A Formal ORM-to -UML Mapping Algorithm

The object-role model (ORM) data structure can be represented in the unified modeling language (UML) using the five fact encoding constructs: class attribute, association, association class, sub-class and the association qualifier. In the existing literature there exist numerous mappings of how individual fact types from an ORM information model can be mapped onto ‘well-formed’ UML expressions. What is lacking in the existing literature is a precise description of the conditions on the ‘source’ object-role model under which a specific UML fact encoding construct can be applied in the ‘target’ UML class diagram. In this paper we will show under what conditions, a specific UML fact encoding construct must be applied in a way that results in a well-formed UML class diagram.computer science applications;

UML Class Diagram or Entity Relationship Diagram : An Object Relational Impedance Mismatch

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model –towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to ithave been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram forconceptual modeling for relational databases, and several popular course text books use UMLnotation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on theother hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice databasedesigner due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER,UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts Keywords: EERD, UML Class Diagram, Relational Database Design, Structural Constraints, relational and object database impedance mismatch. The ER model was originally put forward by Chen [1] and subsequently extensions have been added to add further semantics to the original model; mainly the concepts of specialisation, generalisation and aggregation. In this paper we refer to an Entity-Relationship model (ER) as the basic model and an extended or enhanced entity-relationship model (EER) as a model which includes the extra concepts. The ER and EER models are also often used to aid communication between the designer and the user at the requirements analysis stage. In this paper when we use the term “conceptual model” we mean a model that is not implementation specific.ISBN: 978-84-616-3847-5 3594Peer reviewe

Guidelines for representing complex cardinality constraints in binary and ternary relationships

Ternary relationships represent the association among three entities whose constraints database designers do not always know how to manage. In other words, it is very difficult for the designer to detect, represent and add constraints in a ternary relationship according to the domain requirements. To remedy the shortcomings in capturing the semantics required for the representation of this kind of relationship, the present paper discusses a practical method to motivate the designer's use of ternary relationships in a methodological framework. The method shows how to calculate cardinality constraints in binary and ternary relationships and to preserve the associated semantics until the implementation phase of the database development method.This work forms part of the ‘Thuban: Natural Interaction Platform for Virtual Attending in Real Environments’ project (TIN2008-02711), the Spanish Ministry of Industry, Tourism and Trade through the project Semants (TSI-020100-2009-419) and also by the Spanish research projects: MA2VICMR: Improving the access, analysis and visibility of the multilingual and multimedia information in web for the Region of Madrid (S2009/TIC-1542).Publicad

The Use of UML Class Diagrams To Teach Database Modelling and Database Design

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model – towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to it have been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram for conceptual modelling for relational databases, and several popular course text books use UML notation to some degree [2] [3]. This paper looks at the usefulness of using UML class diagrams for teaching database design in undergraduate courses. In this paper we look specifically at two concepts which can cause problems for the novice database designer. Firstly transferring the concept of a weak entity from an Entity Relationship model to UML and secondly the notation for structural constraints in different diagramming notations. We also look at the mixture of notations which students mistakenly use when modelling. This is often the result of different notations being used on different courses throughout their degree. Peter Chen wrote in his original paper “The entity-relationship model can be used as a tool in the structured design of databases using the network model” today we could write “the UML class diagram can be used as a tool in the structured design of databases using the relational model”. Or can we

A Detailed Comparison of UML and OWL

As models and ontologies assume an increasingly central role in software and information systems engineering, the question of how exactly they compare and how they can sensibly be used together assumes growing importance. However, no study to date has systematically and comprehensively compared the two technology spaces, and a large variety of different bridging and integration ideas have been proposed in recent years without any detailed analysis of whether they are sound or useful. In this paper, we address this problem by providing a detailed and comprehensive comparison of the two technology spaces in terms of their flagship languages – UML and OWL – each a de facto and de jure standard in its respective space. To fully analyze the end user experience, we perform the comparison at two levels – one considering the underlying boundary assumptions and philosophy adopted by each language and the other considering their detailed features. We also consider all relevant auxiliary languages such as OCL. The resulting comparison clarifies the relationship between the two technologies and provides a solid foundation for deciding how to use them together or integrate them

What’s in a Relationship: An Ontological Analysis

Abstract. In a series of publications, we have proposed a foundational system of ontological categories which has been successfully used to evaluate and im-prove the quality of conceptual modeling grammars and models. In this article, we continue this work by using this foundational ontology to provide real-world semantics and sound modeling guidelines for one of the most fundamental (and yet one of the most problematic) constructs in conceptual modeling, namely, the relationship type. In addition, we systematically compare our approach with a classical ontological treatment of this construct in the literature, provided by the BWW framework.

Extending the methods for computing the importance of entity types in large conceptual schemas

Visualizing and understanding large conceptual schemas requires the use of specific methods. These methods generate clustered, summarized, or focused schemas that are easier to visualize and understand. All of these methods require computing the importance of each entity type in the schema. In principle, the totality of knowledge defined in the schema could be relevant for the computation of that importance but, up to now, only a small part of that knowledge has been taken into account. In this paper, we extend seven existing methods for computing the importance of entity types by taking into account more relevant knowledge defined in the structural and behavioural parts of the schema. We experimentally evaluate the original and extended versions of these methods with three large real-world schemas. We present the two main conclusions we have drawn from the experiments.Postprint (published version

Large-scale database modeling: Discovering attributes, entities, and relationships

This thesis is concerned with the team efforts to develop a, large database to track medical information. Entity relational model approach is taken to study an extensive set of forms for structure discovery. This approach has led to thousands of attributes and hundreds of entities and relationships. A meta-database is used to manipulate this data for further design