Data Harmonization and FAIR
Create data pipelines for various use cases and support on-premise and cloud-based data analysis
Overview
The team of data documentationists and data scientists create data pipelines for various use cases and support on-premise and cloud-based data analysis through a federated approach. The team uses the Observational Medical Outcomes Partnership (OMOP) Common Data Model – a standardized data model for health data with internationally recognized vocabularies. The platform harmonizes data generated internally and externally through the Center’s partnership projects across Africa and beyond. In addition, metadata for APHRC research datasets is indexed and made machine searchable using tools such as Schema.org to increase visibility and allow global data sharing
Related Projects
Related Publications
- Data Science Program, Data Synergy, Education and Youth Empowerment(EYE), Human Development
- Data Science Program, Health and Wellbeing
- Data Science and Sharing (DASSA), Data Science Program, Data Synergy
- Data Science and Sharing (DASSA), Data Science Program, Data Synergy
- Data Science and Sharing (DASSA), Data Science Program, Data Synergy
- Data Science and Sharing (DASSA), Data Science Program, Data Synergy
- Data Science and Sharing (DASSA), Data Synergy
- Data Science Program, Education and Youth Empowerment(EYE), Human Development