It marks the start of many doctoral programmes, and a considerable challenge for all sorts of researchers: the systematic review. This type of structured literature research takes up a great deal of time and manpower. However, there is hope on the horizon: the new machine learning-based Automated Systematic Review application can save researchers a great deal work. The technical side of things is already up and running - the developers recently won the Victorine Initiative award in recognition of their work. The next step for the team is to make the programme suitable for end users.
You wouldn't necessarily expect to see them all together at the same table: software developers, information specialists from the university library and researchers from various faculties. But here they are, hunched over their overworked laptops in the new ASReview Innovation Lab at Bolognalaan 101 to test the new software in the spirit of real cooperation. How's the installation process going? Can you enter search queries and import files? How user-friendly is the front end? Crucially, the researchers have asked the testers to share their 'light-bulb moments' and frustrations.
The test marks a tense and exciting moment. It was only two years ago that professor of Statistics Rens van de Schoot turned to Associate Professor Daniel Oberski in despair and blurted out: 'I'm doing a selection from tens of thousands of sources; can't we get a machine to do that?' Daniel, who works in the Applied Data Science research focus area, couldn't see why not. The two men submitted a successful application to the Research IT innovation fund. Information and Technology Services (ITS) decided to allocate two engineers to the project, who then succesfully developed a learning programme. Rens: 'As a researcher, I now only have to review 5-10 % of the sources. I mark each title 'yes' or 'no' to indicate whether it's relevant to my research project. The machine then starts learning right away and gains a better understanding of what I'm looking for at every iteration. Once I've helped it get started, the computer will automatically screen the other 90-95%.'