Exploring data has always been at the core of science, but new tools are paving the way to better sense-making –  and we’re at the forefront. 

Data volume and complexity are exploding, and interpreting data to gain more insights and draw conclusions is becoming more and more challenging. Applying AI in data analytics today is more common than ever, but there are still substantial challenges. To meet these, traditional ‘big data’ analytics approaches will need to be combined with AI in novel ways. For instance, it’s important to avoid bias, to understand how and why AI classifies data, and how and why it reaches specific conclusions, among other pressing questions. 

The eScience Center works on these questions, with a particular focus on developments currently emerging in applied AI, visual analytics, computer vision, data mining, statistics, natural language processing and time series analysis. 

Talking about a revolution; we can’t wait to see what is unveiled as we move ahead.

See how we brought data to life in the Case Law App, a network analysis tool for legal research.