5 Matching Annotations
  1. Feb 2022
  2. Sep 2021
  3. Mar 2020
    1. Not only are public transport datasets useful for benchmarking route planning systems, they are also highly useful for benchmarking geospatial [13, 14] and temporal [15, 16] RDF systems due to the intrinsic geospatial and temporal properties of public transport datasets. While synthetic dataset generators already exist in the geospatial and temporal domain [17, 18], no systems exist yet that focus on realism, and specifically look into the generation of public transport datasets. As such, the main topic that we address in this work, is solving the need for realistic public transport datasets with geospatial and temporal characteristics, so that they can be used to benchmark RDF data management and route planning systems. More specifically, we introduce a mimicking algorithm for generating realistic public transport data, which is the main contribution of this work.
  4. Feb 2020
  5. Jan 2020