Harmonization of Sensor Measurement to Support Health Research

Nicole Burnett


In the Salt Lake Valley there are three permanent Environmental Protection Agency (EPA) certified air quality monitoring stations that intake air samples and produce results of the air quality in the proximity of the monitor station. Due to the fact that the monitors only represent a small area of the 500-square-mile Salt Lake Valley, there are spatial gaps when using the air quality monitoring data for epidemiological studies. Researchers, as well as Salt Lake Valley residents are recording air quality data measurements from their individual sensors as well. With the help of my team, I am developing a conceptual data model that harmonizes and stores air quality measurements from different sensors. This way researchers could access vast amounts of air quality data to support their studies in one place.

With the help of my team, we performed a literature review using PubMed with the search criterion “Pediatric Asthma Sensor Studies’. A list of metadata elements were manually extracted from the literature, and a first conceptual model was made.

Next I helped my team collect sample data from different sources across the Salt Lake Valley. With the data that was collected I evaluated the conceptual model. Existing fields found in the data, but not present in the model, were added to the model. I then met with air quality experts in Utah to review the model and modified it further based on their inputs.

We now have a model that works with a database to harmonize and store vast amounts of air quality data from different sensors. This model will now be used in data integration platform such as OpenFurther to support study next effects of the environment (exposome) on health and well-being.


Air Quality; Sensor; Data Harmonization

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