International Semantic Web Conference (ISWC) 2018


We present an end-to-end approach that takes unstructured textual input and generates structured output compliant with a given vocabulary.

We address the problem of characterizing breast cancer, which today is done using staging guidelines. Our demo will show different breast cancer staging results that leverage the Whyis semantic nanopublication knowledge graph framework [8].

To investigate the cause and progression of a phenomenon, such as chronic disease, it is essential to collect a wide variety of data that together explains the complex interplay of different factors, e.g., genetic, lifestyle, environmental and social.

We will demonstrate a reusable framework for developing knowledge graphs that supports general, open-ended development of knowledge curation, interaction, and inference. Knowledge graphs need to be easily maintainable and usable in sometimes complex application settings.