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ObjectStore is an object-oriented database system supporting persistence orthogonal to type, transaction management, and associative queries. Collections are provided as objects. The data model is non-1NF, as objects may have embedded collections. Queries are integrated with the host language in the form of query operators whose operands are a collection and a predicate. The predicate may itself contain a (nested) query operating on an embedded collection. Indexes on paths may be added and removed dynamically. Collections, being treated as objects, may be referred to indirectly, e.g., through a by-reference argument. For this reason and others, multiple execution strategies are generated, and a final selection is made just prior to query execution. Nested queries can result in interleaved execution and strategy selection.

Spatial queries can be evaluated in native space or in a parameter space. In the latter case, data objects are transformed into points and query objects are transformed into search regions. The requirement for different data and query representations may prevent the use of parameter-space searching in some applications. Native-space and parameter-space searching are compared in the context of a z order-based spatial access method. Experimental results show that when there is a single query object, searching in parameter space can be faster than searching in native space, if the data and query objects are large enough, and if sufficient redundancy is used for the query representation. The result is, however, less accurate than the native space result. When there are multiple query objects, native-space searching is better initially, but as the number of query objects increases, parameter space searching with low redundancy is superior. Native-space searching is much more accurate for multiple-object queries.

Spatial objects other than points and boxes can be stored in spatial indexes, but the techniques usually require the use of approximations that can be arbitrarily bad. This leads to poor performance and highly inaccurate responses to spatial queries. The situation can be improved by storing some objects in the index redundantly. Most spatial indexes permit no flexibility in adjusting the amount of redundancy. Spatial indexes based on z-order permit this flexibility. Accuracy of the query response increases with redundancy, (there is a “diminishing return” effect). Search time, as measured by disk accesses first decreases and then increases with redundancy. There is, therefore, an optimal amount of redundancy (for a given data set). The optimal use of redundancy for z-order is explored through analysis of the z-order search algorithm and through experiments.

Covers application as well as system aspects of managing and integrating unstructured and structured data. Problems of representation, features, and abstraction are discussed. Other aspects considered are browsing unstructured data and multimedia systems and text.>

The PROBE research project has produced results in the areas of data modeling, spatial/temporal query processing, recursive query processing, and database system architecture for nontraditional application areas, many of which involve spatial data and data with complex structure. An overview of PROBE is provided, focusing on the facilities for dealing with spatial and temporal data. It is shown how the PROBE database system and simple application-specific object classes combine to efficiently support PROBE's spatial data model. It is also shown how an image-database application can be supported using PROBE's data model and spatial query processor. The current status of the PROBE project and future plans are discussed.>

An object-oriented approach to management of engineering design data requires object persistence, object-specific rules for concurrency control and recovery, views, complex objects and derived data, and specialized treatment of operations, constraints, relationships and type descriptions. We discuss object-orientation as more than an implementation paradigm, and show how an object-oriented approach simplifies both use and implementation of engineering design systems.

DBMSs must offer spatial query processing capabilities to meet the needs of applications such as cartography, geographic information processing and CAD. Many data structures and algorithms that process grid representations of spatial data have appeared in the literature. We unify much of this work by identifying common principles and distilling them into a small set of constructs. (Published data structures and algorithms can be derived as special cases.) We show how these constructs can be supported with only minor modifications to current DBMS implementations. The ideas are demonstrated in the context of the range query problem. Analytical and experimental evidence indicates that performance of the derived solution is very good (e.g., comparable to performance of the kd tree.)

By interleaving the bits of the binary representations of the attribute values in a tuple, an integer corresponding to the tuple is created. A set of these integers represents a relation. The usual ordering of these integers corresponds to an ordering of multidimensional data that allows the use of conventional file organizations, such as Btrees, in the efficient processing of multidimensional queries (e.g. range queries). The class of data structures generated by this scheme includes a type of kd tree whose balance can be efficiently maintained, a multidimensional Btree which is simpler than previously proposed generalizations, and some previously reported data structures for range searching. All of the data structures in this class also support the efficient implementation of the set operations.