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. Author manuscript; available in PMC: 2019 Apr 1.
Published in final edited form as: Annu Rev Public Health. 2017 Dec 20;39:95–112. doi: 10.1146/annurev-publhealth-040617-014208

Table 1:

Types of Big Data for Public Health

Source Examples Aspect of bigness1 Key technical issues Typical uses
-omic/biological Whole exome profiling, metabolomics Wide Lab effects, informatics pipeline Etiologic research, screening
Geospatial Neighborhood characteristics Wide Spatial autocorrelation Etiologic research, surveillance
Electronic health records Records of all patients with hypertension Tall, often also Wide Data cleaning, natural language Clinical research, surveillance
Personal monitoring Daily GPS records, Fitbit readings Tall Redundancy, inferring intentions Etiologic research, potentially clinical decision-making
Effluent data Google Search Results, Reddit Tall Selection biases, natural language Surveillance, screening, identifying hidden social networks.
1

‘Wide’ datasets have many columns; ‘tall’ datasets have many rows.