Table 1.

Challenges by type of data

Data Type	Challenge Types	Challenges
Mobile Device	Technical	Data coverage in spatial and temporal dimensions may vary dramatically and is limited by the quality of the mobile network.
	Methodological	The accuracy and reliability of the geolocation are a concern due to the appropriateness of data-sharing devices and processes. The OD flows for each user are estimated by clustering the users’ staying points. Different clustering methods and selection criteria could lead to different results. The OD flows obtained from mobile devices need to be spatially aggregated to different geographic units to reveal the dynamics of human mobility at different spatial scales.
	Social and political	Data privacy concerns prevent the sharing of individual user records. Only spatially aggregated information is available.
Social Media	Technical	Accuracy of geo-information varies across different social media platforms, user settings, and mobile devices.
	Methodological	Data bias from different user groups (e.g., races, regions, and age.) Social media data is more heterogeneous with high variability of data types, formats, and qualities.
	Social and political	The locational information in social media data should not be used to identify individual users.
Connected Vehicle (CV)	Technical	The tremendous volume and rapid data collection speeds of CV data lead to rigorous requirements for computing and storage devices. The spatiotemporal coverage and availability of the CV data vary across regions.
	Methodological	Different CV data companies are partnered with different original equipment manufacturers (OEMs) to collect CV data from a variety of vehicles. The data collection and processing also vary from OEM to OEM, leading to severe data uncertainty. Meanwhile, only vehicle movements are covered by CV data; the mobility of active transportation (e.g., biking, walking) is missing.
	Social and political	The high detailed trajectory and driving behavior datasets collected from CVs may have the risk of revealing too much personal information (e.g., home and working addresses.)