1. Open data in teaching and education
Juha-Matti Teuho & Linda Hemmann
Welcome to Open Data workshop. Before the actual workshop part, we would like to say a few words about using the open data in teaching and education.

2. Open data Anyone can access, free to use and share
Why should we use it in education?
How can we use it?
First of all, what is open data?
It is the kind of data that anyone can access and it is free to use and share. So the question is, how can we use open data in teaching and education? And why should we use it? Hopefully after this workshop we have answered to these questions!
High-school students analysing CMS open data. Photo credit: Marzena Lapka

3. Benefits of using open data
Open data is everywhere
Bring real scientific data to schools
Link between classrooms and recent research
Make students enthusiastic about science
It is easy to use!
Let’s begin with the benefits of using open data.
First of all, open data is everywhere. It is produced by companies, governments and organisations so there is a huge amount of open data from various fields on the internet to be explored and used in teaching.
From the physics point of view, you can use data from such experiments that couldn’t be done in a classroom environment. For example the CMS experiment produces open data for educational use, which is great since we can use actual scientific data from latest research to be used in classroom. Therefore open data acts as a link between classrooms and recent research.
This way the students get to play with real data, which can even make students more interested in science and physics.
Also, if you have the right tools, it is easy to use and analyse open data.

4. How can we use open data in education?
Data-analysis
Programming, spreadsheet, other software
Jupyter Notebooks and programming
Tools are scientifically valid and widely used
How can we use open data in education then?
Open data is easily accessible but one has to know how to analyse it. There are plenty of option for data-analysis such as programming, spreadsheet and other kinds of software..
For data-analysis, our main tools are Jupyter Notebooks. They are interactive notebooks, which combine traditional text, code and graphs. So the Notebooks are actually just a platform for our data-analysis and the actual analysis and plotting is done with Python-programming.
By the way, how many of you have tried programming before using Python or some other language?
Python is a very straightforward programming language, which has great opportunities for data-analysis and it is easy to start with if you don’t have any experience on programming yet.
Currently we are making teaching material using open data from the CMS project. This material includes particle physics theory and data-analysis exercises with open data. We are also working on other material than particle physics.
Other benefit of these tools is that they are not only for our purposes. They are actually widely used in the scientific community.

5. Other possibilities Visualize collisions using CMS event display
Collect your own data (e.g. Phyphox)
We can also use other kind of tools in addition to Jupyter Notebooks and Python.
For example the CMS event display is a cool way to view collisions and try to figure out which particles were created in a collision.
Another interesting possibility is to collect the data yourself. Students can download Phyphox app on their phone. Phyphox turns your device into a laboratory. A smartphone has many kinds of sensors which can be used to collect data. You can see some of the sensors in the figure. The data can then be easily transferred to a computer for further analysis. We are currently making teaching material where this app is used.

6. Workshop Today we use MyBinder because no software installation needed
no need to create an account
handy tool in classroom
easy to share and open for everyone
Let’s try out one of our exercises!
Open the demo exercise on MyBinder here and follow the instructions on the notebook
Let’s get to the workshop part then.
In this workshop we are going to use MyBinder, which is this online platform where you can manipulate Jupyter Notebooks.
The reason we are using MyBinder is that you don’t have to install anything on your computer or create any accounts. This is why it is also really useful in classroom, since there is no need to install anything on the student computers.
Also the notebooks are easy to share via MyBinder.
So, let’s hop on to the workshop part then!
In this exercise you will learn how to use Notebooks and Python to create a histogram of the invariant mass of two muons created in a collision. You’ve probably heard of the invariant mass on the previous lectures.
So, please follow the link on the slides to open the exercise notebook in MyBinder. You can find the link also on the Indico page. The link is called “Workshop”.
After you’ve opened the link, wait for the notebook to load and follow the instructions on the notebook.
If you have any questions now or during the workshop, just ask us or Kati behind you and we will come and help you.

7. Questions? Got interested? Have these tools been tested in classroom?
Where and how can you use them
How to create your own materials
Instructions and teaching material
Questions?
Ok, we’re running out of time. You may have some questions about this project so here are answerrs to some questions.
Have these tools been tested in classroom?
Yes they have and the feedback from the students have been really positive.
How can you use these materials?
You can find all the material behind a link called “material” in Indico.
Feel free to use it and modify it if you like. Any improvement suggestions and other kind of contributions are apprciated.
Currently it might be a little hard to navigate through that material so if you have any trouble, you can contact us and we’ll figure it out.
How can you create your own materials?
There are plenty of tutorials how to use Python and Jupyter and there is quick instructions on those on our material as well.
Here is also a link for the material repository.
Ok, that’s all. Thanks for listening. Do you have any questions?