Driving Scientific Discovery through Machine Intelligence

We’re developing an integrated knowledge graph for research. This model allows machines to identify and understand insights in unstructured data, such as articles, compared to today’s information about it.

The Discovery Lab studies technology, infrastructure and methods to develop intelligent services for researchers, focusing on finding and interpreting scientific literature, to formulate hypotheses, and to interpret data. The lab operates at the crossroads of Knowledge Representation, Machine Learning and Natural Language Processing. We are advancing the ability to construct, use and study large-scale research knowledge graphs that integrate knowledge across heterogeneous scientific content and data. This will allow for a deeper, richer use of content and data across a larger span of domains than possible thus far, and enables us to grow the knowledge graph faster and more reliably, and provide better recommendations, more contextual question answering, more successful query construction, and the automatic generation of hypotheses. In other words: to drive scientific discovery using machine intelligence.

The Discovery Lab is an ICAI lab, funded by Elsevier, Vrije Universiteit Amsterdam and the University of Amsterdam, and supported by a PPS (Publiek-Private Samenwerking) subsidy from the Dutch government.