To mark the launch of the DSC and celebrate all the data-driven research done at the UvA, we are hosting the inaugural Data Science Day. This will include workshops, pitch presentations and a keynote from Suzy Moat, Professor of Behavioural Science and Co-director, Data Science Lab at Warwick Business School. Register now to attend the workshops or afternoon event.
|Date||7 October 2021|
The inaugural Data Science Day will be a hybrid event, taking place at the Allard Pierson Museum and online via Hopin. The event is hosted by the Data Science Centre (DSC), part of the University Library.
Registration is now open for the workshops and the afternoon event.
Data Science Day – 7th October
|- Morning Session -|
|- Afternoon Session -|
Introduction to Data Science Day
by Paul Groth, Scientific Director of the DSC
How the UvA supports data research
By Max Haring, Head of Library Academic Support, University Library
Colleagues from across the UvA will showcase the work they are doing with the help of data science.
By Suzy Moat, Professor of Behavioural Science and Co-director, Data Science Lab at Warwick Business School
Suzy Moat is Professor of Behavioural Science at Warwick Business School, where she directs the Data Science Lab with her colleague Tobias Preis. She is also a Fellow of The Alan Turing Institute.
Moat's research investigates whether data on our usage of the Internet, from sources such as Google, Twitter, Wikipedia and Instagram, can help us measure and predict human behaviour.
Her work touches on problems as diverse as generating rapid indicators of disease spread, estimating crowd sizes, and evaluating whether the beauty of the environment we live in might affect our health and happiness.
The results of her research have been featured by television, radio and press worldwide, by outlets such as BBC, CNN, The Guardian, The Economist, New Scientist and Wired. Moat also acts as an advisor to government and public bodies on related topics.
Two workshops will showcase the latest research being enhanced by data science across the UvA. The workshops are open to all UvA PhD students and employees. Lunch will be included. There are limited places available for the workshops so register now!
In order to host this event in line with government regulations, we will be using the CoronaCheck app. Therefore it is necessary to provide proof of a negative test result or a vaccination certificate or proof that you have recovered from corona and valid ID.
In recent years, network analysis has been applied to identify and analyse patterns of statistical association in multivariate psychological data. In these approaches, network nodes represent variables in a dataset, and edges represent pairwise conditional associations between variables in the data, while conditioning on the remaining variables. This workshop provides an anatomy of these techniques, describes the current state of the art, and demonstrates the use of these techniques in the open statistics JASP software developed at the UvA.
Pre-requisites for attendees
No special prerequisites are needed. Workshop participants can bring their own data and download JASP prior to the workshop, so they can apply the methodology to their own dataset. Participants who do not have their own data can use an example dataset that is included with JASP.
Faculty of Social and Behavioural Sciences
Programme group Psychological Methods
This workshop will introduce you to open data science using R, RStudio and GitHub so you can work with data in an open, reproducible, and collaborative way. “Open data science” means that methods, data, and code are available so that others can access, reuse, and build from it without much fuss. Here you will learn a workflow with R, RStudio, git and GitHub.
This is going to be fun, because learning these open data science tools and good practices is empowering. In this workshop, we will cover the basics of literate programming with R Markdown, create publication-grade graphs with ggplot2 and see how you can collaborate with your most important collaborator: you!
RStudio virtual machines will be set up in the cloud before the workshop to make sure everything has access to datasets and required R packages.
Pre-requisites for attendees
No prior knowledge is required although some prior experience with R and RStudio would help to follow along.