
Worked on the GSA/datagov-harvester repository to enhance data harvesting and transformation workflows. Integrated MDTranslator to enable cross-schema data transformation, updating the HarvestSource model to support new schema types and improving error handling for clearer diagnostics. Migrated the application to support DCAT-US 1.1 schemas, including both federal and non-federal variants, and configured the transformer service within Docker Compose to facilitate continuous integration pipelines. Expanded test coverage to ensure reliable data transformation and end-to-end validation. Leveraged Python, Docker, and Flask to implement robust backend features, focusing on data engineering, schema design, and automated testing to improve pipeline resilience.
Concise monthly summary for 2024-11 focusing on key accomplishments in GSA/datagov-harvester. Highlights include MDTranslator integration enabling cross-schema data transformation, DCAT-US 1.1 schema updates with CI-enabled transformer service, and enhanced testing/error handling, improving data quality and pipeline resilience.
Concise monthly summary for 2024-11 focusing on key accomplishments in GSA/datagov-harvester. Highlights include MDTranslator integration enabling cross-schema data transformation, DCAT-US 1.1 schema updates with CI-enabled transformer service, and enhanced testing/error handling, improving data quality and pipeline resilience.

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