The visual analytics of big, open public transport data – a framework and pipeline for monitoring system performance in Greater Sydney. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Lock, Oliver; Bednarz, Tomasz; Pettit, Christopher
• Is Part Of: Big earth data. Volume 5:Issue 1(2021)
• Page Start: 134
• Page End: 159
• Publication Date: 2021-01-02
• Subjects: WebGL -- visual analytics -- public transportation -- transport performance -- visualisation -- open data -- big data; Earth sciences -- Periodicals; Earth sciences -- Research -- Periodicals; Geographic information systems Periodicals; 550
• DOI: 10.1080/20964471.2020.1758537
• Languages: English
• ISSNs: 2096-4471

Abstract

ABSTRACT: Many cities, countries and transport operators around the world are striving to design intelligent transport systems. These systems capture the value of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility, interests, economic activity and lifestyles. They aim to provide services that can enable transportation customers and managers to be better informed and make safer and more efficient use of infrastructure. In developing principles, guidelines, methods and tools to enable synergistic work between humans and computer-generated information, the science of visual analytics continues to expand our understanding of data through effective and interactive visual interfaces. In this paper, we describe an application of visual analytics related to the study of movement and transportation systems. This application documents the use of rapid, 2D and 3D web visualisation and data analytics libraries and explores their potential added value to the analysis of big public transport performance data. A novel approach to displaying such data through a generalisable framework visualisation system is demonstrated. This framework recalls over a year's worth of public transport performance data at a highly granular level in a fast, interactive browser-based environment. Greater Sydney, Australia forms a case study to highlight potential uses of the visualisation of such large, passively-collected data sets as an applied research scenario. In this paper, we argue that such highly visual systems can add data-driven rigour to service planning and longer-term transport decision-making. Furthermore, they enable the sharing of quality of service statistics with various stakeholders and citizens and can showcase improvements in services before and after policy decisions. The paper concludes by making recommendations on the value of this approach in embedding these or similar web-based systems in transport planning practice, performance management, optimisation and understanding of customer experience.