Semantic Web Japan, Personalized Medicine, and Knowledge Explorer

I recently had the good fortune of being invited to give a keynote at the Japanese Semantic Web conference, held at Keio University in beautiful city of Tokyo, Japan. The speaker before me, Tetsuro Toyoda, described how Semantic Web was being used at RIKEN (The Institute of Physical and Chemical Research). Many of these interesting activities can be found at RIKEN database, such as Semantic-JSON and Semantic Table. There was a healthy showing of commercial interest present at the conference, as well as a demonstration of a (Japanese) medical terminology system that made use of OWL and could provide English translations. I wish our Japanese colleagues a quick recovery from the recent earthquake and tsunami. Although Tokyo was not hit as hard as other areas, it has still been severely affected, with power blackouts causing many delays in a return to normality.

After Tokyo, I traveled to beautiful city of Vancouver to speak at the Best Practices in Personalized Medicine Workshop, which was held as part of the Heart + Lung Research & Education FEST. The Semantic Web session where I spoke also had nicely complimentary talks from Xavier Lopez (Oracle) and Mark Wilkinson (UBC). At B2PM, Leroy Hood opened with a keynote expanding on P4 – his description of a new approach to medicine that is “powerfully predictive, personalized, preventative — meaning we’ll shift the focus to wellness — and participatory” and described recent progress. B2PM attendees presented and discussed how to achieve the goals of personalized medicine. Many participants have expressed interest in making use of the established network to further the cause of personalized medicine.

I have been learning about the Sentient Knowledge Explorer from IO Informatics. Knowledge Explorer has some very useful features and functionality that includes the generation of SPARQL queries from user selected sub-networks without requiring knowledge of SPARQL. A full description can be found at the W3C use case description “Case Study: Applied Semantic Knowledgebase for Detection of Patients at Risk of Organ Failure through Immune Rejection”.

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