AN AUTOMATIC METHOD FOR THE DESIGN OF MULTIDIMENSIONAL SCHEMAS FROM OBJECT ORIENTED DATABASES

2013 ◽  
Vol 12 (06) ◽  
pp. 1223-1259 ◽  
Author(s):  
YASSER HACHAICHI ◽  
JAMEL FEKI
Keyword(s):  
Data Model ◽  
Design Method ◽  
Object Oriented ◽  
Large Data ◽  
Automatic Generation ◽  
Specific Model ◽  
Data Repository ◽  
Schema Design ◽  
Object Database ◽  
Entity Relationship

A data warehouse (DW) is a large data repository system designed for decision-making purposes. Its design relies on a specific model called multidimensional. This multidimensional model supports analyses of huge volumes of data that trace the enterprise's activities over time. Several design methods were proposed to build multidimensional schemas from either the relational data model or the entity-relationship data model. Almost all proposals that treated the object-oriented data model assume the presence of the data source UML class-diagram. However, in practice, either such a diagram does not exist or is obsolete due to multiple changes/evolutions of the information system. Furthermore, these few proposals require an intense manual intervention of the designer, which requires a high expertise both in the DW domain and in the object database domain. To overcome these disadvantages, this work proposes an automatic DW schema design method starting from an object database (schema and its instances). This method applies a set of extraction rules to identify multidimensional concepts and to generate star schemas. It is defined for the standard ODMG model and, thus, can be adapted with slight changes for other object database models. In addition, its extraction rules have the merit of being independent of the domain semantics. Furthermore, they automatically generate schemas classified according to their analytical potential; this classification helps the DW designer in selecting the most relevant schemas among the generated ones. Finally, being automatic, our method is supported by a toolset that also prepares for the automatic generation of the Extract Transform and Load procedures used to load the DW.

Enforcing Cardinality Constraints in the ER Model with Integrity Methods

2002 ◽  
pp. 1-16 ◽  
Author(s):  
Mira Balaban ◽  
Peretz Shoval
Keyword(s):  
Data Model ◽  
Object Oriented ◽  
Database Schema ◽  
Direct Impact ◽  
Cardinality Constraints ◽  
Relationship Type ◽  
Er Model ◽  
Entity Relationship

Entity-Relationship (ER) schemas include cardinality constraints that restrict the dependencies among entities within a relationship type. The cardinality constraints have direct impact on application transactions, since insertions or deletions of entities or relationships might affect related entities. Application transactions can be strengthened to preserve the consistency of a database with respect to the cardinality constraints in a schema. Yet, once an ER schema is translated into a logical database schema, the direct correlation between the cardinality constraints and application transaction is lost, since the components of the ER schema might be decomposed among those of the logical database schema. We suggest extending the Enhanced-ER (EER) data model with integrity methods that can enforce the cardinality constraints. The integrity methods can be fully defined by the cardinality constraints, using a small number of primitive update methods, and are automatically created for a given EER diagram. A translation of an EER schema into a logical database schema can create integrity routines by translating the primitive update methods alone. These integrity routines may be implemented as database procedures, if a relational DBMS is utilized, or as class methods, if an object-oriented DBMS is utilized.

An Object-Oriented Approach to Conceptual Hypermedia Modeling

2011 ◽  
pp. 41-54
Author(s):  
Wilfried Lemahieu
Keyword(s):  
Data Model ◽  
Object Oriented ◽  
Implementation Framework ◽  
Object Oriented Approach ◽  
Entity Relationship ◽  
Oriented Approach

This chapter introduces the MESH approach to hypermedia modeling and navigation, which aims at relieving the typical drawbacks of poor maintainability and user disorientation. The main focus is upon the data model, which combines established entity-relationship and object-oriented abstractions with proprietary concepts into a formal hypermedia data model. Uniform layout and link typing specifications can be attributed and inherited in a static node typing hierarchy, whereas both nodes and links can be submitted dynamically to multiple complementary classifications. In addition, the data model’s support for a context-based navigation paradigm, as well as a platform-independent implementation framework, are briefly discussed.

scholarly journals Product Lifecycle Management with the Asset Administration Shell

Computers ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 84
Author(s):  
Andreas Deuter ◽  
Sebastian Imort
Keyword(s):  
Data Model ◽  
Research Work ◽  
Idea Generation ◽  
Automatic Generation ◽  
Product Lifecycle Management ◽  
Product Lifecycle ◽  
Digital Representation ◽  
Holistic Concept ◽  
Standard Interface ◽  
Lifecycle Management

Product lifecycle management (PLM) as a holistic process encompasses the idea generation for a product, its conception, and its production, as well as its operating phase. Numerous tools and data models are used throughout this process. In recent years, industry and academia have developed integration concepts to realize efficient PLM across all domains and phases. However, the solutions available in practice need specific interfaces and tend to be vendor dependent. The Asset Administration Shell (AAS) aims to be a standardized digital representation of an asset (e.g., a product). In accordance with its objective, it has the potential to integrate all data generated during the PLM process into one data model and to provide a universally valid interface for all PLM phases. However, to date, there is no holistic concept that demonstrates this potential. The goal of this research work is to develop and validate such an AAS-based concept. This article demonstrates the application of the AAS in an order-controlled production process, including the semi-automatic generation of PLM-related AAS data. Furthermore, it discusses the potential of the AAS as a standard interface providing a smooth data integration throughout the PLM process.

ODM: An object oriented data model

1989 ◽  
Vol 7 (1) ◽  
pp. 3-35
Author(s):  
Mojtaba Mozaffari ◽  
Yuzuru Tanaka
Keyword(s):  
Data Model ◽  
Object Oriented

Study of the Spatio-Temporal Data Model in Sea Battlefield

2012 ◽  
Vol 246-247 ◽  
pp. 744-748
Author(s):  
Yue Lin Sun ◽  
Lei Bao ◽  
Yi Hang Peng
Keyword(s):  
Data Model ◽  
Object Oriented ◽  
Space Time ◽  
Comprehensive Analysis ◽  
Temporal Data ◽  
Data Types ◽  
Spatio Temporal ◽  
The Right ◽  
Effective Analysis

An effective analysis of the battlefield situation and spatio-temporal data model in a sea battlefield has great significance for the commander to perceive the battlefield situation and to make the right decisions. Based on the existing spatio-temporal data model, the present paper gives a comprehensive analysis of the characteristics of sea battlefield data, and chooses the object-oriented spatio-temporal data model to modify it; at the same time this paper introduces sea battlefield space-time algebra system to define various data types formally, which lays the foundation for the establishment of the sea battlefield spatio-temporal data model.

Integrated 3D Spatial Data Model of Object-Oriented Digital Landslide

2012 ◽  
Vol 204-208 ◽  
pp. 4872-4877
Author(s):  
Da Xi Ma ◽  
Xiao Hong Liu ◽  
Li Wei Ma
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data Modeling ◽  
Object Oriented ◽  
Landslide Modeling ◽  
Space Data ◽  
Spatial Data Model ◽  
Three Dimensional Space

By analyzing the attributes of three-dimensional space data model, the integrated 3D spatial data adopts object-oriented method for digital landslide modeling. It achieves spatial data modeling for landslide geological entity. An experimental case is given to indicate the feasibility of this approach for spatial data modeling.

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