Towards a complete conceptual model: Petri nets and entity-relationship diagrams

1993 ◽  
Vol 18 (5) ◽  
pp. 275-298 ◽  
Author(s):  
Carlos A Heuser ◽  
Eduardo Meira Peres ◽  
Gernot Richter
Keyword(s):  
Petri Nets ◽  
Conceptual Model ◽  
Entity Relationship ◽  
Entity Relationship Diagrams

From Conceptual Models to Data Models

2011 ◽  
pp. 148-170 ◽  
Author(s):  
Antonio Badia
Keyword(s):  
Conceptual Model ◽  
Conceptual Models ◽  
Object Oriented ◽  
Data Models ◽  
Xml Database ◽  
Relational Schemas ◽  
Trade Offs ◽  
Object Relational ◽  
Entity Relationship ◽  
Entity Relationship Diagrams

This chapter describes transformations between conceptual models (mainly entity-relationship diagrams and also UML) and data models. It describes algorithms to transform a given conceptual model into a data model for a relational, object-relational, object-oriented and XML database. Some examples are used to illustrate the transformations. While some transformations are well known, some (like the transformation into XML or into object-relational schemas) have not been investigated in depth. The chapter shows that most of these transformations offer options which involve important trade-offs that database designers should be aware of.

The Problem of Equivalence for Entity-Relationship Diagrams

1983 ◽  
Vol SE-9 (5) ◽  
pp. 617-630 ◽  
Author(s):  
S. Jajodia ◽  
P.A. Ng ◽  
F.N. Springsteel
Keyword(s):  
Entity Relationship ◽  
Entity Relationship Diagrams

A METRIC-BASED APPROACH FOR PREDICTING CONCEPTUAL DATA MODELS MAINTAINABILITY

2001 ◽  
Vol 11 (06) ◽  
pp. 703-729 ◽  
Author(s):  
MARIO PIATTINI ◽  
MARCELA GENERO ◽  
LUIS JIMÉNEZ
Keyword(s):  
Structural Complexity ◽  
Data Models ◽  
Major Step ◽  
Development Life Cycle ◽  
Novel Method ◽  
Is Development ◽  
Entity Relationship ◽  
Conceptual Data ◽  
Entity Relationship Diagrams

It is generally accepted in the information system (IS) field that IS quality is highly dependent on the decisions made early in the development life cycle. The construction of conceptual data models is often an important task of this early development. Therefore, improving the quality of conceptual data models will be a major step towards the quality improvement of the IS development. Several quality frameworks for conceptual data models have been proposed, but most of them lack valid quantitative measures in order to evaluate the quality of conceptual data models in an objective way. In this article we will define measures for the structural complexity (internal attribute) of entity relationship diagrams (ERD) and use them for predicting their maintainability (external attribute). We will theoretically validate the proposed metrics following Briand et al.'s framework with the goal of demonstrating the properties that characterise each metric. We will also show how it is possible to predict each of the maintainability sub-characteristics using a prediction model generated using a novel method for induction of fuzzy rules.

NoSQL Data Modeling

2018 ◽  
pp. 94-123
Keyword(s):  
Conceptual Model ◽  
Data Modeling ◽  
Basic Structure ◽  
Object Modeling ◽  
Similar Model ◽  
Nosql Databases ◽  
Nosql Database ◽  
Er Model ◽  
Entity Relationship ◽  
Huge Challenge

The chapter discusses the necessity for data modeling in NoSQL world. The NoSQL data modeling is a huge challenge because one of the main features of NoSQL databases is that they are schema-free, that is they allow data manipulation without the need for the previous modeling or developing an entity-relationship (ER) or similar model. Although the absence of a schema can be an advantage in some situations, with the increase in the number of NoSQL database implementations, it appears that the absence of a conceptual model can be a source of substantial problems. In order to better understand the need for data modeling in NoSQL databases, first the basic structure of an ER model and an analysis of its limitations are summarized, especially regarding an application in NoSQL databases. The concept and Object modeling notation is presented as one of the possible solutions for data modeling in NoSQL databases.

Information Technology Transfer in Econometric Forecasting: A Pictorial Approach

1993 ◽  
Vol 8 (1) ◽  
pp. 3-13
Author(s):  
P. Pete Chong ◽  
Ye-Sho Chen ◽  
James M. Pruett
Keyword(s):  
Information Technology ◽  
Technology Transfer ◽  
Information Exchange ◽  
Management Tool ◽  
Task Management ◽  
System Maintenance ◽  
Concise Information ◽  
Entity Relationship ◽  
Entity Relationship Diagrams

Successful information technology transfer requires effective communication and clear, concise information exchange. This paper, using the Louisiana econometric model as a case study, proposes a pictorial approach to present and manage complex factors essential to information technology transfer. The approach utilizes multi-layer entity-relationship diagrams to provide a meaningful framework for the entire forecasting process, provide clarity to ensure better model maintenance when changes in social/economic structures require reformulations, and provide a procedural and data dictionary for clear documentation. The pictorial approach is both intuitive and readable, capable of serving as a task management tool, a model implementation aid, and a system maintenance resource.

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