An Architecture for Metadata-driven Integration of Heterogeneous Sensor and Health Data for Translational Exposomic Research

被引：0
|
作者：
Gouripeddi, Ramkiran [1 ]
Le-Thuy Tran [1 ]
Madsen, Randy [2 ]
Gangadhar, Tanvi [3 ]
Mo, Peter [2 ]
Burnett, Nicole [4 ]
Butcher, Ryan [2 ]
Sward, Katherine [5 ]
Facelli, Julio [1 ]
机构：
[1] Univ Utah, Dept Biomed Informat, Salt Lake City, UT 84112 USA
[2] Univ Utah, Ctr Clin & Translat Sci, Salt Lake City, UT USA
[3] Univ Utah, Sch Comp, Salt Lake City, UT USA
[4] Univ Utah, Dept Chem, Salt Lake City, UT 84112 USA
[5] Univ Utah, Coll Nursing, Salt Lake City, UT 84112 USA
来源：
2019 IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL & HEALTH INFORMATICS (BHI) | 2019年
关键词：
exposome; sensor informatics; data integration; metadata management; clinical research;
D O I：
10.1109/bhi.2019.8834657
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Exposomic research requires the generation of comprehensive spatio-temporal records of exposures along with capturing associated metadata describing limitations and uncertainties associated with the data. We describe the architecture of a metadata-driven Big Data integration platform for integration of sensor and health data to support diverse translational exposomic research.
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页数：4
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