Semantic Trajectories Modeling and Analysis CHRISTINE PARENT, University of Lausanne STEFANO SPACCAPIETRA, Swiss Federal Institute of Technology (EPFL) CHIARA RENSO, ISTI-CNR GENNADY ANDRIENKO, Fraunhofer Institute IAIS NATALIA ANDRIENKO, Fraunhofer Institute IAIS VANIA BOGORNY, Federal University of Santa Catarina (INE/UFSC) MARIA LUISA DAMIANI, University of Milan ARIS GKOULALAS-DIVANIS, IBM Research-Zurich JOSE MACEDO, Federal University of Ceará NIKOS PELEKIS, University of Piraeus YANNIS THEODORIDIS, University of Piraeus ZHIXIAN YAN, Swiss Federal Institute of Technology (EPFL) ___________________________________________________________________ Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for i) constructing trajectories from movement tracks, ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the paper surveys the new privacy issues that rise due to the semantic aspects of trajectories. Categories and Subject Descriptors: H. Information Systems, H.2. Database Management, H.2.0 General General Terms: algorithms, design, legal aspects, management Additional Key Words and Phrases: movement, mobility tracks, tracking, mobility data, trajectories, trajectory behavior, semantic enrichment, data mining, activity identification, GPS ________________________________________________________________________ This work is supported by the EU, FET OPEN, 2009-2012 Programme, Coordination Action type Project MODAP (Mobility, Data Mining, and Privacy) http://www.modap.org Authors’ addresses: Gennady and Natalia Andrienko, Fraunhofer Institute IAIS, Schloss Birlinghoven, Sankt-Augustin, D- 53754 Germany, email: {gennady|natalia}.andrienko@iais.fraunhofer.de; Vania Bogorny, UFSC-CTC-INE, CEP 88040-900 - Campus Universitário Cx.P. 476, Florianópolis S.C., Brazil, vania@inf.ufsc.br; Maria Luisa Damiani: Università degi Studi di Milano, Via Comelico 39, 20135 Milano, Italy, email: mdamiani@dico.unimi.it; Aris Gkoulalas-Divanis: IBM Research GmbH, Säumerstrasse 4, CH-8803 Rüschlikon, Switzerland, agd@zurich.ibm.com; José Macedo: Campus do PICI, Computer Science Department, Fortaleza, Brazil, CEP 60.115-190, jose.macedo@lia.ufc.br; Christine Parent: Université de Lausanne HEC-ISI, 1015 Lausanne, Switzerland, email: christine.parent@unil.ch; Nikos Pelekis: Department of Statistics and Insurance Science, University of Piraeus, Karaoli-Dimitriou 80, Piraeus, GR-18534, Greece, email: npelekis@unipi.gr; Chiara Renso: ISTI–CNR, Via Moruzzi 1, 56010, Pisa, Italy, email: chiara.renso@isti.cnr.it; Stefano Spaccapietra and Zhixian Yan: EPFL-IC-LSIR, Station 14, CH-1015 Lausanne, email: {stefano.spaccapietra, zhixian.yan}@epfl.ch; Yannis Théodoridis: Department of Informatics, University of Piraeus, GR-18534 Piraeus, Greece, email: ytheod@unipi.gr 39