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- jwe1540-9589.2045 title "Geospatially Partitioning Public Transit Networks for Open Data Publishing".
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- jwe1540-9589.2045 name "Geospatially Partitioning Public Transit Networks for Open Data Publishing".
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- jwe1540-9589.2045 name "Geospatially Partitioning Public Transit Networks for Open Data Publishing".
- jwe1540-9589.2045 topic query_processing.
- jwe1540-9589.2045 topic route_planning.
- jwe1540-9589.2045 topic open_data.
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- jwe1540-9589.2045 subject route_planning.
- jwe1540-9589.2045 subject open_data.
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- jwe1540-9589.2045 topic query_processing.
- jwe1540-9589.2045 topic route_planning.
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- jwe1540-9589.2045 abstract "Public transit operators often publish their open data in a data dump, but developers with limited computational resources may not have the means to process all this data efficiently. In our prior work we have shown that geospatially partitioning an operator’s network can improve query times for client-side route planning applications by a factor of 2.4. However, it remains unclear whether this works for all network types, or other kinds of applications. To answer these questions, we must evaluate the same method on more networks and analyze the effect of geospatial partitioning on each network separately. In this paper we process three networks in Belgium: (i) the national railways, (ii) the regional operator in Flanders, and (iii) the network of the city of Brussels, using both real and artificially generated query sets. Our findings show that on the regional network, we can make query processing 4 times more efficient, but we could not improve the performance over the city network by more than 12%. Both the network’s topography, and to a lesser extent how users interact with the network, determine how suitable the network is for partitioning. Thus, we come to a negative answer to our question: our method does not work equally well for all networks. Moreover, since the network’s topography is the main determining factor, we expect this finding to apply to other graph-based geospatial data, as well as other Link Traversal-based applications.".
- jwe1540-9589.2045 datePublished "2021".
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- decentralized-footpaths author me.
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- decentralized-footpaths title "Decentralized Publication and Consumption of Transfer Footpaths".
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- decentralized-footpaths name "Decentralized Publication and Consumption of Transfer Footpaths".
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- decentralized-footpaths name "Decentralized Publication and Consumption of Transfer Footpaths".
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- decentralized-footpaths abstract "Users expect route planners that combine all modes of transportation to propose good journeys to their destination. These route planners use data from several sources such as road networks and schedule-based public transit. We focus on the link between the two; specifically, the walking distances between stops. Research in this field so far has found that computing these paths dynamically is too slow, but that computing all of them results in a quadratically scaling number of edges which is prohibitively expensive in practice. The common solution is to cluster the stops into small unconnected graphs, but this restricts the amount of walking and has a significant impact on the travel times. Moreover, clustering operates on a closed-world assumption, which makes it impractical to add additional public transit services. A decentralized publishing strategy that fixes these issues should thus (i) scale gracefully with the number of stops; (ii) support unrestricted walking; (iii) make it easy to add new services and (iv) support splitting the work among several actors. We introduce a publishing strategy that is based on the Delaunay triangulation of public transit stops, where every triangle edge corresponds to a single footpath that is precomputed. This guarantees that all stops are reachable from one another, while the number of precomputed paths increases linearly with the number of stops. Each public transit service can be processed separately, and combining several operators can be done with a minimal amount of work. Approximating the walking distance with a path along the triangle edges overestimates the actual distance by 20% on average. Our results show that our approach is a middle-ground between completeness and practicality. It consistently overestimates the walking distances, but this seems workable since overestimating the time needed to catch a connection is arguably better than recommending an impossible journey. The estimates could still be improved by combining the great-circle distance with our approximations. Alternatively, different triangulations could be combined to create a more complete graph.".
- decentralized-footpaths datePublished "2019".
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