An Approach to Semantic Processing of GPS Traces

Recording the movement of objects or persons with GPS-technology has been widely adopted. So called GPS traces are used for enriching travel diaries (Wolf et al. 2001), for learning significant places (Ashbrook and Starner 2003), for monitoring animal movement (Steiner et al. 2000) or for building road maps (Cao and Krumm 2009). While all of the mentioned applications rely on GPS traces, the methods for collecting and processing the data differ. One of the basic goals in processing GPS raw data is to extract re-occurring motion patterns (Laube et al. 2005, Zheng et al. 2008). In a current research project called HOTSPOT, we try to answer the question, which knowledge about an object or person's movement can be extracted from a single GPS trace. One of the unique aspects of the project is that our approach to knowledge extraction only relies on GPS raw data and explicitly avoids any kind of map matching or usage of additional data sources. In this position paper we tackle aspects of semantic data processing. With semantic data processing we refer to methods attaching meaning to sub-sequences of GPS traces. We propose a method for semantic processing of GPS traces, resulting in basic motion and course change activities. The method can be applied to any kind of raw GPS data and prepares the data for further analysis of motion patterns.