Determination of long-distance travel demand: How to merge distinct data sources into a meaningful and consistent picture?
Angelika Schulz, Tobias Kuhnimhof, Miriam Magdolen, Bastian Chlond, Katja Köhler
Abstract
Angelika Schulz, Tobias Kuhnimhof, Miriam Magdolen, Bastian Chlond, Katja Köhler
Abstract
Although for most travel segments data are available, there is no up-to-date and consistent overall picture of long-distance travel demand, neither in terms of total transport volumes, nor in terms of socio-demographic characteristics of the corresponding population and the driving forces. Analyses in this respect, however, require a meaningful data framework. The challenge is to gather and prepare available data according to a suitable definition of 'long-distance travel' and to close data gaps based on complementary data collection or any other empirically founded assumptions. The objective of this paper is fourfold: First, the challenge of data merging is described against the background of diverging definitions of long-distance travel. Secondly, the adopted approach of 'data fusion' is presented. Thirdly, the current picture of long-distance travel in Germany is outlined. Finally, methodological issues and challenges of data collection and data merging focusing on long-distance travel are discussed.
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Although for most travel segments data are available, there is no up-to-date and consistent overall picture of long-distance travel demand, neither in terms of total transport volumes, nor in terms of socio-demographic characteristics of the corresponding population and the driving forces. Analyses in this respect, however, require a meaningful data framework. The challenge is to gather and prepare available data according to a suitable definition of 'long-distance travel' and to close data gaps based on complementary data collection or any other empirically founded assumptions. The objective of this paper is fourfold: First, the challenge of data merging is described against the background of diverging definitions of long-distance travel. Secondly, the adopted approach of 'data fusion' is presented. Thirdly, the current picture of long-distance travel in Germany is outlined. Finally, methodological issues and challenges of data collection and data merging focusing on long-distance travel are discussed.
Key concepts: Merge (version control), Data collection, Computer science, Travel behavior, Travel time, Data science, Data mining, Econometrics