UvA wants all faculties to be able to work with data
If it were up to Rector Peter Paul Verbeek, every UvA researcher would have to be able to work with large databases. Starting Monday, September 25th, the UvA Library will therefore start a four-day programming course for researchers to brush up on the necessary knowledge. “Science can no longer do without the use of data.”
Many students deliberately choose a degree in the humanities just to avoid too much exposure to mathematics. For them, Rector Peter-Paul Verbeek’s new ambition may come as a shock: All faculties must be able to handle large data sets. Or in Verbeek’s words: “Science can no longer do without the use of data.”
The Data Science Center was created to teach these skills. Part of the university library, the center helps scientists and master’s students use data in their research.
That can be quite diverse, as data science is an umbrella term for all methods used to extract knowledge from data sets. “This can involve analysis to discover patterns or methods to create predictive models,” explains Eva Lekkerkerker, digital skills coordinator at the University Library. “Those patterns and models can lead to a deeper understanding of the world. And with that knowledge, you can better inform policy.”
In the natural sciences and psychology, the use of statistics may be more obvious, but the humanities also benefit from data science, according to Lekkerkerker. “There it often involves text recognition. With artificial intelligence, you can perform sentiment analysis to find out what feelings are in a text or detect the dominant themes with topic modeling. You can get through 50,000 documents a lot more easily that way; you can’t read that all at once.”
Thus some students and researchers need to learn additional skills. That’s why Lekkerkerker is running courses at the library: from an introduction to programming - a four-day course that starts Monday, September 25th - to machine learning or statistical analysis. The courses are free; participants just have to bring their own lunch.
Lekkerkerker herself was not a fan of programming at first, but now she actually enjoys it. “Programming is like learning a new language. Compare it to learning Italian on Duolingo, then it’s a little less scary.”
PhD student Yuliia Kazmina already made the switch to data science. She majored in economic policy and now calls herself a computational social scientist. She is working on a huge data project called Popnet, conducting research on segregation based on population register analyses. “Data science used to be an add-on tool. Now it’s the main focus of my work. I continue to ask social science questions, but use data to better answer those questions.”
Using statistics or programming does suit her, but for those who may find it challenging, Kazmina has a tip: “It did get easier. There are also many tools that don’t require you to write the whole programming language yourself but just to click a button that already has code behind it. And, of course, you can always add a data analyst to your research team, although they are hard to find.”
October 13th, 2023 is the annual Data Science Day where leading experts and researchers share knowledge about the latest developments in data science and AI.
