Because these IoT-based sensors gather different types of data, often in different formats and sometimes vendor-specific, the successful integration of these diverse datasets and data feeds can be quite challenging. In addition, their coalescence within decision support systems and other analytics platforms is paramount to the usefulness of the data for data products development that support improved decision-making.Other challenges include: 

This paper presents challenges faced by the transit industry in adopting new technologies and the use of associated data.

Following are needs of transportation agencies with respect to managing data from emerging technologies, such as connected vehicles, as identified in NCHRP 08-116

Based on an assessment of the various freight data challenges drawn from the literature, a set of broad freight data needs were developed. These needs cut across multiple planning and operational functions such as, long-range freight planning, system performance monitoring, modal-shift analysis, last-mile deliveries, e-commerce, truck idling, truck parking, and land-use. 

Leadership regarding freight data collection, organization, analysis, and standards

The rise of new data sources and determining how best to incorporate them into the transportation planning process is a major area of research and consideration. At the same time, the desire to integrate private and third party datasets into the regional and community planning process is associated with a number of challenges. The following list contains a number of specific challenges associated with evolving travel behavior (considering such influences as new modes and TNCs) and integrating new data resources into the planning process:  

Only a few agencies have successfully implemented the work zone data specification into production. This low adoption rate exists despite a high degree of interest in the specification itself based on comments found on the official GitHub site and discussions between IOOs and the FHWA. Based on these comments and conversations, the slow adoption of the standard appears to stem from other roadblocks and challenges. Following is a list of challenges that agencies face in working with work zone data:

To measure and report on TIM performance, data need to be collected and analyzed. Traditionally, transportation agencies have relied almost solely on their own data to monitor TIM performance, if at all. However, a transportation agency’s view of traffic incidents is often limited to specific routes, within urban areas, and specific times of the day. Incidents occur on many different types of routes statewide – both urban and rural – at all times of the day and night, and transportation agencies are usually not the first responding agency to many incidents.

Common challenges were identified in the literature and in interviews with ICM system deployers. The sheer magnitude of data coming from many new and different sources presented challenges that resulted in the development of unanticipated interfaces and more customized solutions. Some of these included:

Urban mobility is organized into three broad categories of collective, individual, and freight transportation. While the mobility of passengers is the outcome of individual decisions based on different rationales, freight mobility is decided in tandem between the cargo owners and transportation service providers.

https://transportgeography.org/contents/chapter8/urban-mobility/

The ODE is a real-time virtual data router that ingests and processes operational data from various connected devices—including vehicles, infrastructure, and traffic management centers—and distributes it to other devices and subscribing transportation management applications.