In Pharma, large-scale implementations FAIR principles (FAIR: findable, accessible, interoperable, and reusable) have become a widely adopted strategy to drive the digital transformation and to evolve into a data-driven industry. However, until now, FAIR implementation excels in Research and Development. FAIR has not yet really made its way into Enterprise Data Management. In the presentation, we will give insights on our FAIR capability stack for reference data (terminology, metadata, schema definition, and conceptual models) and its application in the Roche R&D data landscape to ensure semantic interoperability.

We will also demonstrate how we apply FAIR to our Master Data by systematically providing global unique persistent, and resolvable identifiers to our resources. The presentation will also explain the required capabilities to build FAIR enterprise data and the governance of our reference data space at Roche. Finally, we expose our FAIR Architecture Playbook for IT Professionals.

• FAIR applications, services, and data
• Information Architecture
• Reference Data
• Enterprise Data
• Data Governance

Speaker: Martin Romacker

Product Manager Roche Data Marketplace
F. Hoffmann-La Roche

Martin is the Product Manager for the Roche Data Marketplace in the Enterprise Data Product Line of Roche Informatics. His main areas of activity are terminology management, semantic engineering, data quality, data curation, and data governance. Martin is currently the project lead of the FAIR Metrics assessment initiative in a cross-functional program for Enhanced Data and Insight Sharing.