An Advanced Data Warehouse for Integrating Large Sets of GPS Data

Ove Andersen; Benjamin Bjerre Krogh; Christian Thomsen; Kristian Torp

doi:10.1145/2666158.2666172

An Advanced Data Warehouse for Integrating Large Sets of GPS Data

Ove Andersen, Benjamin Bjerre Krogh, Christian Thomsen, Kristian Torp

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

8 Citations (Scopus)

Abstract

GPS data recorded from driving vehicles is available from many sources and is a very good data foundation for answering traffic related queries. However, most approaches so far have not considered combining GPS data from many sources into a single data warehouse. Further, the integration of GPS data with fuel consumption data (from the so-called CAN bus in the vehicles) and weather data has not been done. In this paper, we propose a data warehouse design for handling GPS data, fuel consumption data, and weather data. The design is fully implemented in a running system using the PostgreSQL DBMS. The system has been in production since March 2011 and the main fact table contains today approximately 3.4 billion rows from 16 different data sources. We show that the system can be used for a number of novel traffic related analyses such as relating the fuel consumption of vehicles with the road network and road congestion.

Original language	English
Title of host publication	Proceedings of the 17th International Workshop on Data Warehousing and OLAP
Number of pages	10
Publisher	Association for Computing Machinery
Publication date	7 Nov 2014
Pages	13-22
ISBN (Print)	978-1-4503-0999-8
DOIs	https://doi.org/10.1145/2666158.2666172
Publication status	Published - 7 Nov 2014
Event	International Workshop on Data Warehousing and OLAP - , Hong Kong Duration: 7 Nov 2014 → 7 Nov 2014 Conference number: 17

Workshop

Workshop	International Workshop on Data Warehousing and OLAP
Number	17
Country/Territory	Hong Kong
Period	07/11/2014 → 07/11/2014

Keywords

data warehousing
GPS-data
integration

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10.1145/2666158.2666172

http://dl.acm.org/citation.cfm?id=2666172&dl=ACM&coll=DL&CFID=628211305&CFTOKEN=91499912

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title = "An Advanced Data Warehouse for Integrating Large Sets of GPS Data",

abstract = "GPS data recorded from driving vehicles is available from many sources and is a very good data foundation for answering traffic related queries. However, most approaches so far have not considered combining GPS data from many sources into a single data warehouse. Further, the integration of GPS data with fuel consumption data (from the so-called CAN bus in the vehicles) and weather data has not been done. In this paper, we propose a data warehouse design for handling GPS data, fuel consumption data, and weather data. The design is fully implemented in a running system using the PostgreSQL DBMS. The system has been in production since March 2011 and the main fact table contains today approximately 3.4 billion rows from 16 different data sources. We show that the system can be used for a number of novel traffic related analyses such as relating the fuel consumption of vehicles with the road network and road congestion.",

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booktitle = "Proceedings of the 17th International Workshop on Data Warehousing and OLAP",

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An Advanced Data Warehouse for Integrating Large Sets of GPS Data. / Andersen, Ove; Krogh, Benjamin Bjerre; Thomsen, Christian et al.
Proceedings of the 17th International Workshop on Data Warehousing and OLAP . Association for Computing Machinery, 2014. p. 13-22.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - An Advanced Data Warehouse for Integrating Large Sets of GPS Data

AU - Andersen, Ove

AU - Krogh, Benjamin Bjerre

AU - Thomsen, Christian

AU - Torp, Kristian

N1 - Conference code: 17

PY - 2014/11/7

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N2 - GPS data recorded from driving vehicles is available from many sources and is a very good data foundation for answering traffic related queries. However, most approaches so far have not considered combining GPS data from many sources into a single data warehouse. Further, the integration of GPS data with fuel consumption data (from the so-called CAN bus in the vehicles) and weather data has not been done. In this paper, we propose a data warehouse design for handling GPS data, fuel consumption data, and weather data. The design is fully implemented in a running system using the PostgreSQL DBMS. The system has been in production since March 2011 and the main fact table contains today approximately 3.4 billion rows from 16 different data sources. We show that the system can be used for a number of novel traffic related analyses such as relating the fuel consumption of vehicles with the road network and road congestion.

AB - GPS data recorded from driving vehicles is available from many sources and is a very good data foundation for answering traffic related queries. However, most approaches so far have not considered combining GPS data from many sources into a single data warehouse. Further, the integration of GPS data with fuel consumption data (from the so-called CAN bus in the vehicles) and weather data has not been done. In this paper, we propose a data warehouse design for handling GPS data, fuel consumption data, and weather data. The design is fully implemented in a running system using the PostgreSQL DBMS. The system has been in production since March 2011 and the main fact table contains today approximately 3.4 billion rows from 16 different data sources. We show that the system can be used for a number of novel traffic related analyses such as relating the fuel consumption of vehicles with the road network and road congestion.

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KW - GPS-data

KW - integration

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DO - 10.1145/2666158.2666172

M3 - Article in proceeding

SN - 978-1-4503-0999-8

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EP - 22

BT - Proceedings of the 17th International Workshop on Data Warehousing and OLAP

PB - Association for Computing Machinery

T2 - International Workshop on Data Warehousing and OLAP

Y2 - 7 November 2014 through 7 November 2014

ER -

An Advanced Data Warehouse for Integrating Large Sets of GPS Data

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Keywords

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