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Linking open data and the crowd for real-time passenger information
Corsar D., Edwards P., Nelson J., Baillie C., Papangelis K., Velaga N. Journal of Web Semantics43  18-24,2017.Type:Article
Date Reviewed: Oct 26 2017

Buses have run on country roads for ages, yet our present-day frantic lifestyle pushes us to feel lost if that familiar shape doesn’t appear around the corner at the precise moment we expect it; on the other hand, that same frantic lifestyle allows us to always stay connected thanks to electronic gadgets. If only some little magic existed that would allow us to track every bus of every line on every road, thus mitigating our anxiety.

This paper presents one such application; it is called GetThere and it offers real-time passenger information for rural areas. It takes data from government, transport companies, and people traveling on buses, and after some data consistency checks, offers information right on the traveler’s smartphone screen. From a technical point of view, it is an ontological framework to model mobility information using semantic web technologies. Its goal is to list bus routes and their timetables, real-time vehicle location, and up-to-date information in case of service disruption. These goals are expected to benefit first of all the general public, but also the scientific community--in fact, this application is also a testbed for data integration from heterogeneous sources, use of open data sources, as well as analysis and forecast of quality of service.

As noted above, the application takes advantage of existing ontologies, which are descriptions of some knowledge domain in terms of entities, classes, attributes, and relations; in this case, the ontologies describe the local public transport ecosystem using existing open data sources. From these ontologies, more traditional datasets are built. Web services in turn query the datasets and group information thus obtained for user interaction; among all web services, a very important one is the quality evaluation service that measures such parameters as timeliness, accuracy, relevance, and availability of information for the whole system. Finally, GetThere uses these web services and brings information to smartphone screens. The paper details all of this with two very clear figures that help visualize the whole flow of information.

The next part of the paper evaluates the performance of the whole system, including the app and its back-end server. There is first a standard description of test setup in terms of server hardware and software, and agents simulating users, buses, and routes. Then come results from a live user trial. First is a standard description of the trial itself in terms of criteria for subject enrollment and duration of trial; data from interviews both before and after the trial are reported, too. But the most unconventional and unexpected part of the paper can be found tucked away in a footnote on the front page: a link to the dot.rural project page (http://www.dotrural.ac.uk/irp) where readers can download the actual app, albeit only for Android phones at present, as well as find broader coverage of the project; it’s a pity this link is not very visible.

At the end, the authors honestly draw some conclusions: in future work, the use of open-source data should be improved; some scalability issues must be solved, because information from too many sources degrades performance; and potential privacy problems must be overcome before adopting such a system on a large scale, for example, integrating it with other public transport services (rail, ferry).

Reviewer:  Andrea Paramithiotti Review #: CR145620 (1712-0820)
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