Trajectory Data Set from GeoLife Project

GeoLife GPS Trajectories
http://research.microsoft.com/en-us/downloads/b16d359d-d164-469e-9fd4-da...

This is a GPS trajectory dataset collected in (Microsoft Research Asia) GeoLife project by 165 users in a period of over two years (from April 2007 to August 2009). This dataset recoded a broad range of users¡¯ outdoor movements, including not only life routines like go home and go to work but also some entertainments and sports activities, such as shopping, sightseeing, dining, hiking, and cycling. Therefore, the dataset can be used in many research fields, such as mobility pattern mining, user activity recognition, location-based social networks, and location recommendation. Please cite the following two papers when using this GPS dataset. [1] Yu Zheng, Like Liu, Longhao Wang, Xing Xie. Learning Transportation Modes from Raw GPS Data for Geographic Application on the Web, In Proceedings of International conference on World Wild Web (WWW 2008), Beijing, China. ACM Press: 247-256. [2] Yu Zheng, Lizhu Zhang, Xing Xie, Wei-Ying Ma. Mining interesting locations and travel seque!
nces from GPS trajectories. In Proceedings of International conference on World Wild Web (WWW 2009), Madrid Spain. ACM Press: 791-800. Refer to the user guide attached in the dataset for details.

The data set can be downloaded at http://research.microsoft.com/en-us/downloads/b16d359d-d164-469e-9fd4-da...

 

MODAP Consortium

The consortium consists of 11 partners from 7 countries in Europe.
Sabanci University (Coordinator) Fraunhofer IAIS Hasselt University
CNR - Area Della Ricerca di Pisa Université de Lausanne EPFL - Ecole Polytechnique Fédérale de Lausanne University of Piraeus Research Centre University of Milan
Wind Telecomunicazioni SpA Alterra B.V. EPFL - National Kapodistrian University of Athens

Sponsors

MODAP Project funded by:
European Union FET-OPEN
EU FET-OPEN 2009-2012
The Future and Emerging Technologies Open Scheme