User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research

Table 2 Investigated characteristics of user documented food consumption data related to data management and extracted information (n = 176)

Characteristic	Description	Extracted information (n)
Data export	Whether the data collected by the app is exportable directly via the apps infrastructure (not via integrated aggregators)	No information (117), Yes (55), No (4)
Access method^a	The type of data export	File download (40), Email export (9), API (5), SDK (3), No information (3), Dropbox^b (3), AirDrop^c (1), Google Account^d (1), Google Drive^e (1)
Data format^a	The format the data can be exported	PDF (18), CSV (18), Excel (9), No information (8), JSON (4), HTML (3), SQLite^f data file (2)
External data sources^a	What type of third parties systems does the app exchange data with	Aggregators (44), Partner apps (40), Health and fitness trackers (24)

^aPer characteristic multiple inputs were possible and hence the individual percentages do not add up to 100%
^bcloud storage provider or online backup service that is also used as a file-sharing platform
^clets Mac and iOS devices share files wirelessly
^drequired for access to certain Google online services and supports app data storage
^epersonal cloud storage service that lets users store and synchronize digital content across computers, laptops and mobile devices
^fSQLite is a relational database management system
API Application Programming Interface, SDK, Software Development Kit, PDF Portable Document Format, CSV Comma Separated Values, JSON JavaScript Object Notation, HTML Hypertext Markup Language

ISSN: 1475-2891