Agencies should not be concerned if they do not (or will not) have access to data to populate all fields in the database, or if there are not enough data elements/attributes defined in the database to match existing data. In most cases, agencies may find that they do not have the ability to report all data elements in the model TIM performance measurement database for all incidents. The database was designed so that most of the data elements are null-able, meaning that these fields can be left empty without any consequences on the storage of the data. Where it will affect the agency is in its ability to run specific queries. If a key piece of information is missing in the database, say when the incident was first reported or when the roadway was cleared, then the RCT cannot be calculated. If, on the other hand, the agency does not have information on surface conditions, the TIM performance measures can be calculated, they just cannot be analyzed/reported by different surface conditions.
Alternatively, if more information is available to an agency than is in the model TIM performance measurement database schema, data elements can be added to the schema, and queries can be created to use these data elements. The database script available for download prepopulates the database lookup tables with commonly occurring conditions, and in most cases these lists are not exhaustive. For example, roadway surface conditions are prepopulated as: dry, wet, snow, and ice. In some cases, an agency may find that these prepopulated values are not representative of or do not sufficiently capture local conditions/data. These prepopulated values can be modified (e.g., values can be eliminated, added, or re-defined). For example, in the “Organization” look-up table, the names or numbers of different police or fire departments could be entered, as well as the names of the various private towing companies that might respond to incidents. The database schema is flexible and requires little work to adjust as needed. On the other hand, users should exercise some caution when modifying the schema, as the schema was designed with the idea that different agencies could all report the same data, with the same definitions so that the data could be aggregated and/or compared across regions/states. If the database is modified to a point where a field deviates from its original meaning, aggregation of the data and/or comparisons may be more difficult or impossible to achieve.