A route planner based on Open Data
Keywords: Linked Data, Open Data, big data, mobility, route planning, smart cities
Supervision: Pieter Colpaert Ruben Verborgh
Students: max 1
We can imagine that an infinite amount of data can be used to advise you on how to get home by public transit (time tables and real-time updates), on foot (where are the side walks, criminality rates of neighborhoods), by car (road blocks or traffic events) and so forth. At IDLab we invented Linked Connections: a way to publish public transport data in real-time including the historic and planned data. We want you to experiment with creative ways to publish and query the Web for route planning advice.
The student will be part of our core team at IDLab to develop a multidimensional index for Linked Data Fragments. She or he will think about the trade-offs when publishing any kind of dataset in different dimensions, so that a public transit route planning algorithm can still be used (without this being the only goal of the publisher). The goal is to implement a more dynamic route planning client. We will evaluate our implementation on query execution time, but also bandwidth, flexibility, developer experience as well as end-user experience.