Showing papers on "Spatiotemporal database published in 1995"

Ranking in Spatial Databases

Abstract: An algorithm for ranking spatial objects according to increasing distance from a query object is introduced and analyzed. The algorithm makes use of a hierarchical spatial data structure. The intended application area is a database environment, where the spatial data structure serves as an index. The algorithm is incremental in the sense that objects are reported one by one, so that a query processor can use the algorithm in a pipelined fashion for complex queries involving proximity. It is well suited for k nearest neighbor queries, and has the property that k needs not be fixed in advance.

Knowledge Discovery in Large Spatial Databases: Focusing Techniques for Efficient Class Identification

Abstract: Both, the number and the size of spatial databases are rapidly growing because of the large amount of data obtained from satellite images, X-ray crystallography or other scientific equipment Therefore, automated knowledge discovery becomes more and more important in spatial databases So far, most of the methods for knowledge discovery in databases (KDD) have been based on relational database systems In this paper, we address the task of class identification in spatial databases using clustering techniques We put special emphasis on the integration of the discovery methods with the DB interface, which is crucial for the efficiency of KDD on large databases The key to this integration is the use of a well-known spatial access method, the R*-tree The focusing component of a KDD system determines which parts of the database are relevant for the knowledge discovery task We present several strategies for focusing: selecting representatives from a spatial database, focusing on the relevant clusters and retrieving all objects of a given cluster We have applied the proposed techniques to real data from a large protein database used for predicting protein-protein docking A performance evaluation on this database indicates that clustering on large spatial databases can be performed, both, efficiently and effectively

A database interface for clustering in large spatial databases

Abstract: Both the number and the size of spatial databases are rapidly growing because of the large amount of data obtained from satellite images, X-ray crystallography or other scientific equipment. Therefore, automated knowledge discovery becomes more and more important in spatial databases. So far, most of the methods for knowledge discovery in databases (KDD) have been based on relational database systems. In this paper, we address the task of class identification in spatial databases using clustering techniques. We present an interface to the database management system (DBMS), which is crucial for the efficiency of KDD on large databases. This interface is based on a spatial access method, the R*-tree. It clusters the objects according to their spatial neighborhood and supports efficient processing of spatial queries. Furthermore, we propose a method for spatial data sampling as part of the focusing component, significantly reducing the number of objects to be clustered. Thus, we achieve a considerable speed-up for clustering in large databases. We have applied the proposed techniques to real data from a large protein database used for predicting protein-protein docking. A performance evaluation on this database indicates that clustering on large spatial databases can be performed both efficiently and effectively using our approach.

Schema and Database Evolution in the O2 Object Database System

Abstract: When the schema of an object-oriented database system is modified, the database needs to be changed in such a way that the schema and the database remain consistent with each other. This paper describes the algorithm implemented in the new forthcoming release of the 02 object database for automatically bringing the database to a consistent state after a schema update has been performed. The algorithm, which uses a deferred strategy to update the database, is a revised and extended version of the screening algorithm first sketched in [7].

Process and apparatus for simplifying access to information stored in databases

Abstract: Simplified access to relational databases is achieved. The inherent relationships that exist between tables in a relational database are detected and a dictionary is constructed that contains attributes that defines the relationships that exist within the database. The attributes of the database contained within the dictionary are mapped to objects of the database so that a user can navigate the database without using a database programming language using menus created from the dictionary.

Spatial Databases, The Final Frontier

Abstract: During the last decade database systems are used to represent spatial information mainly in the twodimensional plane or the three-dimensional space. Applications that rely on spatial databases can be found in CAD-CAM, VLSI, robotics, historical databases, geographical information systems, architectural sciences, visual perception and autonomous navigation, tracking, environmental protection and medical imaging.

Temporal database system implementations

Abstract: Although research on temporal database systems has been active for about 20 years, implementations have not appeared until recently. This is one reason why current commercial database systems provide only limited temporal functionality. This paper summarizes extant state of the art of temporal database implementations. Rather than being very specific about each system we have attempted to provide an indication of the functionality together with pointers to additional information. It is hoped that this leads to more efforts pushing the implementation of temporal database systems in the near future.

Management of uncertainty in database systems

Abstract: As models of the real world, databases are often permeated with forms of uncertainty, including imprecision, incompleteness, vagueness, inconsistency, and ambiguity. This chapter addresses issues of database uncertainty. It defines basic terminology, and it classifies the various kinds of uncertainty. It then surveys solutions that have been attempted, and it speculates on the reasons that have hindered the development of generalpurpose database systems with powerful uncertainty capabilities. Finally, it describes challenging new applications that will require such capabilities, and it points to promising directions for research.

Optimal Redundancy in Spatial Database Systems

Abstract: In spatial database systems rectangles are commonly used to approximate real spatial data. A technique that approximates extended objects with a collection of rectangles is the z-ordering method. Since each of these rectangles eventually corresponds to an entry in a spatial index, the object may be referenced several times. This redundancy effect is controllable. In this paper, we present an empirically derived formula to assess the expected redundancy for the z-ordering approximation technique given some simple parameters. After showing the applicability of this formula to a large class of different object geometries, we make use of this result to determine the optimal redundancy for real spatial data by means of theoretical considerations. In order to verify our theoretical results, we conducted several experiments using real spatial data and found a good correspondence.

Estimating data accuracy in a federated database environment

Abstract: The need for integration of data in a heterogeneous or federated database environment creates a corresponding need for estimating the accuracy of the integrated data as a function of the accuracy of the originating data sources. Even in a single database system, different base relations are frequently characterized by dissimilar levels of accuracy; however, no technique exists for defining the accuracy of this single database system in terms of the accuracy of the base relations. This need is further heightened in the case of federated environments involving multiple heterogeneous databases. To address this need, a generalized method is proposed for estimating the overall data accuracy in terms of the accuracy of relevant base relations and the actual database query. The query is examined in terms of its underlying set of base operators. A rigorous theoretical framework encompassing all these possible base operators is presented in this paper using the relational model. While the accuracy estimates are postulated on the basis of uniform distribution, the implications of non-uniform error distributions are also examined in theoretical terms. Finally, a running example is utilized to highlight the practical implications of the proposed theoretical framework.

Visual Database Systems 3

Abstract: This paper discusses the design and implementation of interactive smooth zooming of a starfield display (which is a visualization of a multi-attribute database) and introduces the zoom bar, a new widget for zooming and panning. Whereas traditional zoom techniques are based on zooming towards or away from a focal point, this paper introduces a novel approach based on zooming towards or away from a fixed line. Starfield displays plot items from a database as small selectable glyphs using two of the ordinal attributes of the data as the variables along the display axes. One way of filtering this visual information is by changing the range of displayed values on either of the display axes. If this is done incrementally and smoothly, the starfield display appears to zoom in and out, and users can track the motion of the glyphs without getting disoriented by sudden, large changes in context.

DISCO: A Constraint Database System with Sets

Abstract: This paper describes the implementation of a constraint database system with integer and set of integers data types. The system called DISCO allows Datalog queries and input databases with both integer gap-order [30] and set order constraints [31]. The DISCO query language can easily express many complex problems involving sets. The paper also presents efficient running times for several sample queries.

Extending Temporal Relational Databases to Deal with Imprecise and Qualitative Temporal Information

Abstract: In several application domains, there is a need for historical databases supporting also imprecise and qualitative temporal information. We propose a formal theory for handling imprecise and qualitative temporal information in a relational temporal database. In particular, we introduce a relational algebra in which the traditional operators are extended in order to deal with imprecise and qualitative time; we examine the properties of the operators, showing that the algebra we introduce is a consistent extension of the snapshot algebra. Finally, we show how a temporal relational database based on this theory can be built on top of a conventional relational database.

Research Foundations in Object-Oriented and Semantic Database Systems

Abstract: Will reading habit influence your life? Many say yes. Reading research foundations in object oriented and semantic database systems is a good habit; you can develop this habit to be such interesting way. Yeah, reading habit will not only make you have any favourite activity. It will be one of guidance of your life. When reading has become a habit, you will not make it as disturbing activities or as boring activity. You can gain many benefits and importances of reading.

Design of Temporal Relational Databases Based on Dynamic and Temporal Functional Dependencies

Abstract: In earlier work, we introduced dynamic and temporal functional dependencies (DFDs and TFDs), which are used in conjunction with conventional functional dependencies. The purpose of this paper is to study how DFDs and TFDs affect database design in a temporally ungrouped historical data model. The result is a generalization of conventional normalization theory for temporal databases.

Database Issues for Data Visualization: Supporting Interactive Database Explorartion

Abstract: A recurrent theme from the Second Database Issues for Data Visualization workshop was the importance of interactively exploring databases using numerous tools and techniques. Database exploration is a discovery process where relevant information or knowledge is identified and extracted from data. It is related to the field of Knowledge Discovery in Databases (KDD), and emphasizes the process of knowledge discovery: the development of hypotheses about the data, and the validation of those hypotheses. Discovery is not only possible from analytic tools, but also from graphical, textual, numeric, and tabular presentations of data. Flexibility in data processing and output presentation are fundamental requirements of any data exploration environment. A shared sentiment among workshop participants was that database exploration requires the cooperation of database management, data analysis and data visualization facilities, as shown in Figure 1. Interaction is also central to database exploration. The user must interact with data to discover information. User-data interactions must, then, be supported by an integrated exploration system. Because of the potential complexity of such a system, interactions occur at many levels between the data, system and user. These include interactions among software modules and user-data interfaces. Process management will play a larger role in the development of adequate exploration environments, because such environments will be integrations of numerous types of systems that focus on smaller aspects of the overall problem. If we are to realize any benefits from such an integration, the whole must be greater than the sum of the components.

Accessing a Relational Database through an Object-Oriented Database Interface

Abstract: Object-oriented database systems (ODBs) are designed for use in applications characterized by complex data models, clean integration with the host programming language, and a need for extremely fast creation, traversal, and update of networks of objects These applications are typically written in C or C++, and the problem of how to store the networks of objects, and update them atomically has been difficult in practice Relational database systems (RDBs) tend to be a poor fit for these applications because they are designed for applications with different performance requirements ODBs are designed to meet these requirements and have proven more successful in pioviding”persistence for applications such as ECAD and MCAD’ Interest in ODBs has-spread be$ond the CAD communities, to areas such as finance and telecommunications These applications have many similarities to CAD applications For example, in financial applications, the data structures describing a mutual fund’s portfolio can be quite complex, applications are written in C or C++, and fast traversal of the data structures is important These application areas often have an additional requirement the need to make use of “legacy” data stored in relational database systems (RDBs) For years, the developers of these applications have worked in non-object-oriented languages; and have had to deal with the problem of turning tuple streams into the complex data structures manipulated by their applications Now, the developers who have started using object-oriented languages and database systems would like to continue the transition by insulating themselves from the relational model and SQL

Dynamic and Flexible Vision of a Spatial Database

Abstract: Today geographical databases must provide a dynamic and flexible data model. The notion of spatial view allows different, independent external interpretations of a database schema. A spatial view is an extension of the classical view concept as found in relational databases. A spatial view is a set of atoms. Each atom is defined with a set of database relations, a set of conventional spatial and non spatial database operators and a set of visualization operators. Manipulations of views allow building of new views according to specific needs.

A Language for the Support of Constraints in Temporal Active Databases

Abstract: Complex applications in domains such as decision analysis and real time systems require a database that supports active enforcement of constraints with temporal aspects. In this paper we present a temporal active language for the support of constraints in temporal active databases. The language primitives are presented using examples and an EBNF, followed by a discussion of the language properties.

A Non-Uniform Data Fragmentation Strategy for Parallel Main-Menory Database Systems

Abstract: In multi-processor database systems there are processor initialization and inter-communication overheads that diverge real systems from the ideal linear behaviour as the number of processors increases. Main-memory database systems suffer more since the database processing cost is small compared to disk-based database systems and thus comparable to the processor initialization cost. The usual uniform data fragmentation strategy divides a relation into equal data partitions, leading to idleness of single processors after local query execution termination and before global termination. In this paper, we propose a new, non-uniform data fragmentation strategy that results in concurrent termination of query processing among all the processors. The proposed fragmentation strategy is analytically modeled, simulated and compared to the uniform strategy. It is proven that the non-uniform fragmentation strategy offers inherently better performance for a parallel database system than the uniform strategy. Furthermore, the non-uniform strategy scales-up perfectly till an upper limit, after which a system re-configuration is needed.

Spatial Database Querying with Logic Languages

Abstract: Several d&rent data structures, generally grouped in Raster and Vectors representation models, are used to store images and all hinds of spatial data. One solution, for a spatial data manipulation language to be independent of the storage model, is to base the language on the spatial relations of objects (i.e. the positions of objects relative to each other). This paper proposes a logic intermediate language allowing a declarative querying. We show that this language can be easily computed by a procedural execution using a small set of operators. This language enables expression of direction and topological spatial relations and ensures a physical data independence and the processing can benefit from spatial access methods. The language is composed of two complementary sub-languages. The first one uses an object approximate and results in the selection of a set of candidate objects, which are investigated more in detail using the second one.

Using Temporal Constructs in Temporal Databases

Abstract: Temporal Databases have developed to the point where there is a proposed query language, TSQL2, [1] and a database implementation, Multical, [2] based on this language. It is now appropriate to review the power and relevance of this approach. It is accepted that TSQL2 is appropriate for a number of types of temporal query. This paper examines TSQL2 with respect to the requirements of an application area to see how well it can be applied to solving the problems with temporal querying in this area. The weaknesses of TSQL2 in this application area are identified and an alternative graphical query language, called GEST is presented to overcome these weaknesses. GEST has the same power as TSQL2, but improves on it, in three ways: it is based on a WIMP interface; it can cope with incomplete temporal information; and it can also support a variety of temporal constructs that are difficult to implement in TSQL2.