As the complexity of public transport networks grew during the 20th century, so did the inventiveness of the attempts to communicate those networks to users. Angular schematic maps, in the form of the London Underground map attributed to Harry Beck, have since become common for core urban and suburban public transport networks. Since at least the 1990s these maps have infected service design, with high frequency bus networks increasingly structured to be readily communicable as stylised network maps – inevitably limiting the range of direct destinations offered. Inter-regional networks necessarily remain complicated, and, as illustrated by various European attempts at national network flow maps, are challenging to communicate in schematic form. At least on paper. Continue reading “Aquius – An Alternative Approach to Public Transport Network Discovery”
This essay analyses and explores the regional passenger fare structure of Renfe, Spain’s national railway operator. The question, “Is Alta Velocidad Fast?”, derives from Renfe’s tradition of pricing slower trains cheaper. The question asks whether, in the era of yield management (balancing current patronage to current capacity by modifying price), the traditional fare structure should be applied to high speed, AV, operations? The journey provides an insight into the structure of modern transport geography, the haphazard strategic development and exploitation of Alta Velocidad, the management of national inequalities through fares, the conflation of public and commercial roles within single shared operations, and, from a perspective other than infrastructure, the contemporary challenges to Spain’s railways. Continue reading “Is Alta Velocidad Fast?”
The UK‘s local public transport data is effectively a closed dataset. The situation in the US seems similar: In spite of the benefits only a handful of agencies have released raw data freely (such as BART and TriMet on the west coast of America).
That hasn’t stopped “screen-scraping” of data or simply typing in paper timetables (from Urban Mapping to many listed here). Unfortunately, the legal basis for scraping is complex, which creates significant risks for anyone building a business. For example, earlier this year, airline Ryanair requested the removal of all their data from Skyscanner, a flight price comparison site that gathers data by scraping airlines’ websites. How many airlines would need to object to their data being scraped before a “price comparison” service becomes unusable?
Micro-blogging, primarily through Twitter, has started to show the potential of individual travellers to report information about their journeys: Ron Whitman‘s Commuter Feed is a good example. Tom Morris has also experimented with London Twitter feeds.
This article outlines why the “social web”/tech-entrepreneur sector may wish to stop trying to use official sources of data, and instead apply the technology it understands best: People. Continue reading “Social Reconstruction of Public Transportation Information”
The United Kingdom’s local public transport network is likely to become part of Google Transit. Technically that should be far easier in the UK than in North America, where Google Transit was first developed: The UK has a decade’s bitter experience putting all the data together. In practice it is raising wider issues over data control and availability, that the public sector is somewhat reluctant to tackle.
This article describes how the UK’s public transport data is being integrated into Google. It questions why data is being made available based solely on the business model adopted. It explores the real value of this information, and presents a case for the liberalisation of data.
Readers unfamiliar with the topic area should read my earlier Introduction to UK Local Public Transport Data, which contains non-technical background information, and defines many of the terms used (such as “local”). The original research for this was done in June/July 2007, so may now be slightly out of date.
The illustration on the right is the Google part of a visual representation of web trends, based on the Tokyo metro map, by Information Architects Japan.
This article provides a basic non-technical introduction to the United Kingdom’s electronic local public transport data: The data sources primarily used to produce passenger travel information. It does not cover solely operational data, for example, financial, patronage or staff rostering.
The article is intended to provide a background for anyone wishing to understand how these data sources might be used. It was written to support my commentary on the Implications of Google Transit in the UK. The article first introduces the local public transport sector (primarily bus and rail), then explores the development of different data formats, before summarising data availability.