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Lecture, Presentation, Training materials
HemaFAIR Lecture 4 - Introduction to the OMOP Common Data Model
This lecture, delivered by Prof. Ronald Cornet (Amsterdam UMC, University of Amsterdam), introduces the OMOP Common Data Model (OMOP CDM) and its role in enabling the standardisation, integration and large-scale analysis of observational health data. The session explains how OMOP CDM provides a harmonised data structure and standardised vocabularies that allow heterogeneous clinical and research datasets to be transformed into a common, interoperable format.
The lecture presents the core components of the OMOP CDM, including its schema, standard concepts and the Extract-Transform-Load (ETL) process required to map source data to the common model. Within the HemaFAIR context, it highlights how the adoption of OMOP supports FAIR data principles, facilitates cross-institutional studies and enables federated and reproducible observational research in rare diseases and haemoglobinopathies.
DOI: https://doi.org/10.5281/zenodo.14854774
Licence: Creative Commons Attribution 4.0 International
Contact: Dr Sotiroula Chatzimatthaiou at sotiroula@cing.ac.cy
Keywords: FAIR principles, Research Data Management, Open Science, Data sharing, Data reuse, Metadata, European research projects, HemaFAIR, Common data model, OMOP
Target audience: Researchers, Data Scientist, Data stewards, Data managers, Students
Resource type: Lecture, Presentation, Training materials
Version: 1
Status: Active
Prerequisites:
No prerequisites. This material is intended as a first introduction to the Biomedical Ontologies
Learning objectives:
-Explain the purpose and key features of the OMOP Common Data Model
-Describe how OMOP CDM enables the standardisation and interoperability of observational health data
-Recognise the role of standard vocabularies and common data structures in integrated data analysis
-Understand the main steps of the ETL process for transforming source data into OMOP
-Identify how OMOP supports FAIR data, multicentre studies and federated research
-Appreciate its application in rare disease and haemoglobinopathy research within the HemaFAIR framework
Date published: 2025-02-12
Contributors: Martijn Kersloot, Petros Kountouris
Scientific topics: FAIR data, Data management, Open science
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