## 3 Data
### Crossing Selection for a Sample County (Cass)  
The site verification of the FRA HRGCs inventory data resulted in the creation of a new, corrected, and more complete HRGCs database that was used for comparative model estimation and crash predictions. However, before model estimations and crash predictions, each of these two datasets were integrated with the FRA HRGCs Accident/Incident database using the unique FRA crossing ID. Crash data on the 560 HRGCs revealed 28 reported crashes during 2017-2021. These 28 crashes were 16.3% of all public HRGCs crashes reported in Nebraska during the same five-year period. For this study, HRGCs inventory data errors and missing information were the focus; such issues may also exist in the FRA HRGCs Accident/Incident database; however, those were not part of this research. Data validation is the process of ensuring that the data entered into a system are accurate, complete, and consistent. It is an important step in the data management process as it helps us to ensure the integrity of the data and ensures that the data are fit for their intended purpose [20]. The inventory data of HRGCs in nine Nebraska counties were validated based on the checks illustrated in Figure 3.  
For every HRGC visited, a comprehensive examination of 53 database variables was conducted and digital images were acquired. Any inaccuracies in the database were rectified in accordance with field conditions, and missing values were added if those attributes were found in the field. The disparity between the recorded information in the FRA HRGCs inventory database and the actual conditions at crossing 064112B is vividly exemplified in Figure 4, which showcases a discrepancy in the presence of yield signs, pavement type, approach surface type, and pavement markings in the FRA dataset compared to the on-ground conditions. The red square points indicate a zoomed illustration of yield signs and pavement marking. Figure 2: FRA HRGCs data filtration process of a sample county (Cass) [2]. Figure 4: Data correction example, crossing 064112B [19]. Figure 3: Validation checks for HRGCs inventory data collection [2]. Additionally, crossing storage distances were validated. For example, Figure 5 illustrates how the storage distance in the FRA data was measured as 64 feet, but field validation corrected it to 40 feet. The safety of HRGCs has been strongly correlated with storage distance [18]. The illustration in Figure 6 details data validation for a specific location (crossing 064130Y), where a discrepancy was found between the actual number of flashing light pairs and the number recorded in the Federal Railroad Administration's (FRA) inventory dataset. The validation involved a field check and revealed the difference, indicating that the FRA inventory data entries on several physical aspects were incorrect. Figure 5: Data correction example, crossing 072946C [2]. It should be noted that the satellite images presented in Figures 4-6 are not scaled as satellite images inherently lack a uniform scale due to variations in altitude and sensor characteristics, making the addition of a scale potentially misleading [2]. Table 2 provides a summary of the corrections and addition of missing values. In aggregate, data on 560 HRGCs were successfully verified. Additionally, six HRGCs sites were found to be abandoned, non-operational, or altogether non-existent. The effort resulted in 2241 corrected values and 1732 missing values added to the database, providing an average of 7.4% of the database values that were changed at every visited HRGCs. It is noteworthy that the research team was unable to verify dynamic characteristics such as daily train traffic and highway AADT. As such, those variable values in the FRA database and the corrected database were the same.