Our goal is to improve the accuracy, reliability, and usability of data through careful annotation, transformation, validation, and harmonization processes. We focus on ensuring data consistency and quality to support reliable analysis and research outcomes.
- Annotate source data with ontologies
- Transform source data into LinkML model
- Create validation pipelines for harmonized data
- Quality Control (QC):
- Define metrics
- Execute metrics and provide reports
- Document provenance of all data, ontology annotations, and transforms
- Create data harmonization tools to support long term sustainability
- Coming Soon