DAEDALUS: A knowledge discovery analysis framework for movement data

In this work we propose DAEDALUS, a knowledge discovery system that enables a uniform querying of movement data and patterns. Such system is founded on a formal framework that defines knowledge discovery execution process as a progressive combination of mining and querying operators. The core component of DAEDALUS is the query language that extends SQL in two respects, namely a pattern definition operator and the capability of uniformly manipulate both raw data and unveiled patterns. DAEDALUS is specifically focussed on movement data and has been implemented as a query execution layer on top of the Hermes Moving Object Database. A qualitative evaluation of the system will show the power of DAEDALUS in progressive mining task over movement data.