Webinar Summary

Data for drug discovery and healthcare is often trapped in silos which hampers effective interpretation and reuse. To remedy this, such data needs to be linked both internally and to external sources to make a FAIR data landscape which can power knowledge graphs and semantic models.

This webinar will describes how data generation for drug discovery begins with the identification of targets and finishes, often over a decade later, as a submission to the FDA. Between discovery and submission, data has to effectively move across disciplines, research activities and laboratories. However, across these different stages of research, data is often not linked, making it challenging to interpret and reuse effectively. So how can we link data both internally and to external sources and thus make our landscape more FAIR? We can use knowledge graphs and semantic models!

About the Speaker

Ilaria is a Data Engineer at The Hyve, specialising in Semantic Modelling and Knowledge Graphs with applications in healthcare and drug discovery. As a mathematician by training, Ilaria came to the bioinformatics field through her interest in the intersection of biology, mathematics and engineering. In her free time, she tries to get away from her computer, and enjoys cooking and spending time outside.

This on-demand webinar is part of the FAIR Webinar Series. For more information about the Pistoia Alliance’s FAIR Implementation project, please contact us.

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