Webinar Summary

• To position FAIR as a key enabler to automate and accelerate R&D process workflows
• FAIR Implementation within the context of a use case
• Grounded in precise outcomes (e.g. faster and bigger science / more reuse of data to enhance value / increased ability to share data for collaboration and partnership)
• To make data actionable through FAIR interoperability

Webinar Program

Case Study – Mathew Woodwark, Head of Data Infrastructure and Tools, Data Science & AI, AstraZeneca

• Data and process priorities at a Corporate R&D level
• FAIR data as a corporate asset by design
• The challenges to overcome

FAIR digital objects for automating processes – Erik Schultes, International Science Coordinator, GO-FAIR

• The role of FAIR digital objects for automating processes in a collaborative and federated world
• The digital molecular structure and digital twins examples
• Why convergence for FAIR data and services is important

FAIR automation workflows and applications – Georges Heiter, Founder & CEO, Databiology

• Delivering FAIR automation workflows and applications to the Data Scientist in R&D
• Why FAIR automation is important (smarter /faster science – reusability /provenance)
• How a use case centric approach can gain traction

Hosted expert panel – All presenters

• A few prepared questions
• Questions from the audience

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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