Author(s)

A H Kaas & R D Frederiksen

Abstract

The operation of public transport systems is inherently a rather complex matter. Not only does a public transport system rely on a given infrastructure; it is also dependent on the available rolling stock and the possible timetable. Despite the interdependence between different data, public transport companies often structure their data in a non-holistic way; e.g. by making separate departments responsible for infrastructure, timetable and rolling stock data, respectively. This tendency is strengthened by the deregulation of the public transport sector in many countries making different companies responsible for data of the same transport system. For this reason, data are often placed on different software platforms; Timetable and rolling stock data in different relational databases, infrastructure data are often divided in tabular data stored in a relational database, and geographical data stored in either CAD or GIS. Some data are even stored in closed proprietary formats inside transport modelling software packages. With the introduction of object-oriented GIS based on standard relational databases, an elegant solution to these problems is now possible. The answer is to create an intelligent, rule-based, open and extensible object-oriented data model. Making a data model intelligent and rule-based involves building functions (methods) into the data model itself, rather than into the client of the data model, e.g. into a transport model package. Based on defined rules, these functions can ensure data integrity at all times. More advanced functions can be programmed to modify the underlying data so that otherwise illegal edits can be made without compromising data integrity.

Keywords