Online network analysis from heterogeneous datasets - Case study in London train network

  etwork is one of the largest public city transportation networks in the world. There are about 1000km of track in the network and about 4 million journeys made every day (Transport, 2003a). It includes three modes of train-based system; rail, tram and tube (the name of the underground railway system). Table 1 shows the names of the network lines in each mode of transportation.

Mode Name Rail Dockland Light Railway, National Rail Tram Tramlink Tube Bakerloo, Central, Circle, District, East London, Hammersmith & City, Jubilee, Metropolitan, Northern, Piccadilly, Victoria, Waterloo
Table 1. The network lines in London train network The base route map provided by (Transport, 2003b) is in raster format which is a cartographic map showing the routes and connections of the train network in London. This base data was converted into vector format by digitising and then converted into GML format. Each train line (e.g. Bakerloo, Tramlink, Victoria) are stored in a separate GML file. Additional data of the station and interchange station are also created and stored in GML files.

3. The architecture of the software system
The aim of this research is to develop a software system that enables the analysis of network data that comes from multiple different data sources. To achieve this aim, we use the web to share data and utilise GML as the data format. The intelligent engine is required to retrieve data from different data sources through the web. Such an engine also needs to have the capability of getting the data request from the user about which datasets they want, and then deliver these data back to the user once all the required data has been retrieved. The software system also has to provide tools to build the network topology based on the network data depending on the rules of connectivity defined and to carry out the network analysis. Th

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