Modeling Fuzzy Information in the IFO and Relational Data Model

2011 ◽  
pp. 273-293
Author(s):  
Z. M. Ma
Keyword(s):  
Fuzzy Set ◽  
Relational Database ◽  
Real World ◽  
Data Model ◽  
Data Models ◽  
Computer Applications ◽  
Relational Data Model ◽  
Relational Database Schema ◽  
Conceptual Data ◽  
Design Databases

Computer applications in non-traditional areas have put requirements on conceptual data modeling. Some conceptual data models, being the tool of design databases, have been proposed. However, information in real-world applications is often vague or ambiguous. Currently, less research has been done in modeling imprecision and uncertainty in conceptual data models and the design of databases with imprecision and uncertainty. In this chapter, a different level of fuzziness based on fuzzy set and possibility distribution theory will be introduced into the IFO data model and the corresponding graphical representations will be given. The IFO data model is then extended to a fuzzy IFO data model, denoted IF2O. In particular, we provide the approach to mapping an IF2O model to a fuzzy relational database schema.

scholarly journals NETWORK MODELLING AND SEMANTIC 3D CITY MODELS: TESTING THE MATURITY OF THE UTILITY NETWORK ADE FOR CITYGML WITH A WATER NETWORK TEST CASE

2018 ◽  
Vol IV-4 ◽  
pp. 13-20 ◽  
Author(s):  
I. Boates ◽  
G. Agugiaro ◽  
A. Nichersu
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Database Schema ◽  
Future Research ◽  
Physical Parameters ◽  
Test Case ◽  
Network Modelling ◽  
Complex Development ◽  
Relational Database Schema ◽  
Utility Network

<p><strong>Abstract.</strong> Recent advances in semantic 3D city modelling and a demand from utility network operators for multi-utility data models integration have contributed to the emergence of an open Application Domain Extension (ADE) of the CityGML data model tailored to multiple types of utility networks. This extension, called the Utility Network ADE, is still in active development. However, work is already well underway to create data samples and to develop methods of modelling thereupon. In this paper, a mapping of the Utility Network ADE data model to a relational database schema is introduced. A sample of a freshwater network using the Utility Network ADE and based on data from the city of Nanaimo, Canada, is also presented. This sample has also been imported into a relational database schema built upon the 3DCityDB (a database implementation of CityGML) extended with a schema of the Utility Network ADE. Further to this, a series of basic network analysis functions have been defined and implemented in SQL to interact with the database so as to carry out sample atomic processes involved in network modelling, such as reading semantic properties of elements, calculating composite physical parameters of the network as a whole, and performing simple topological routing to serve as a guiding example for further and more complex development. A brief outlook is also presented, suggesting areas with high potential for future research and development of this nascent data model.</p>

scholarly journals N-Tier Soft Set Data Model: An Approach to Combine the Logicality of SQL and the Flexibility of NoSQL

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Jiang Wu ◽  
Du Ni ◽  
Zhi Xiao
Keyword(s):  
Set Theory ◽  
Data Model ◽  
Data Models ◽  
Soft Set ◽  
Relational Model ◽  
Relational Data ◽  
Huge Amount ◽  
Nosql Databases ◽  
Relational Data Model ◽  
Normative Perspective

To process a huge amount of data, computing resources need to be organized in clusters that can be scaled out easily. Still, traditional SQL databases built on the relational data model are difficult to be put to use in such clusters, which has motivated the movement named NoSQL. However, NoSQL databases have their limits by using their own data models. In this paper, the original soft set theory is extended, and a new theory system called n-tier soft set is brought up. We systematically constructed its concepts, definitions, and operations, establishing it as a novel soft set algebra. And some features of this algebra display its natural advantages as a data model which could combine the logicality of the SQL model (also known as the relational model) and the flexibility of NoSQL models. This data model provides a unified and normative perspective logic for organizing and manipulating data, combines metadata (semantic) and data to form a self-described structure, and combines index and data to realize fast locating and correlating.

New SQL Standard in Database Modeling

2005 ◽  
pp. 2116-2121 ◽  
Author(s):  
Eric Pardede ◽  
J. Wenny Rahayu ◽  
David Taniar
Keyword(s):  
Relational Database ◽  
Real World ◽  
Complex Structure ◽  
Object Oriented ◽  
Structured Data ◽  
Database Applications ◽  
Database Modeling ◽  
Relational Data Model ◽  
Structured Objects ◽  
Object Oriented Database

Relational Database (RDB) is arguably the most widely used repository for database applications. Since the 1970s, we have witnessed the relational data model, from which the RDB is originated, evolving. The progress aims to answer the increasing requirement in database applications. One of them is the requirement to deal with complex structure of real world problems. Unlike its Object-Oriented Database (OODB) counterpart, the RDB, for example, does not have facilities to store large structured objects, semi-structured data, and so forth.

Extending Relational Data Model to Resolve the Conflicts in Schema Integration of Multiple Databases in Virtual Enterprise

1999 ◽  
Author(s):  
Z. M. Ma ◽  
W. J. Zhang ◽  
Q. Li
Keyword(s):  
Relational Database ◽  
Information Integration ◽  
Data Model ◽  
Production Management ◽  
Virtual Enterprise ◽  
Relational Data ◽  
Schema Integration ◽  
Essential Requirement ◽  
Relational Data Model

Abstract Virtual enterprise is typically one kind of information-based enterprise. The features of information system in virtual enterprise can be generalized as heterogeneous and distributed. Its organization and production management put an essential requirement on information integration. In this paper, we shall discuss the forms of conflict in schema integration of multiple databases in virtual enterprise, and give an approach to resolve the conflicts. In order to implement this approach in relational database, an extended relational data model is proposed and the notion of marked partial value is introduced. Based on this extended data model, some relational operations for data management are defined. A case study is discussed about query processing on relational database with partial values.

Multivalued Dependencies in Fuzzy Multivalued Relational Databases Using Fuzzy Functions

2015 ◽  
Vol 23 (04) ◽  
pp. 589-626 ◽  
Author(s):  
Devendra K. Tayal ◽  
P. C. Saxena
Keyword(s):  
Real World ◽  
Data Model ◽  
Relational Databases ◽  
Relational Model ◽  
Relational Data ◽  
Inference Rules ◽  
Functional Dependencies ◽  
Technical Institute ◽  
Relational Schema ◽  
Relational Data Model

In this paper we discuss an important integrity constraint called multivalued dependency (mvd), which occurs as a result of the first normal form, in the framework of a newly proposed model called fuzzy multivalued relational data model. The fuzzy multivalued relational data model proposed in this paper accommodates a wider class of ambiguities by representing the domain of attributes as a “set of fuzzy subsets”. We show that our model is able to represent multiple types of impreciseness occurring in the real world. To compute the equality of two fuzzy sets/values (which occur as tuple-values), we use the concept of fuzzy functions. So the main objective of this paper is to extend the mvds in context of fuzzy multivalued relational model so that a wider class of impreciseness can be captured. Since the mvds may not exist in isolation, a complete axiomatization for a set of fuzzy functional dependencies (ffds) and mvds in fuzzy multivalued relational schema is provided and the role of fmvds in obtaining the lossless join decomposition is discussed. We also provide a set of sound Inference Rules for the fmvds and derive the conditions for these Inference Rules to be complete. We also derive the conditions for obtaining the lossless join decomposition of a fuzzy multivalued relational schema in the presence of the fmvds. Finally we extend the ABU's Algorithm to find the lossless join decomposition in context of fuzzy multivalued relational databases. We apply all of the concepts of fmvds developed by us to a real world application of “Technical Institute” and demonstrate that how the concepts fit well to capture the multiple types of impreciseness.

Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection

2019 ◽  
Vol 30 (1) ◽  
pp. 1-21
Author(s):  
Ljubica Kazi ◽  
Zoltan Kazi
Keyword(s):  
Data Model ◽  
System Development ◽  
Data Models ◽  
University Student ◽  
Specific Data ◽  
Entity Relationship Model ◽  
Relationship Model ◽  
Er Model ◽  
Entity Relationship ◽  
Conceptual Data

Conceptual data models can change during the information system development and teamwork phases, which require constantly monitoring with synonyms detection. This study elaborates on an approach for detecting synonyms in an entity-relationship model based on mapping with ontological elements. The use of a specific data model validator (DMV) tool enables formalization of the ontology and ER models, as well as their integration with the set of reasoning rules. The reasoning rules enable mapping between formalized elements of the ontology and ER model, and the extraction of synonyms. Formalized elements and reasoning rules are processed within Prolog for the extraction of synonyms. An empirical study conducted by using university student exams demonstrates usability of the proposed approach. The results show effectiveness in extraction of synonyms in all types of conceptual data model elements.

Fuzzy Information Modeling with the UML

2011 ◽  
pp. 153-176 ◽  
Author(s):  
Zongmin Ma
Keyword(s):  
Knowledge Engineering ◽  
Unified Modeling Language ◽  
Data Modeling ◽  
Data Models ◽  
Information Modeling ◽  
Fuzzy Information ◽  
Unified Modeling ◽  
Management Group ◽  
Conceptual Data ◽  
Design Databases

Computer applications in nontraditional areas have put requirements on conceptual data modeling. Some conceptual data models, being the tool of design databases, were proposed. However, information in real-world applications is often vague or ambiguous. Currently, less research has been done in modeling imprecision and uncertainty in conceptual data models. The UML (Unified Modeling Language) is a set of object-oriented modeling notations and is a standard of the Object Data Management Group (ODMG). It can be applied in many areas of software engineering and knowledge engineering. Increasingly, the UML is being applied to data modeling. In this chapter, different levels of fuzziness are introduced into the class of the UML and the corresponding graphical representations are given. The class diagrams of the UML can hereby model fuzzy information.

Engineering Conceptual Data Models from Domain Ontologies

2008 ◽  
pp. 1068-1080
Author(s):  
Haya El-Ghalayini ◽  
Mohammed Odeh ◽  
Richard McClatchey
Keyword(s):  
Data Model ◽  
Domain Knowledge ◽  
System Development ◽  
Data Models ◽  
Mapping Algorithm ◽  
Domain Ontologies ◽  
Conceptual Data ◽  
High Degree ◽  
Quantitative And Qualitative Methods

This article studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of developing information systems. A mapping algorithm has been proposed and embedded in a special purpose transformation engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this article focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies. The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities, along with their relationships being derived from the consensual semantics of domain knowledge. The results are encouraging and support the potential role that this approach can take part in the process of information system development.

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