Understanding RailState Data
Understanding the RailState dataset is important for interpreting results accurately and for contextual insight.
The dataset accessed via the API and UI is the same. It is based on a summary of rail traffic as detected by RailState's national networks of AI-backed sensors. Not every rail line or route option between regions is covered. It is not a summary of all traffic moving - it is a summary of all traffic that RailState has detected.
Data summarized reflects movements detected at a specific sensor site, or between connecting sensors, and is not an indication of the movement's ultimate origin or ultimate destination.
RailState does not receive nor display any data as reported by a railroad, including Car Location Messages (CLMs) and waybills.
Some operational or environmental factors may at times impede our ability to collect data. As well, as new sensors are added and network density expands it is important to note that data is reflected on a go-forward basis only. The data should be considered preliminary and may be subject to further changes or updates.
The RailState UI offers a host of functionality that helps in segmenting and further analysing movements, and provides filter functionality in those areas where RailState AI has been able to determine such attributes. As RailState has incorporated new elements and introduced new logic to satisfy specific requirements it should be understood that as is the nature with machine learning and computer vision, functionality, and as such capture rates and classification, improves over time as learning from data sets occurs.