How to foster healthcare research thanks to semantic graph technology for data integration

In this talk, we present the challenges for data interoperability of the Swiss Personalized Health Network and describe how the Lausanne University Hospital in collaboration with Trivadis is contributing to address them through the use of graph-based data integration technologies. Graph based technologies can enable hospitals to have a unified and flexible view of their own data (currently stored in heterogeneous data silos) and perform quick and intuitive queries for a number of activities ranging from medical research to health quality measurements.

Zum Video: https://bbb.ch-open.ch/playback/presentation/2.0/playback.html?meetingId=3d633380f46ae77fefa9179b8e3151f35dc0866f-1603452355419

Weitere Informationen

The digitalization of medicine and the advancement of techniques from data science and artificial intelligence (AI) are revolutionizing healthcare and promise better diagnoses and more personalized treatments. Yet, the lack of data standardization across different medical datasets within and across institutions hinders the broad application of these techniques in medicine. In this talk, we present the challenges for data interoperability of the Swiss Personalized Health Network and describe how the Lausanne University Hospital in collaboration with Trivadis is contributing to address them through the use of graph-based data integration technologies. Graph based technologies can enable hospitals to have a unified and flexible view of their own data (currently stored in heterogeneous data silos) and perform quick and intuitive queries for a number of activities ranging from medical research to health quality measurements.

Ablauf der Session

– Swiss Personalized Health Network (SPHN): challenges and goals

– Data interoperability in SPHN:  a sustainable and flexible strategy based on three pillars (standard-agnostic semantics framework, formal descriptive language, data models)

– Challenges for hospitals related to the transformation of data from conventional relational data models into semantic-graph-based representation  

– Solution implemented by CHUV (with the help of Trivadis) based on Oracle Spatial and Graph, RDF and Protégé

– Outlook to the near future: using graph-based technology to unify CHUV data for research and facilitate compliance with the FAIR data principles (Findable, Accessible, Interoperable, Reusable)

Zielgruppe

People interested in Knowledge Graph and their possible use cases. No special IT knowledge is required.

Träger-Organisation

Trivadis
https://www.trivadis.com/de/
vincent.gremaud@trivadis.com