Urban areas get more and more congested everyday due to the increasing number of moving vehicles. This imposes the need for efficient analysis, modeling, and processing of traffic data. Moreover, the extraction of additional information about traffic conditions, optional routes and the possible prediction of troublesome situations, such as traffic jams, becomes necessary. In this work, we describe the analysis, pre-processing, modeling, and storage techniques for trajectory data that constitute a Moving Object Database (MOD). MOD is the backbone of the ΙΧΝΗΛΑΤΗΣ 1 system, which specifically focuses on extracting further information about the movement of vehicles in the Athens municipal area. Based on real-world requirements, we initially analyse the traffic data and make modeling decisions to capture these requirements in a MOD. We, then, design MOD focusing on the spatiotemporal concepts, relations and restrictions among the characteristic concepts of the system −namely, the vehicles, trajectories, and roads. Furthermore, specific, innovative preprocessing, design, and storage techniques for the trajectory data in MOD are given. Then, we present the architecture of ΙΧΝΗΛΑΤΗΣ; its core components are the characteriser, cluster finder, and associator, which are used to perform data extraction in MOD. A mining language to accommodate typical data extraction queries is presented, in terms of syntax and semantics. Answers to characteristic, complex, questions on MOD, which are based on real-world data about traffic in the Athens Metropolitan Area, show the applicability of the approach. In this paper, we describe the formatting guidelines for ACM SIG Proceedings. KeywordsData model, data mining, moving objects. MOTIVATIONAs the number of moving vehicles increases rapidly everyday, the need for analysis, modeling and processing of traffic data is vital. Moreover, the extraction of additional information about traffic conditions, optional routes and possible prediction of troublesome situations, such as traffic jams, becomes necessary.In this work, we deal with the analysis, pre-processing, modeling and storage techniques of traffic data in a Moving Object Database (MOD) for a traffic management system. Furthermore, 1 ΙΧΝΗΛΑΤΗΣ ('PATH-FINDER' in Greek): A research project funded by the Hellenic General Secretariat of Research and Technology (2002-2004).we apply data extraction techniques in MOD, assisting the prediction of difficult situations, or optional cases, such as alternative routes when traffic is congested.In order to realize MOD, based on real-world requirements about traffic in the Athens Metropolitan Area, we analyse the fundamental concept of the movement of a vehicle and register its semantics and properties in terms of a conceptual model. We organize them in a database, including vehicles, routes, trajectories (i.e., traces left behind, as vehicles move), and relations among them.Building a MOD is not a trivial issue. It consists of (i) spatial data, (i) non-spatial data and (iii) trajectories....

A special-purpose extension of the Entity-Relationship model for the needs of conceptual modeling of geographic applications, called the Geo-ER Model, is presented. Handling properties associated to objects not because of the objects' nature but because of the objects' position , calls for dealing -at the semantic modeling level-with space, location and dimensionality of objects, spatial relationships, space-depending attributes, and scale and generalization of representations. In order to accomplish this in the framework of ER and its derivatives, we introduce special entity sets, relationships, and add new constructs. The rationale as well as examples of usage of the Geo-ER model from actual projects are presented.

Heterogeneous geographic databases contain multiple views of the same geographic objects at different levels of spatial resolution. When users perceive geographic objects as one spatial unit, although they are physically separated into multiple parts, appropriate methods are needed to assess the consistency among the aggregate and the parts. The critical aspect is that the overall spatial relationships with respect to other geographic objects must be preserved throughout the aggregation process. We developed a systematic model for the constraints that must hold with respect to other spatial objects when two parts of an object are aggregated. We found three sets of configurations that require increasingly more information in order to make a precise statement about their consistency: (1) configurations that are satisfied by the topological relations between the two parts and the object of interest; (2) configurations that need further information about the topological relation between the object of concern and the connector in order to be resolved unambiguously; and (3) configurations that require additional information about the topological relation between the aggregate's boundary and the boundary or interior of the object of interest to be uniquely described. The formalism extends immediately to relations between two regions with disconnected parts as well as to relations between a region and an arbitrary number of separations.

For some spatiotemporal applications, it can be assumed that the modeled world is precise and bounded, and that also our record of it is precise. While these simplifying assumptions are sufficient in applications like a land information system, they are unnecessarily crude for many other applications that manage data with spatial and/or temporal extents, such as navigational applications. This work explores fuzziness and uncertainty, subsumed under the term indeterminacy, in the spatiotemporal context. To better illustrate the basic spatiotemporal concepts of change or evolution, it is shown how the fundamental modeling concepts of spatial objects, attributes, and relationships and time points and periods are influenced by indeterminacy and how they can be combined. In particular, the focus is on the change of spatial objects and their geometries across time. Four change scenarios are outlined, which concern discrete versus continuous change and asynchronous versus synchronous measurement, and it is shown how to model indeterminacy for each. A case study illustrates the applicability of the paper's general proposal by describing the uncertainty related to the management of the movements of point objects, such as the management of vehicle positions in a fleet management system.

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