When Was Citymapper Created?Citymapper has been around for some time now, but what exactly are they? How is it different from other navigation applications? What are the sources of the Data that they use? And how did they come up with their data-collection algorithms? The answer to this question lies in their use of data from public transport systems and other sources. Keeping these two factors in mind, let's take a look at the history of the app.
Data collected by CitymapperCitymapper is a mobile app which mediates open data from TfL's bus timetable. The application leverages behavioural patterns to collect environmental data, making users into a distributed data infrastructure. By allowing users to contribute data, Citymapper provides a means to track behavioural patterns and develop new technologies that are more useful to citizens. In the long term, data collected by the app will provide a new understanding of the city's environment. The data collected by Citymapper is based on open data from the city authorities and other sources. The team behind the app collates the data from various sources and formats. They fix inaccuracies and improve data quality to improve the customer experience. This model is particularly useful in urban areas where a single bus can carry up to 3,000 people. Ultimately, the data is invaluable to both city residents and business owners alike.
Data collected from other sourcesCitymapper combines infrastructural and data power in an effort to redefine the way we live and plan in cities. The app's rebranding, however, goes further than simply claiming epistemological superiority. In fact, the app nominates itself as the organisation to'replan' the future of London. This paradigm, however, tends to view cities as computer systems and, consequently, the rise of data analytics led tech companies to designate themselves as the best urban planners. Unfortunately, this can lead to detrimental effects on other epistemologies. The Citymapper app collects data from a variety of sources and uses this for a variety of purposes, including improving the service and improving the user experience. As users navigate around the city, they become a GPS router, sensing and responsive node, and a part of the infrastructure of the app. While relying on external sources for its information, the app also makes use of data from users to improve its design, functionality, and content.
Data collected from public transport systemsWhereIsMyTransport is a data organization that collects and manages information on public transport systems worldwide. Their database covers over 40 cities in 27 countries on four continents. They estimate that informal public transport systems move 80% of the population in urban centers, and they comprise tens of thousands of vehicles operated by independent operators. Most of this data is not mapped and available to commuters, who often spend five hours on a daily commute. The project was conceived to mediate bus timetables. In the process, it transformed users into environmental sensing nodes that collect and process data from public transport systems. These users have become the infrastructure of the app's data-driven services. By leveraging the behavioural patterns of their users, Citymapper has both a social and infrastructural impact. This study is just one of many examples of this type of data-driven data application.
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