A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
Maintaining knowledge about temporal intervals
Communications of the ACM
A Spatio-Temporal Taxonomy for the Representation of Spatial Set Behaviours
STDBM '99 Proceedings of the International Workshop on Spatio-Temporal Database Management
Spatio-Temporal Databases
Complex spatio-temporal pattern queries
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Geoinformatica
A query language for moving object trajectories
SSDBM'2005 Proceedings of the 17th international conference on Scientific and statistical database management
Conceptual Modeling for Traditional and Spatio-Temporal Applications: The MADS Approach
Conceptual Modeling for Traditional and Spatio-Temporal Applications: The MADS Approach
Reporting leadership patterns among trajectories
Proceedings of the 2007 ACM symposium on Applied computing
A conceptual view on trajectories
Data & Knowledge Engineering
Mobility, Data Mining and Privacy: Geographic Knowledge Discovery
Mobility, Data Mining and Privacy: Geographic Knowledge Discovery
Aggregation languages for moving object and places of interest
Proceedings of the 2008 ACM symposium on Applied computing
Understanding transportation modes based on GPS data for web applications
ACM Transactions on the Web (TWEB)
A taxonomy of collective phenomena
Applied Ontology
Goal-based trajectory analysis for unusual behaviour detection in intelligent surveillance
Image and Vision Computing
Spatiotemporal pattern queries
Geoinformatica
Semantic trajectories modeling and analysis
ACM Computing Surveys (CSUR)
On the Management and Analysis of Our LifeSteps
ACM SIGKDD Explorations Newsletter
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Mobility data is becoming an important player in many application domains. Many techniques have been elaborated to extract statistical knowledge from the data sets gathering raw data tracks about the moving objects of interest to an application. These data tracks obey the physical-level specifications of the devices used for data acquisition (GPS, GSM, RFID, smart phones, and other sensors). Nowadays, interest has shifted from raw data tracks analysis to more application-oriented ways of analyzing more meaningful movement records suitable for the specific purposes of the application at hand. This trend has promoted the concept of semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This keynote paper intends to provide the foundations of a semantic approach to data about movement. It focuses on the definitions of the most important concepts about mobility data, concepts that are frequently used but rarely rigorously defined.