About the programme

In the morning programme, you'll gain an understanding of the principles of data visualisation and storytelling, applying them to craft effective visual representations. In the afternoon programme, you'll discover how to easily build interactive visualisations and dashboards using Python panel, and how to make them accessible online. By the end of the workshop, you will be able to create powerful storytelling visuals with your own research data.
You can join for the full day, or the morning programme only. The workshop is in English.

Programme

Morning programme
Please note: no prior knowledge is required

09.30 - 10.30: Principles of data visualisation; and drafting visualisation
10.45 - 12.30: Data storytelling; and refining visualisation
12.30 - 13.00: Lunch break

Afternoon programme
Please note: basic familiarity with Python is required

13.00 - 14.00: Interactive visualisations and dashboarding in Python
14.15 - 15.15: Develop your own  dashboard in Python(panel + hvPlot) to visualise.
15.30 - 16.00: Deploying dashboards without servers (Pyodide)

Plenary instruction is combined with hands-on practice with your own datasets in small groups.  The workshop will cover different packages for interactive visualisations and dashboarding in Python, focusing mostly on the HoloViz (panel, hvplot, etc) ecosystem. You will learn how to run panel apps directly in the browser via pyodide (no server required). 

Preparation

Please note: preperation is only required for the afternoon session. 
Bring your own laptop. We encourage you to bring your own datasets to the workshop. If you want to work with your own data, you will be asked to send the following information at least two days prior to the workshop:

• Dataset: (one/two sentences description of the data)
• Level of analysis: (what do the rows represent)
• Number of observations: (number)
• What is a main message you'd like to convey with the data: (no need to be linked to a research question) (e.g. there is a difference between treatments a and b, variables x and y are correlated, etc.)
• Important variables: (name + optional description)

Workshop instructor

Dr. Javier Garcia Bernardo (Universiteit Utrecht) 
Assistant Professor, ODISSEI Social Data Science Team.

Registration

It is possible to attend only the morning programme. The morning session is open to everyone – no prior knowledge is required.
Interested in joining for the full day? Please note that the afternoon programme requires some familiarity with Python. This workshop is free of charge and open to all researchers at UvA. Interested MA students are also welcome. Lunch, coffee and tea is included. If you have any questions about the workshop or need to cancel your registration, please contact us at dsc@uva.nl.