Abstract not found

Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as three-dimensional (2D space + time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for sp...

We consider spatio-temporal databases supporting spatial objects with continuously changing position and extent, termed moving objects databases. We formally define a data model for such databases that includes complex evolving spatial structures such as line networks or multi-component regions with holes. The data model is given as a collection of data types and operations which can be plugged as attribute types into any DBMS data model (e.g. relational, or object-oriented) to obtain a complete model and query language. A particular novel concept is the sliced representation which represents a temporal development as a set of units, where unit types for spatial and other data types represent certain "simple" functions of time. We also show how the model can be mapped into concrete physical data structures in a DBMS environment. 1 Introduction A wide and increasing range of database applications has to deal with spatial objects whose position and/or extent changes over time...

Spatial data types or algebras for database systems should (1) be fully general, that is, closed under set operations, (2) have formally defined semantics, (3) be defined in terms of finite representations available in computers, (4) offer facilities to enforce geometric consistency of related spatial objects, and (5) be in-dependent of a particular DBMS data model, but cooperate with any. We present an algebra that uses realms as geometric domains underlying spatial data types. A realm, as a general database concept, is a finite, dynamic, user-defined structure underlying one or more system data types. Problems of numerical robustness and topological correctness are solved within and below the realm layer so that spatial algebras defined above a realm have very nice algebraic properties. Realms also interact with a DMBS to enforce geometric consistency on object creation or up-date. The ROSE algebra is defined on top of realms and offers general types to represent point, line, and region features, together with a comprehensive set of operations. It is described within a polymorphic type system and interacts with a DMBS data model and query language through an abstract object model interface. An example integration of ROSE into the object-oriented data model 02 and its query language is presented.

Contents 1 Introduction 2 2 Map Data Modeling 4 2.1 Two-Dimensional Spatial Entities and Relationships . . . . . . . . . . . . . . . . . . . . . 4 2.2 Raster and Vector Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3 Subdivisions as Cell Complexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.4 Topological Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.5 Multiresolution Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3 Map data processing 8 3.1 Spatial Queries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2 Map Overlay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.3 Geometric Problems in Map Generalization . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.4 Map Labeling . . . . . . . . . . . . . . . . . . . . . . . . . . .

Over the last ten years, a subfield of GIScience has been recognized that addresses the linkage between human thought regarding geographic space and the mechanisms of implementing these in computational models. This research area has developed an identity through a series of successful international conferences and the establishment of a journal. It has also been complemented through community activities such as international standardization efforts and GIS interoperability. Historically, much of the advancement in computational methods has occurred at---or close to---the implementation level, as exemplified by the attention on the development of spatial access methods. Significant progress has been made at the levels of spatial data models and spatial query languages, although we note the lack of a comprehensive theoretical framework comparable to the relational data model in databases management systems. The difficult problems that need future research efforts are at the highly abstract level of capturing semantics of geographic information. A cognitive motivation is most promising as it shapes the focus on the users' needs and points of view, rather than on efficiency as in the case of a bottom-up system design. We also identify the need for new research in fields, models of qualitative spatial information, temporal aspects, knowledge discovery, and the integration of GIS with database management systems.

The use of scripting makes it possible to overcome many important difficulties in the development of database applications. By extending a general-purpose scripting language with constructs derived both from the database kernel and from the intended application domain, issues such as query processing and user interfacing can be approached in an economical and flexible way. This is illustrated by describing our experience with SAND-Tcl, a scripting tool developed by us for building spatial database applications. SAND-Tcl is an extension of the Tcl embedded scripting language with the constructs of the SAND environment for developing applications involving both spatial and non-spatial data. SANDTcl acts as a "glue" to hold together all the subsystems of SAND. In fact, query evaluation plans are SAND-Tcl programs (or scripts) which are written on-the-fly by SAND in response to a query defined by the user. This permits the rapid prototyping of algorithms and makes SAND a useful tool both f...

(ii) a component-based design in which spatial, temporal and historical extensions are formalised incrementally, for subsequent use together or separately; (iii) compatibility with mainstream query processing frameworks for object databases; and (iv) the integration of the spatio-temporal proposal with the ODMG standard. Spatio-temporal extensions to data models have been an active area of research for a number of years. To date, much of this work has focused on the relational data model, with object data models receiving far less consideration. Where descriptions of such object models do exist, there is currently a lack of systems which build upon these models to 1

Many geographical applications deal with spatial objects that cannot be adequately described by determinate, crisp concepts because of their intrinsically indeterminate and vague nature. Current geographical information systems and spatial database systems are unable to cope with this kind of data. To support such data and applications, we introduce vague spatial data types for vague points, vague lines, and vague regions. These data types cover and extend previous approaches and are part of a data model called VASA (Vague Spatial Algebra). Their formal framework is based on already existing, general exact models of crisp spatial data types, which simplifies the definition of the vague spatial model. In addition, we obtain executable specifications for the operations which can be immediately used as implementations. This paper gives a formal definition of the three vague spatial data types as well as some basic operations and predicates. A few example queries illustrate the embedding and expressiveness of these new data types in query languages.

A realm is a planar graph over a finite resolution grid that has been proposed as a means of overcoming problems of numerical robustness and topological correctness in spatial database systems. While the realm structure and the spatial algebra that is associated with it provide a range of desirable facilities for modelling spatial information in database systems, widespread exploitation will only be practical if efficient implementation strategies are identified. This paper shows how data types can be supported efficiently over virtual realms, where the finite resolution grid is not stored explicitly, but is generated only partially and as needed. This approach avoids the considerable storage space overheads associated with the original proposal for the implementation of realms, and provides overall runtime performance that often improves upon that of less space efficient implementation strategies.