An ontology-based framework to support performance monitoring in public transport systems
place - europe, planning - service quality, planning - standards, organisation - performance, operations - performance
Public transport system, Transmodel, Monitoring system, Key Performance Indicators, Ontology, Logic reasoning
Managers of public transport systems have been facing for years the strategic challenge of maintaining high quality of transport services to improve the mobility of citizens, while reducing costs and ensuring safety and low environmental impact. A well-established way to evaluate the performance achieved by the system or by specific activities is to monitor Key Performance Indicators (KPI). However, existing management systems, which refer to flexible yet large and complex data models, provide a limited support to define and select relevant KPIs for the objectives at hand, and even the identification of whether and how the data model is capable to achieve a certain informative need is a critical and time-consuming task. This work is aimed to propose a framework to ease the development of a monitoring system in the public transport domain. The approach is based on the ontological representation of all the knowledge regarding indicators and their formulas, business objectives, dimension analysis and their relation with the Transmodel, the European reference data model for public transport information systems. On its top, a reasoning framework provides logic functionalities to interactively support designers in a set of common design tasks: the choice of the most suitable indicators for the performance monitoring needs at hand, the definition of new indicators and the identification of the minimal set of Transmodel modules needed to calculate them. A case study is included to discuss these applications, while an evaluation shows the feasibility of the approach.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Benvenuti, F., Diamantini, C., Potena, D., & Storti, E. (2017). An ontology-based framework to support performance monitoring in public transport systems. Transportation Research Part C: Emerging Technologies, Vol. 81, pp. 188-208.