Conceptual Data Modeling: Entity-Relationship Modeling

2014 ◽  
pp. 84-107
Keyword(s):  
Data Modeling ◽  
Entity Relationship ◽  
Conceptual Data ◽  
Entity Relationship Modeling

scholarly journals Mapping Common Errors in Entity Relationship Diagram Design of Novice Designers

2021 ◽  
Vol 13 (1) ◽  
pp. 1-19
Author(s):  
Rami Rashkovits ◽  
Ilana Lavy
Keyword(s):  
Data Model ◽  
System Development ◽  
Data Modeling ◽  
Database Schema ◽  
Solo Taxonomy ◽  
Key Factor ◽  
Novice Designers ◽  
Entity Relationship ◽  
Entity Relationship Diagram ◽  
Conceptual Data

Data modeling in the context of database design is a challenging task for any database designer, even more so for novice designers. A proper database schema is a key factor for the success of any information systems, hence conceptual data modeling that yields the database schema is an essential process of the system development. However, novice designers encounter difficulties in understanding and implementing such models. This study aims to identify the difficulties in understanding and implementing data models and explore the origins of these difficulties. This research examines the data model produced by students and maps the errors done by the students. The errors were classified using the SOLO taxonomy. The study also sheds light on the underlying reasons for the errors done during the design of the data model based on interviews conducted with a representative group of the study participants. We also suggest ways to improve novice designer's performances more effectively, so they can draw more accurate models and make use of advanced design constituents such as entity hierarchies, ternary relationships, aggregated entities, and alike. The research findings might enrich the data body research on data model design from the students' perspectives.

METHOD FOR SYNTHESIS OF CONCEPTUAL DATA MODELS BASED ON PROCESS DOMAIN MODELS

2020 ◽  
pp. 80-87
Author(s):  
С.И. Рябухин
Keyword(s):  
Data Modeling ◽  
Database Design ◽  
Data Models ◽  
Process Models ◽  
Domain Models ◽  
Conceptual Data

Процессные модели предметной области широко применяются при проектировании баз данных, а именно в ходе концептуального моделирования данных. Предлагается решение проблемы неоднозначности преобразования процессных доменных моделей типа SADT в концептуальные модели данных. Domain process models are widely used in database design, namely in conceptual data modeling. The solution of the problem of ambiguity of transformation of process domain models of the SADT type into conceptual data models is proposed.

Conceptual data modeling of expert systems

IEEE Expert ◽  
1989 ◽  
Vol 4 (1) ◽  
pp. 50-61 ◽  
Author(s):  
J.P. Held ◽  
J.V. Carlis
Keyword(s):  
Expert Systems ◽  
Data Modeling ◽  
Conceptual Data

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.

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