Comparison of public data opening in the Global Urban transportation field

With the development of the Internet, more and more urban public institutions have started or have established the Open Data portal in the field of transportation, and six cities such as New York, Paris, London, Toronto, Madrid and Singapore are the typical representatives, but each city's Open data types and open strategies are different.

I. Open Data comparisons

Six cities, such as New York, Paris, London, Toronto, Madrid and Singapore, have opened public data on traffic, including public transport (bus, Subway, train), urban roads, highways and highways, respectively, on the website of the traffic authorities, the traffic operator's website or the Open Data portal of the city. Data on bike lanes and sidewalk traffic conditions.

Through comparison, six cities can be open to the public transport field data into four major categories: first, the description of data, including the public transport network operators name, price, type of transport, timetable, etc., the second is geographical location data, including station location, parking spots, public transport lines, etc., the third is statistical data, including the annual and monthly number of public transport, the number of stops, etc. four are real-time data, including monitoring images, bus timetables, public transport, such as real-time speed.

(i) Total Open data

Figure 1 compares the total number of open data in six urban traffic areas, where the horizontal axis represents the total amount of open data, the amount of real-time data in the ordinate table, and the size of the Open data to be accessible. The accessibility of Open data indicates whether the data can be accessed via the website (e.g. in Paris), or may be queried by application (e.g. in Madrid, Toronto).

Fig. 1 Comparison of the total amount of open data in urban traffic field

(ii) Comparison of Open data types

Figure 2 compares the data sets of five vehicles of public transport, trains, bicycles, automobiles and ships, which are open in six cities. As can be seen, not all cities are fully open to four types of data, and some cities are rarely open or even open to certain data types. Singapore, London and New York have more open data, while Paris, Madrid and Toronto remain. In addition, it is most common to describe class data and geo-positioning class data in all data types.

The 16 data sets opened in Paris, the description class and geo-location class data accounted for the majority, and statistical class data and real-time data are relatively rare. Among them, the geographical location class data total 9, including urban building location map, transportation network map, street map, etc. descriptive data including the theoretical timetable of public transport, statistical data are relatively fragmented, mainly the annual number of subway and quarterly air quality; Paris is the only city without any real-time data.

Fig. 2 Comparison of data set types in urban traffic field

Madrid has very few open data, only more than 10 datasets, of which two are real-time data for public transport, and rarely live data, no statistical data.

New York has the largest number of open datasets, but lacks descriptive data (which may be relevant to the wide dissemination of such data in other channels).

Toronto opened 23 datasets, datasets of various types and all data sets with a lot of descriptive information, including parking spaces, bicycle traffic network, bus network map, monthly and annual peak time statistics and so on. But real-time data is only 3 datasets, which are real-time images of bicycles, real-time bus schedules and traffic conditions.

(Responsible editor: Mengyishan)