Geo Data Description

Work in progress. These tutorial materials are still under active development and will continue to change until the tutorial takes place on October 20, 2026. Content, links, and exercises may be incomplete or shift without notice.

The tutorial uses two datasets: a synthetic OMOP CDM population (described in OMOP Data Description) and the public PM2.5 dataset for the United States described on this page (an external source, used to demonstrate cataloging and ingestion of a real dataset). Session 1 catalogs the public dataset; Sessions 2-4 link it against the synthetic OMOP population. See Geo Data Visualization for a characterization of this dataset.


Public GIS PM2.5 dataset (United States)

2014-2019 CDC PM 2.5 Monthly Predictions for US Counties

This is the public source dataset participants catalog in Exercise 1 and ingest in Exercise 2.

NOTE: there are several alternative sources for PM 2.5 data in the Gaia Catalog. We may encourage participants to use different data sources and then compare resuts.

Overview

Aggregated monthly PM 2.5 modelled estimates that span 2014-01-01 to 2019-12-31 derived from the CDC Daily County-Level PM2.5 Concentrations 2001-2022 provided by the CDC National Environmental Public Health Tracking Network. The aggregated data are then joined to the TIGER line county geometries provided by the US Census Bureau.

From the CDC description: This dataset provides modeled predictions of PM2.5 levels from the EPA Downscaler model. Data are at the county level for 2001-2022. These data are used by the CDC National Environmental Public Health Tracking Network to generate air quality measures. By using these data, you signify your agreement to comply with the following requirements: 1. Use the data for statistical reporting and analysis only. 2. Do not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. 3. Do not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: . 4. Do not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. 5. Acknowledge, in all reports or presentations based on these data, the original source of the data and CDC. 6. Suggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking.

Sources

NOTE: the gaiaCatalog source first pulls the CDC daily data from an API and then aggregates the data to monthly derivatives which are then joined to the US Census Bureau TIGER line geometries for US counties. The University of Miami Geospatial Digital Special Collections maintains a pre-aggregated version of the 2014-2019 CDC PM 2.5 Monthly Predictions for US Counties dataset for the tutorial available for download in SQL and gpkg formats.

Coverage

  • Spatial coverage: United States Counties
  • Temporal coverage: 2014 - 2019 with monthly data points.
  • Variable definition and unit: PM2.5 concentration, µg/m³, monthly max, mean, median, and population weighted mean._

Access and license

Role in the tutorial

This is the dataset participants evaluate against the fitness rubric and catalog with a metadata record in Exercise 1, then ingest and spatially/temporally link to the synthetic OMOP population (OMOP Data Description) in Exercise 2.