Memorias de investigación
Ponencias en congresos:
Providing Reliable Access to Real-Time and Historic Public Transport Data Using Linked Connections
Año:2017
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Using Linked Data based approaches, public transport companies are able to share their time tables and its updates in an affordable way while allowing user agents to perform multimodal route planning algorithms. Providing time table updates, usually published as data streams, means that data is being constantly modified and in the presence of large analytical queries, results might be affected due to the changing data. In this demo we introduce a mechanism to tackle this problem by guaranteeing that a user agent will always receive version based responses, therefore ensuring data consistency. Such mechanism also enables access to historical data that could be used for deep analysis of transport systems. However, how this data shall be archived, in order to keep this approach scalable and inexpensive is still a matter of study. In a demonstrator, we published and query data from the Belgium national train system (SNCB) and Madrid Regional Transport Consortium (CRTM). This paper represents the first step towards establishing an affordable framework to publish reliable transport data.
Internacional
Si
Nombre congreso
16th International Semantic Web Conference
Tipo de participación
970
Lugar del congreso
Viena, Austria
Revisores
Si
ISBN o ISSN
1613-0073
DOI
Fecha inicio congreso
23/10/2017
Fecha fin congreso
25/10/2017
Desde la página
446
Hasta la página
450
Título de las actas
Proceedings of the ISWC 2017 Posters & Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Julián Rojas Ghent University
  • Autor: David Chaves Fraga UPM
  • Autor: Pieter Colpaert Ghent University
  • Autor: Ruben Verborgh Ghent University
  • Autor: Erik Mannens Ghent University
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial