Interval Sequences: An Object-Relational Approach to Manage Spatial Data

2001 ◽  
pp. 481-501 ◽  
Author(s):  
Hans-Peter Kriegel ◽  
Marco Pötke ◽  
Thomas Seidl
Keyword(s):  
Spatial Data ◽  
Relational Approach ◽  
Object Relational

Object-Relational Spatial Indexing

2011 ◽  
pp. 49-80
Author(s):  
Hans-Peter Kriegel ◽  
Martin Pfeifle ◽  
Marco Potke ◽  
Thomas Seidl ◽  
Jost Enderle
Keyword(s):  
Spatial Data ◽  
Concurrency Control ◽  
Buffer Management ◽  
Database Systems ◽  
Data Types ◽  
Spatial Access ◽  
Access Methods ◽  
Object Relational ◽  
Relational Database Systems ◽  
Spatial Access Methods

In order to generate efficient execution plans for queries comprising spatial data types and predicates, the database system has to be equipped with appropriate index structures, query processing methods and optimization rules. Although available extensible indexing frameworks provide a gateway for seamless integration of spatial access methods into the standard process of query optimization and execution, they do not facilitate the actual implementation of the spatial access method. An internal enhancement of the database kernel is usually not an option for database developers. The embedding of a custom, block-oriented index structure into concurrency control, recovery services and buffer management would cause extensive implementation efforts and maintenance cost, at the risk of weakening the reliability of the entire system. The server stability can be preserved by delegating index operations to an external process, but this approach induces severe performance bottlenecks due to context switches and inter-process communication. Therefore, we present the paradigm of object-relational spatial access methods that perfectly fits to the common relational data model, and is highly compatible with the extensible indexing frameworks of existing object-relational database systems, allowing the user to define application-specific access methods.

Enhancing Decision Support Systems with Spatial Capabilities

2011 ◽  
pp. 2542-2557
Author(s):  
Marcus Costa Sampaio ◽  
Cláudio de Souza Baptista ◽  
André Gomes de Sousa ◽  
Fabiana Ferreira do Nascimento
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Data Warehouse ◽  
Spatial Data ◽  
Support Systems ◽  
Data Cube ◽  
Related Data ◽  
Spatial Dimensions ◽  
Object Relational ◽  
Long Time

This chapter introduces spatial dimensions and measures as a means of enhancing decision support systems with spatial capabilities. By some way or other, spatial related data has been used for a long time; however, spatial dimensions have not been fully exploited. It is presented a data model that tightly integrates data warehouse and geographical information systems — so characterizing a spatial data warehouse (SDW) — ; more precisely, the focus is on a formalization of SDW concepts, on a spatial-aware data cube using object-relational technology, and on issues underlying a SDW — specially regarding spatial data aggregation operations. Finally, the MapWarehouse prototype is presented aiming to validate the ideas proposed. The authors believe that SDW allows for the efficient processing of queries that use, jointly, spatial and numerical temporal data (e.g., temporal series from summarized spatial and numerical measures).

A Multidimensional Methodology with Support for Spatio-Temporal Multigranularity in the Conceptual and Logical Phases

2011 ◽  
pp. 194-230 ◽  
Author(s):  
Concepción M. Gascueña ◽  
Rafael Guadalupe
Keyword(s):  
Spatial Data ◽  
Hierarchical Structures ◽  
The Other ◽  
Fe Model ◽  
Multidimensional Databases ◽  
Object Relational ◽  
Spatio Temporal ◽  
The One ◽  
Spatial Semantics ◽  
Thematic Data

The Multidimensional Databases (MDB) are used in the Decision Support Systems (DSS) and in Geographic Information Systems (GIS); the latter locates spatial data on the Earth’s surface and studies its evolution through time. This work presents part of a methodology to design MDB, where it considers the Conceptual and Logical phases, and with related support for multiple spatio-temporal granularities. This will allow us to have multiple representations of the same spatial data, interacting with other, spatial and thematic data. In the Conceptual phase, the conceptual multidimensional model—FactEntity (FE)—is used. In the Logical phase, the rules of transformations are defined, from the FE model, to the Relational and Object Relational logical models, maintaining multidimensional semantics, and under the perspective of multiple spatial, temporal, and thematic granularities. The FE model shows constructors and hierarchical structures to deal with the multidimensional semantics on the one hand, carrying out a study on how to structure “a fact and its associated dimensions.” Thus making up the Basic factEnty, and in addition, showing rules to generate all the possible Virtual factEntities. On the other hand, with the spatial semantics, highlighting the Semantic and Geometric spatial granularities.

scholarly journals Querying Uncertain Data in Geospatial Object-relational Databases Using SQL and Fuzzy Sets

2013 ◽  
Vol 21 (4) ◽  
pp. 1-12 ◽  
Author(s):  
R. Ďuračiová
Keyword(s):  
Fuzzy Sets ◽  
Spatial Data ◽  
Relational Databases ◽  
Spatial Databases ◽  
Query Language ◽  
Uncertain Data ◽  
Uncertainty Modeling ◽  
Geographic Information ◽  
Object Relational ◽  
Efficient Processing

Abstract This paper deals with uncertainty modeling in spatial object-relational databases by the use of Structured Query Language (SQL). The fundamental principles of uncertainty modeling by fuzzy sets are applied in the area of geographic information systems (GIS) and spatial databases. A spatial database system includes types of spatial data and implements the spatial extension of SQL. The implementation of the principles of fuzzy logic to spatial databases brings an opportunity for the efficient processing of uncertain data, which is important, especially when using various data sources (e.g., multi-criteria decision making (MCDM) on the basis of heterogeneous spatial data resources). The modeling and data processing of uncertainties are presented in relation to the applicable International Organization for Standardization (ISO) standards (standards of the series 19100 Geographic information) and the relevant specifications of the Open Geospatial Consortium (OGC). The fuzzy spatial query approach is applied and tested on a case study with a fundamental database for GIS in Slovakia.

scholarly journals LADM AND INTERLIS AS A PERFECT MATCH FOR 3D CADASTRE

2017 ◽  
Vol XLII-4/W7 ◽  
pp. 23-26 ◽  
Author(s):  
E. Kalogianni ◽  
E. Dimopoulou ◽  
W. Quak ◽  
P. Van Oosterom
Keyword(s):  
Spatial Data ◽  
Complete Solution ◽  
Perfect Match ◽  
Legal Aspects ◽  
International Standards ◽  
National Standards ◽  
Urban Structures ◽  
Land Administration ◽  
3D Cadastre ◽  
Object Relational

Standardization in land administration domain has been expanded to 3D and even 4D representations, adopting a multipurpose character, in order to become the foundation of a sustainable and smart economic development. At the moment, although the potential benefits of 3D Cadastre is argued to be enormous and there are plenty of standards related to 3D Cadastre while others enhancing the role of 3D Cities, there is no complete solution for 3D Cadastre. That being so, the last years, there has been a rapid increase in the integration, harmonization and implementation support of such standards. In this context, the integration of 3D legal spaces with 3D physical objects is gaining ground, as the (invisible) legal boundaries do not always match with the physical counterparts, leading to obscure situations. LADM, the International Standard for land administration, was proved to be one of the best candidates to unambiguously represent 3D Rights, Restrictions and Responsibilities. On the other side, spatial data models and virtual city models manage 3D urban structures without focusing on legal aspects. Many researchers have explored integrations between those aspects giving promising results. In this direction, apart from international standards, also national standards have been developed to enable the communication between land information systems. One of the most representatives is INTERLIS, a Swiss standard, a precise, standardized Object Relational modelling language on the conceptual level, which allows for automated quality control. Thus, in this paper the focus is given on how INTERLIS and LADM complement each other in the actual implementation of land administration systems. Main challenges among others in the context of this research include: 1. extensible hierarchical and versioned code lists in INTERLIS models, 2. formally define LADM constraints in INTERLIS, 3. discuss 3D geometry types and 4. introduce a holistic LADM/INTERLIS approach for country profiles.

On the Support of Mobility in ORDBMS

2014 ◽  
Vol 4 (1) ◽  
pp. 38-64
Author(s):  
Nikos Pelekis ◽  
Elias Frentzos ◽  
Nikos Giatrakos ◽  
Yannis Theodoridis
Keyword(s):  
Spatial Data ◽  
Data Types ◽  
Temporal Semantics ◽  
Movement Data ◽  
Data Framework ◽  
Object Relational ◽  
Data Definition ◽  
Object Databases ◽  
Spatio Temporal ◽  
Manipulation Language

Composition of space and mobility in a unified data framework results into Moving Object Databases (MOD). MOD management systems support storage and query processing of non-static spatial objects and provide essential operations for higher level analysis of movement data. The goal of this paper is to present Hermes MOD engine that supports the aforementioned functionality through appropriate data types and methods in Object-Relational DBMS (ORDBMS) environments. In particular, Hermes exploits on the extensibility interface of ORDBMS that already have extensions for static spatial data types and methods that follow the Open Geospatial Consortium (OGC) standard, and extends the ORDBMS by supporting time-varying geometries that change their position and/or extent in space and time dimensions, either discretely or continuously. It further extends the data definition and manipulation language of the ORDBMS with spatio-temporal semantics and functionality.

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