Methodical Spatial Database Design with Topological Polygon Structures

2012 ◽  
Vol 3 (1) ◽  
pp. 21-30
Author(s):  
Jean Damascène Mazimpaka
Keyword(s):  
Design Process ◽  
Spatial Data ◽  
Spatial Databases ◽  
Early Stage ◽  
Spatial Database ◽  
Database Design ◽  
Integrity Constraints ◽  
Data Types ◽  
Data Infrastructure ◽  
Database Development

Spatial databases form the foundation for a Spatial Data Infrastructure (SDI). For this, a spatial database should be methodically developed to accommodate its role in SDI. It is desirable to have an approach to spatial database development that considers maintenance from the early stage of database design and in a flexible way. Moreover, there is a lack of a mechanism to capture topological relations of spatial objects during the design process. This paper presents an approach that integrates maintenance of topological integrity constraints into the whole spatial database development cycle. The approach is based on the concept of Abstract Data Types. A number of topological classes have been identified and modelling primitives developed for them. Topological integrity constraints are embedded into maintenance functions associated with the topological classes. A semi-automatic transformation process has been developed following the principles of Model Driven Architecture to simplify the design process.

Methodical Spatial Database Design with Topological Polygon Structures

2013 ◽  
pp. 295-304 ◽  
Author(s):  
Jean Damascène Mazimpaka
Keyword(s):  
Design Process ◽  
Spatial Data ◽  
Spatial Databases ◽  
Early Stage ◽  
Spatial Database ◽  
Database Design ◽  
Integrity Constraints ◽  
Data Infrastructure ◽  
Database Development ◽  
Model Driven

Spatial databases form the foundation for a Spatial Data Infrastructure (SDI). For this, a spatial database should be methodically developed to accommodate its role in SDI. It is desirable to have an approach to spatial database development that considers maintenance from the early stage of database design and in a flexible way. Moreover, there is a lack of a mechanism to capture topological relations of spatial objects during the design process. This paper presents an approach that integrates maintenance of topological integrity constraints into the whole spatial database development cycle. The approach is based on the concept of Abstract Data Types. A number of topological classes have been identified and modelling primitives developed for them. Topological integrity constraints are embedded into maintenance functions associated with the topological classes. A semi-automatic transformation process has been developed following the principles of Model Driven Architecture to simplify the design process.

Spatial Databases

2017 ◽  
pp. 111-149
Author(s):  
Grace L. Samson ◽  
Joan Lu ◽  
Mistura M. Usman ◽  
Qiang Xu
Keyword(s):  
Data Storage ◽  
Spatial Data ◽  
Spatial Databases ◽  
Query Language ◽  
Dimensional Space ◽  
Spatial Database ◽  
Multidimensional Data ◽  
Data Types ◽  
3 Dimensional ◽  
Storage And Retrieval

Spatial databases maintain space information which is appropriate for applications where there is need to monitor the position of an object or event over space. Spatial databases describe the fundamental representation of the object of a dataset that comes from spatial or geographic entities. A spatial database supports aspects of space and offers spatial data types in its data model and query language. The spatial or geographic referencing attributes of the objects in a spatial database permits them to be positioned within a two (2) dimensional or three (3) dimensional space. This chapter looks into the fundamentals of spatial databases and describes their basic component, operations and architecture. The study focuses on the data models, query Language, query processing, indexes and query optimization of a spatial databases that approves spatial databases as a necessary tool for data storage and retrieval for multidimensional data of high dimensional spaces.

Query Processing in Spatial Databases

2009 ◽  
pp. 269-278
Author(s):  
Antonio Corral ◽  
Michael Vassilakopoulos
Keyword(s):  
Information Systems ◽  
Query Processing ◽  
Spatial Data ◽  
Spatial Databases ◽  
Spatial Database ◽  
Database System ◽  
Data Types ◽  
Spatial Data Models ◽  
Large Scale Integration ◽  
Efficient Query Processing

Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system several important issues must be taken into account such as: spatial data models, indexing mechanisms and efficient query processing. A spatial database system (SDBS) is a database system that offers spatial data types in its data model and query language and supports spatial data types in its implementation, providing at least spatial indexing and efficient spatial query processing (Güting, 1994). The main reason that has caused the active study of spatial database management systems (SDBMS) comes from the needs of the existing applications such as geographical information systems (GIS), computer-aided design (CAD), very large scale integration design (VLSI), multimedia information systems (MIS), data warehousing, multi-criteria decision making, location-based services, etc.

scholarly journals From Surveying to Geomatics

2016 ◽  
Vol 10 (3-4) ◽  
pp. 153-160 ◽  
Author(s):  
Besim Ajvazi ◽  
Fisnik Loshi ◽  
Béla Márkus
Keyword(s):  
Information And Communication Technologies ◽  
Spatial Data ◽  
Professional Education ◽  
Spatial Databases ◽  
Unmanned Aerial Systems ◽  
Geospatial Information ◽  
Automatic Data ◽  
Data Infrastructure ◽  
Building Information ◽  
Concept Building

In the land surveying profession fast changes have been taking place in the last fifty years. Technological changes are generated by the Information and Communication Technologies; the analogue – digital trends; the automatic data acquisition methods replace manual ones; instead of two-dimensional base maps we use dynamic spatial databases more and more integrated into a global data infrastructure. However, these changes cause impacts also on scientific level. The traditional top-down approach substituted by bottom-up methodologies; in many cases the point-by-point measurement is changed by 3D laserscanning or Unmanned Aerial Systems, which produces huge amount of data, but it needs new algorithms for information extraction; instead of a simple data provision land surveyors support complex spatial decisions. The paper is dealing with some aspects of these changes. In the first chapter the authors would like to highlight the “data-information-knowledge” relations and the importance of changes in professional education. The second chapter gives an example of the benefits of a Global Spatial Data Infrastructure in spatial decision support. Finally we introduce a new concept (Building Information Modelling) in modelling the real world. However, until now BIM is used in building construction industry, it can can be a paradigm shift in geospatial information management in general.

Spatial and Spatiotemporal Data Types as a Foundation for Representing Space-Time Data in GIS

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Markus Schneider
Keyword(s):  
Spatial Data ◽  
Geographical Information Systems ◽  
Moving Objects ◽  
Spatial Databases ◽  
Query Languages ◽  
Geographical Information ◽  
Spatiotemporal Data ◽  
Data Types ◽  
Time Data ◽  
Use Of Data

A data type comprises a set of homogeneous values together with a collection of operations defined on them. This chapter emphasizes the importance of crisp spatial data types, fuzzy spatial data types, and spatiotemporal data types for representing static, vague, and time-varying geometries in Geographical Information Systems (GIS). These data types provide a fundamental abstraction for modeling the geometric structure of crisp spatial, fuzzy spatial, and moving objects in space and time as well as their relationships, properties, and operations. The goal of this chapter is to provide an overview and description of these data types and their operations that have been proposed in research and can be found in GIS, spatial databases, moving objects databases, and other spatial software tools. The use of data types, operations, and predicates will be illustrated by their embedding into query languages.

A Taxonomy for Distance-Based Spatial Join Queries

2017 ◽  
Vol 13 (3) ◽  
pp. 1-24 ◽  
Author(s):  
Lingxiao Li ◽  
David Taniar
Keyword(s):  
Fixed Points ◽  
Spatial Data ◽  
Database Management ◽  
Spatial Databases ◽  
Family Type ◽  
Management Systems ◽  
Data Types ◽  
Full Spectrum ◽  
Spatial Join ◽  
Join Queries

Join operation is one of the most used operations in database management systems, including spatial databases. Hence, spatial join queries are very important in spatial database processing. There are many different kinds of spatial join queries, due to the richness in spatial data types and spatial operations. Therefore, it is important to understand the full spectrum of spatial join queries. The aim of this paper is to give a classification to one family type of spatial join, called the Distance-based Spatial Join. In the taxonomy, the authors divide this spatial join into three categories: (i) AllRange, (ii) All-kNN, and (iii) All-RNN. Each of these categories has its own variants. In this taxonomy, the authors confine the discussions to join queries on fixed points.

scholarly journals User-Centred Design of Multidisciplinary Spatial Data Platforms for Human-History Research

2021 ◽  
Vol 10 (7) ◽  
pp. 467
Author(s):  
Meeli Roose ◽  
Tua Nylén ◽  
Harri Tolvanen ◽  
Outi Vesakoski
Keyword(s):  
Design Process ◽  
Spatial Data ◽  
User Centered Design ◽  
Human Beings ◽  
Human History ◽  
Data Types ◽  
Building Process ◽  
Development Goals ◽  
User Friendly ◽  
User Centered

The role of open spatial data is growing in human-history research. Spatiality can be utilized to bring together and seamlessly examine data describing multiple aspects of human beings and their environment. Web-based spatial data platforms can create equal opportunities to view and access these data. In this paper, we aim at advancing the development of user-friendly spatial data platforms for multidisciplinary research. We conceptualize the building process of such a platform by systematically reviewing a diverse sample of historical spatial data platforms and by piloting a user-centered design process of a multidisciplinary spatial data platform. We outline (1) the expertise needed in organizing multidisciplinary spatial data sharing, (2) data types that platforms should be able to handle, (3) the most useful platform functionalities, and (4) the design process itself. We recommend that the initiative and subject expertise should come from the end-users, i.e., scholars of human history, and all key end-user types should be involved in the design process. We also highlight the importance of geographic expertise in the process, an important link between subject, spatial and technical viewpoints, for reaching a common understanding and common terminology. Based on the analyses, we identify key development goals for spatial data platforms, including full layer management functionalities. Moreover, we identify the main roles in the user-centered design process, main user types and suggest good practices including a multimodal design workshop.

Integrity Constraints in Spatial Databases

2002 ◽  
pp. 144-171 ◽  
Author(s):  
Karla A.V. Borges ◽  
Clodoveu A. Davis Jr. ◽  
Alberto H.F. Laender
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Spatial Databases ◽  
Spatial Information ◽  
Spatial Relationship ◽  
Object Oriented ◽  
Database Management System ◽  
Geometric Constraints ◽  
Integrity Constraints ◽  
Spatial Relationships

This chapter addresses the relationship that exists between the nature of spatial information, spatial relationships, and spatial integrity constraints, and proposes the use of OMT-G (Borges et al., 1999; Borges et al., 2001), an object-oriented data model for geographic applications, at an early stage in the specification of integrity constraints in spatial databases. OMT-G provides appropriate primitives for representing spatial data, supports spatial relationships and allows the specification of spatial integrity rules (topological, semantic and user integrity rules) through its spatial primitives and spatial relationship constructs. Being an object-oriented data model, it also allows some spatial constraints to be encapsulated as methods associated to specific georeferenced classes. Once constraints are explicitly documented in the conceptual modeling phase, and methods to enforce the spatial integrity constraints are defined, the spatial database management system and the application must implement such constraints. This chapter does not cover integrity constraints associated to the representation of simple objects, such as constraints implicit to the geometric description of a polygon. Geometric constraints are related to the implementation, and are covered here in a higher level view, considering only the shape of geographic objects. Consistency rules associated with the representation of spatial objects are discussed in Laurini and Thompson (1992).

Query Processing in Spatial Databases

2005 ◽  
pp. 511-516
Author(s):  
Antonio Corral ◽  
Michael Vassilakopoulos
Keyword(s):  
Query Processing ◽  
Spatial Data ◽  
Spatial Databases ◽  
Query Language ◽  
Database System ◽  
Data Types ◽  
Spatial Query Processing ◽  
Spatial Data Management ◽  
Spatial Data Models ◽  
Efficient Query Processing

Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system, several important issues must be taken into account such as spatial data models, indexing mechanisms, and efficient query processing. A spatial database system (SDBS) is a database system that offers spatial data types in its data model and query language and supports spatial data types in its implementation, providing at least spatial indexing and efficient spatial query processing (Güting, 1994).

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