
Javier Perez worked on establishing the foundational Overture Maps catalog infrastructure within the google/earthengine-catalog repository, focusing on scalable data discovery and analytics. He designed and implemented core catalog components using Jsonnet, integrating initial datasets and standardizing file organization to streamline onboarding and governance. Javier enhanced the Places data model with BigQuery integration hooks and developed Earth Engine JavaScript scripts for visualizing Manhattan and NYC datasets. His work included refining metadata, evolving schema definitions with new RECORD types, and aligning validation processes. This approach improved data discoverability, enabled consistent ingestion, and laid the groundwork for robust geospatial analytics pipelines.
December 2025: Delivered foundational Overture Maps catalog infrastructure and data model enhancements in google/earthengine-catalog. Established core catalog components (overture-maps.jsonnet, overture-maps_places_place.jsonnet, catalog.jsonnet) and integrated initial datasets; cleaned stale ownership references and standardized file naming for clarity. Implemented Overture Maps Places data model with BigQuery integration hooks, added visualization scripts for Manhattan and NYC via Earth Engine, and refined metadata and keywords to improve searchability. Addressed schema evolution by adopting new RECORD types in earthengine_const.libsonnet (with checker updates required). These changes reduce onboarding time for new datasets, enable consistent data discovery, and lay groundwork for scalable analytics pipelines. Technologies demonstrated include Jsonnet-based catalogs, Earth Engine JavaScript visualizations, BigQuery integration, repo refactoring, and governance processes.
December 2025: Delivered foundational Overture Maps catalog infrastructure and data model enhancements in google/earthengine-catalog. Established core catalog components (overture-maps.jsonnet, overture-maps_places_place.jsonnet, catalog.jsonnet) and integrated initial datasets; cleaned stale ownership references and standardized file naming for clarity. Implemented Overture Maps Places data model with BigQuery integration hooks, added visualization scripts for Manhattan and NYC via Earth Engine, and refined metadata and keywords to improve searchability. Addressed schema evolution by adopting new RECORD types in earthengine_const.libsonnet (with checker updates required). These changes reduce onboarding time for new datasets, enable consistent data discovery, and lay groundwork for scalable analytics pipelines. Technologies demonstrated include Jsonnet-based catalogs, Earth Engine JavaScript visualizations, BigQuery integration, repo refactoring, and governance processes.

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