summary sheet that you can keep nearby as a quick reference as you build up your analysis project. |
| 01:31 | First let's take a look at the convention we'll be using for the coordinate system of the car. |
| 01:36 | Positive directions are indicated by the direction of the arrows so X is in the direction of the car travel, Y is lateral to the direction of travel and Z is the vertical direction. |
| 01:48 | In line with our coordinate system convention, when the car is turning left, we define that as positive. |
| 01:55 | This means that when we're looking at the steering trace, positive values are for when the car is turning left and negative values of the steering trace show the car turning right. |
| 02:04 | Again referring to our coordinate system, when dealing with lateral G forces, positive is for the G force we have when the car is turning left and negative is for the G force we have when the car is turning right. |
| 02:17 | For longitudinal G force, positive shows acceleration and negative represents braking. |
| 02:24 | Next let's take a look at the use of colour. |
| 02:26 | Colour can be an incredibly useful tool in helping communicate features in the data. |
| 02:31 | One of the basic ways to use this is to show which part of the car the data relates to. |
| 02:37 | Once you're used to working with these colours and have stuck to some conventions the entire time, it means you don't have to look at the display legend constantly to remind yourself what colour represents what variable. |
| 02:50 | In this example, we see how when you're dealing with a quantity that has one channel for the front and one for the rear, like front and rear brake pressure, then we assign red to the front and blue to the rear. |
| 03:02 | We can apply the same convention to any other data source that has a front and a rear. |
| 03:07 | In the case where we have a quantity that relates to one corner of the car, for example tire pressure, then this is how we would assign the colours. |
| 03:16 | Here we're simply assigning red to the front left, green to the front right, blue to the rear left and yellow to the rear right. |
| 03:25 | You should use these colour conventions when you first set up your data analysis project or build a new math channel. |
| 03:31 | You're free to use whatever conventions make the most sense to you, whether that's to do with which values are positive or negative or if it's to do with the colours you want to use. |
| 03:41 | I just encourage you to use a system, apply it throughout your data analysis project and stick to it. |
| 03:47 | This should give you a basic understanding of some common conventions and how they're used. |
| 03:52 | But before we move on, I want to bring up just how crucial it is to be consistent when naming your logs and math channels. |
| 04:00 | It's hugely helpful for readability and organisation as things become more and more complex and of course this applies to both setting up your logger as well as your data analysis software. |
| 04:12 | Personally the way I like to do this is simply start with the element of the car, then the measurement type and then the position on the car. |
| 04:21 | So for example if I was setting up the logger, I would use channel names like damper position, front left or brake pressure rear. |
| 04:30 | To keep your channel names short it also helps to come up with some standard abbreviations for commonly used terms. |
| 04:37 | Here are some abbreviations for position on the car, pressure, position of the measurement and temperature that will help keep your channel names short. |
| 04:47 | Again, all of these examples show just one way to do it and there's nothing to say you need to follow it exactly if it doesn't work for you. |
| 04:55 | Use whatever is the most logical and readable for you, just be consistent. |
