The Utah Prisms Infrastructure For Generating Air Quality Exposomes
Creators: name: Gouripeddi, Ramkiran
name: Facelli, Julio
name: Sward, Katherine
Publisher: name: Zenodo
Year: 2017
Subjects: Exposome
Sensor Data Model
Software Infrastructure
Data Integration

description: Understanding the effects of the modern environment on pediatric asthma requires generation of a complete picture of the contributing environmental exposures and socio-economic factors. Such an exposome requires integration of data from wearable and stationary sensors, environmental monitors, physiology, medication use and other clinical data. In addition, such an integration would need to have a high spatial-temporal resolution for correlating times and location of exposures to occurrences of conditions and their severities. This would require filling any gaps in the measured data with modeled data along with characterization of any uncertainties.

The Utah PRISMS Federated Integration Architecture is a comprehensive, standards-based, open-source informatics platform that allows sensor data and biomedical data to be integrated in a meaningful manner. We are developing the architecture, data models, processes, hardware and software to acquire, manage, process, and communicate high-resolution clinically relevant exposome information from environmental, physiological, and behavioral sensors and computational models. We envision this infrastructure to support different types of environmental biomedical studies of pediatric asthma and other chronic conditions, and potentially other research. In this presentation, we discuss two main components of the Utah PRISMS infrastructure:

<strong>Sensor Common Data Model</strong>: Federating or integrating increasingly large, complex and multi-dimensional sensor data requires a thorough human understanding of them. These metadata specifications are designed to support the conduct of research utilizing personalized and environmental sensors. These includes sensors ranging from nano-sensors up to satellites. Sensor measurements may include physical, chemical, and biological species. In addition, these sensors include those that instantaneously (or with a transient storage) measure these species or those that collect physical samples with material transfer for later analysis. Sensors may be deployed in various environments, including personal (i.e. implanted &amp; mobile), immediate (i.e. indoor), and general environment (i.e. external environmental protection agency monitors). The purpose of the data model is to establish a library of instruments; describe and document deployments of sensors; assess quality of data collected by different instruments within its deployment environments; support harmonization and integration of data collected from various sensors; and guide for structuring and storing sensor output data.

<strong>Central Big Data Federation/Integration Platform</strong>: This is a standards-based, open-access infrastructure that integrates sensor data and mathematically modeled data with biomedical information along with characterizing uncertainties associated with using these data. The platform consists of components that:


	Discover, characterize, store and version metadata of different sensor data sources
	Standardize semantics across different sensor data sources using ontology services
	Store data in a temporal event based model to support different research uses-cases
	Methods to transform and present data for different use-cases of exposomic studies.


In this symposium, we present initial lessons from the Utah PRISMS Platform that summarizes the interconnected work by diverse expertise including electrical, computer, chemical and industrial engineers, atmospheric and computer scientists, informaticists and pediatric researchers in developing an infrastructure for generating exposomes.
description: U54EB021973, National Institute of Biomedical Imaging and Bioengineering, NIH