On Thursday 7th October, the Data Science Centre (DSC) hosted the inaugural Data Science Day event. The hybrid event took place at the Allard Pierson Muesum with over 130 people attending online and in-person. 

Morning workshops  

The day started with two morning workshops led by Denny Borsboom and Marc Galland.  

Workshop 1: Network approaches to multivariate data 

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 provided an anatomy of these techniques, describes the current state of the art, and demonstrated the use of these techniques in the open statistics JASP software developed at the UvA. 

Workshop 2: Open Science with R 

This workshop introduced open data science using R, RStudio and GitHub, enabling participants to 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.  

Both workshops included participants from six out of the seven faculties at UvA, demonstrating that data science techniques can be applied to all domains and areas of research. 

Afternoon Event 

Supporting Data-Driven Research at UvA 

The afternoon was kicked off by Paul Groth, scientific director of the DSC and Max Haring, head of the research and teaching support team at the Library UvA-HvA. As core members of the DSC team, they discussed the aims of the DSC and how the Library plays a pivotal role in supporting data-driven research 

Artificial Intelligence for Scientific Discovery 

Bernd Ensing, director of the AI4Science Laboratory, gave a talk on the lab, a multidisciplinary initiative in the Faculty of Science launched in the summer of 2019. The lab aims to connect experts of AI and machine learning with researchers in all fields of science. Bernd discussed what they have learned so far and what exciting opportunities the future holds. 

Data-Driven Research Right Now - Pitch Presentations 

10 researchers from five different faculties at UvA had three minutes to present the data-driven research they are doing right now, showcasing how data science is enabling them to level up their research. 

• Joanna Strycharz 
  Digital vulnerabilities and targeting 

• Marc Galland
  Data science goes green 

• Thomas van Binsbergen 
  Designing systems to support data science and data management 

• Tessa Blanken 
  Big behavioural data: Behavioural data-science solutions to COVID-19 

• Leon van Wissen 
  Data-driven research in the Faculty of Humanities 

• Anna Keuchenius 
  The Computational Social and Behavioural Science Community

• Pim van Ooij 
  Clinical implementation of artificial intelligence technology in radiology 

• Dick den Hertog 
  Analytics for a Better World 

• Susanne Baumgartner 
  Smart Tracking

• Frans van der Kloet 
  How neural networks can be used when fitting biological systems/data 

Keynote: Understanding beautiful places and wellbeing with AI 

Suzy Moat, Professor of Behavioural Science and Co-director, Data Science Lab at Warwick Business School gave the keynote address. Suzy'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. 

In her keynote address, Suzy explored the question of whether beautiful environments are good for our health and happiness? She described how millions of ratings from an online game called ‘Scenic-or-Not’ and a mobile app called ‘Mappiness’ have begun to offer new answers to this age-old question. Suzy explained how deep learning can help us understand whether beautiful places are simply natural places - or whether humans might be able to build beautiful places too. 

You can watch all the talks from the afternoon event below.