The GPS trajectory databases serve as bases for many intelligent applications that need to extract some trajectories for future processing or mining. When doing such tasks, spatio-temporal range queries based methods, which find all sub-trajectories within the given spatial extent and time interval, are commonly used. However, the history trajectory indexes of such methods suffer from two problems. First, temporal and spatial factors are not considered simutaneously, resulting in low performance when processing spatio-temporal queries. Second, the efficiency of indexes is sensitive to query size. The query performance changes dramatically as the query size changed. This paper proposes workload-aware Adaptive OcTree based Trajectory clustering Index (ATTI) aiming at optimizing trajectory storage and index performance. The contributions are three-folds. First, the distribution and time delay of the trajectory storage are introduced into the cost model of spatio-temporal range query; Second, the distribution of spatial division is dynamically adjusted based on GPS update workload; Third, the query workload adaptive mechanism is proposed based on virtual OcTree forest. A wide range of experiments are carried out over Microsoft GeoLife project dataset, and the results show that query delay of ATTI could be about 50% shorter than that of the nested index.

The increase in the advanced location based services such as traffic coordination and management necessitates the need for advanced models tracking the positions of Moving Objects (MOs) like vehicles. Due to computer processing limitations, it is impossible for MOs to continuously update their locations. This results in the uncertainty nature of a MO's location between any two reported positions. Efficiently managing and quantifying the uncertainty regions of MOs are needed in order to support different types of queries and to improve query response time. This challenging problem of modeling uncertainty regions associated with MO was recently addressed by researchers and resulted in models that ranged from linear which require few properties of MOs as input to the models, to non-linear that are able to more accurately represent uncertainty regions by considering higher degree input. This paper summarizes and discusses approaches in modeling uncertainty regions associated with MOs. It further illustrates the need for appropriate approximations especially in the case of non-linear models as the uncertainty regions become rather irregularly shaped and difficult to manage. Finally, we demonstrate through several experimental sets the advantage of non-linear models over linear models when the uncertainty regions of MOs are approximated by two different approximations; the Minimum Bounding Box (MBB) and the Tilted Minimum Bounding Box (TMBB).

Support of collaborative work and management of spatio-temporal data has become one of the most interesting and important database applications, which is due to the tremendous progress of database and its surrounding technologies in the last decade. In this paper, we investigate the new generation database technologies that are needed to support such advanced applications. Because of the recent progress of virtual reality technology, virtual work spaces are now available. We examine a typical CSCW (Computer Supported Cooperative Work) fsystem to identify database problems that arise from it. We introduce typical approaches to database improvement based on the high-level view and the virtual reality technique. Also, in this paper, the following are introduced and discussed: the design and implementation of three- and four-dimensional spatio-temporal database systems, VRML (Virtual Reality Modeling Language) database systems, fast access methods to spatio-temporal data, and the interval-based approach to temporal multimedia databases.

This paper describes a way of implementing a conceptual model for temporal data on a commercial object database system. The implemented version is provided as a class library. The library enables applications to handle temporal data. Any application can employ the library because it does not depend on specific applications. Furthermore, we propose an enhanced version of Time Index. The index efficiently processes event queries in particular. These queries search time intervals in which given events are all valid. We also investigate the effectiveness of the enhanced Time Index.

Object-Oriented database systems (OODBMS) are well known for modeling complex and dynamic application domains. Typically OODBMS have to handle large and complex structured objects whose values and structures can change frequently. Consequently there is a high demand for systems which support temporal and versioning features in both objects (or database population) and schema. This paper presents a mechanism for accessing the temporal versioned objects stored in the database which supports schema versioning. The results shown here can be considered as a value-added extension of our model called TVOO described in detail in [1] and [2]. In contrast to conventional database models, in TVOO objects and classes are not physically discarded from the database after they are modified or deleted. They are time dependent and the history of the changes which occur on them are kept as Version hierarchies. Therefore our model enriches the database environment with temporal and versioning features. Also, an access mechanism which makes it possible to access any object under any schema version is defined in such a way that not only objects created under old versions of schema classes can be accessed from new versions, but also objects created by new schema class versions can be accessed from old versions of the respective class.

This paper discusses an object-oriented approach to temporal multimedia data modeling in OMEGA; a multimedia database management under development at the University of Library and Information Science. An object-orientated approach is necessary to integrate various types of heterogeneous multimedia data, but it has become clear that current object-oriented data models are not sufficient to represent multimedia data, particularly when they are temporal. For instance, the current object-oriented data models cannot describe objects whose attribute values change time-dependently. Also, they cannot represent temporal relationships among temporal multimedia objects. We characterize temporal objects as instances of a subclass of class TimeInterval with the temporal attributes and the temporal relationships. This temporal multimedia data model is designed upward compatible with the ODMG-93 standard object model. To organize a temporal multimedia database, a five temporal axes model for representing temporal multimedia objects is also introduced. The five temporal axes--an absolute, an internal, a quasi-, a physical, and a presentation time axis--are necessary to describe time-dependent properties of multimedia objects in modeling, implementing and use. A concrete example of this organization method is also illustrated.