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PoDiGG : a public transport RDF dataset generator

Ruben Taelman (UGent) , Ruben Verborgh (UGent) , Tom De Nies (UGent) and Erik Mannens (UGent)
(2017) WWW'17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB. p.843-844
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Abstract
A large amount of public transport data is made available by many different providers, which makes RDF a great method for integrating these datasets. Furthermore, this type of data provides a great source of information that combines both geospatial and temporal data. These aspects are currently undertested in RDF data management systems, because of the limited availability of realistic input datasets. In order to bring public transport data to the world of benchmarking, we need to be able to create synthetic variants of this data. In this paper, we introduce a dataset generator with the capability to create realistic public transport data. This dataset generator, and the ability to configure it on different levels, makes it easier to use public transport data for benchmarking with great flexibility.

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Citation

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MLA
Taelman, Ruben, et al. “PoDiGG : A Public Transport RDF Dataset Generator.” WWW’17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, Association for Computing Machinery (ACM), 2017, pp. 843–44, doi:10.1145/3041021.3054210.
APA
Taelman, R., Verborgh, R., De Nies, T., & Mannens, E. (2017). PoDiGG : a public transport RDF dataset generator. WWW’17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 843–844. https://doi.org/10.1145/3041021.3054210
Chicago author-date
Taelman, Ruben, Ruben Verborgh, Tom De Nies, and Erik Mannens. 2017. “PoDiGG : A Public Transport RDF Dataset Generator.” In WWW’17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 843–44. Association for Computing Machinery (ACM). https://doi.org/10.1145/3041021.3054210.
Chicago author-date (all authors)
Taelman, Ruben, Ruben Verborgh, Tom De Nies, and Erik Mannens. 2017. “PoDiGG : A Public Transport RDF Dataset Generator.” In WWW’17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 843–844. Association for Computing Machinery (ACM). doi:10.1145/3041021.3054210.
Vancouver
1.
Taelman R, Verborgh R, De Nies T, Mannens E. PoDiGG : a public transport RDF dataset generator. In: WWW’17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB. Association for Computing Machinery (ACM); 2017. p. 843–4.
IEEE
[1]
R. Taelman, R. Verborgh, T. De Nies, and E. Mannens, “PoDiGG : a public transport RDF dataset generator,” in WWW’17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, Perth, Australia, 2017, pp. 843–844.
@inproceedings{8540847,
  abstract     = {{A large amount of public transport data is made available by many different providers, which makes RDF a great method for integrating these datasets. Furthermore, this type of data provides a great source of information that combines both geospatial and temporal data. These aspects are currently undertested in RDF data management systems, because of the limited availability of realistic input datasets. In order to bring public transport data to the world of benchmarking, we need to be able to create synthetic variants of this data. In this paper, we introduce a dataset generator with the capability to create realistic public transport data. This dataset generator, and the ability to configure it on different levels, makes it easier to use public transport data for benchmarking with great flexibility.}},
  author       = {{Taelman, Ruben and Verborgh, Ruben and De Nies, Tom and Mannens, Erik}},
  booktitle    = {{WWW'17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB}},
  isbn         = {{9781450349147}},
  language     = {{eng}},
  location     = {{Perth, Australia}},
  pages        = {{843--844}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{PoDiGG : a public transport RDF dataset generator}},
  url          = {{http://doi.org/10.1145/3041021.3054210}},
  year         = {{2017}},
}
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