Enriched Conceptualization of Subtyping

Author(s):  
Terry Halpin

When modeling information systems, one often encounters subtyping aspects of the business domain that can prove challenging to implement in either relational databases or object-oriented code. In practice, some of these aspects are often handled incorrectly. This chapter examines a number of subtyping issues that require special attention (e.g. derivation options, subtype rigidity, subtype migration), and discusses how to model them conceptually. Because of its richer semantics, the main graphic notation used is that of second generation Object-Role Modeling (ORM 2). However, the main ideas could be adapted for UML and ER, so these are also included in the discussion. A basic implementation of the proposed approach has been prototyped in Neumont ORM Architect (NORMA), an open-source tool supporting ORM 2.

Author(s):  
Terry Halpin

A business domain is typically subject to various business rules. In practice, these rules may be of different modalities (e.g., alethic and deontic). Alethic rules impose necessities, which cannot, even in principle, be violated by the business. Deontic rules impose obligations, which may be violated, even though they ought not to be. Conceptual modeling approaches typically confine their specification of constraints to alethic rules. This chapter discusses one way to model deontic rules, especially those of a static nature. A formalization based on modal operators is provided, and some challenging semantic issues are examined from both logical and pragmatic perspectives. Because of its richer semantics, the main graphic notation used is that of object-role modeling (ORM). However, the main ideas could be adapted for UML and ER as well. A basic implementation of the proposed approach has been prototyped in Neumont ORM Architect (NORMA), a software tool that supports automated verbalization of both alethic and deontic rules.


Author(s):  
Terry Halpin

Some popular information-modeling approaches allow instances of relationships or associations to be treated as entities in their own right. Object-role modeling (ORM) calls this process “objectification” or “nesting.” In the unified modeling language (UML), this modeling technique is called “reification,” and is mediated by means of association classes. While this modeling option is rarely supported by industrial versions of entity-relationship modeling (ER), it is allowed in several academic versions of ER. Objectification is related to the linguistic activity of nominalization, of which two flavors may be distinguished: situational and propositional. In practice, objectification needs to be used judiciously, as its misuse can lead to implementation anomalies, and those modeling approaches that permit objectification often provide incomplete or flawed support for it. This chapter provides an in-depth analysis of objectification, shedding new light on its fundamental nature, and providing practical guidelines on using objectification to model information systems. Because of its richer semantics, the main graphic notation used is that of ORM 2 (the latest generation of ORM); however, the main ideas are relevant to UML and ER as well.


Author(s):  
Esperenza Marcos ◽  
Paloma Caceres

In spite of the fact that relational databases still hold the first place in the market, object-oriented databases are becoming, each day, more widely accepted. Relational databases are suitable for traditional applications supporting management tasks such as payroll or library management. Recently, as a result of hardware improvements, more sophisticated applications have emerged. Engineering applications, such as CAD/CAM (Computer Aided Design/ Computer Aided Manufacturing), CASE (Computer Aided Software Engineering) or CIM (Computer Integrating Manufacturing), office automation systems, multimedia systems such as GIS (Geographic Information Systems) or medical information systems, can be characterized as consisting of complex objects related by complex interrelationships. Representing such objects and relationships in the relational model implies that the objects must be decomposed into a large number of tuples. Thus, a considerable number of joins is necessary to retrieve an object and, when tables are too deeply nested, performance is dramatically reduced (Bertino and Marcos, 2000).


2011 ◽  
pp. 2650-2664
Author(s):  
Renato Barrera ◽  
Abraham Alcántara ◽  
Carlos Alegría ◽  
Ana L. Ávila ◽  
David Esparza

This article presents a system to enable access to those Information Systems at the National Autonomous University of Mexico (UNAM) that are related to Biodiversity and the Environment. The system in question associates existing Geographic Information Systems (GIS’s) as well as standard relational databases in a federation, allows the contents of the individual GIS (or relational databases) to be consulted in a manner transparent to the user, and permits the exports of the underlying systems’ data under the corresponding set of permissions. Our approach is based upon three principles: compliance with international standards, reliance upon Open Source Software in implementation, and usage of servers of proven reliability and robustness. [Article copies are available for purchase from InfoSci-on-Demand.com]


Author(s):  
Andy Carver ◽  
Terry Halpin

This paper contrasts two different approaches to designing relational databases that are free of redundancy. The Object-Role Modeling (ORM) approach captures semantics in terms of atomic (elementary or existential) fact types, before grouping the fact types into relation schemes. Normalization by decomposition instead focuses on “non0loss decomposition” to various, and progressively more refined, “normal forms”. Traditionally, non0loss decomposition of a relation requires decomposition into smaller relations that, upon natural join, yield the exact original population. Non-loss decomposition of a table scheme (or relation variable) requires that the decomposition of all possible populations of the relation scheme is reversible in this way. This paper shows that the dependency requirement for “all possible populations” is too restrictive for definitions of multi-valued and join dependencies over relation schemes. By exploiting ORM modeling heuristics, the authors offer new definitions of these data dependencies and non-loss decomposition, to enable these concepts to be addressed at a truly semantic level.


2020 ◽  
pp. 100001
Author(s):  
Wilko Heitkoetter ◽  
Bruno U. Schyska ◽  
Danielle Schmidt ◽  
Wided Medjroubi ◽  
Thomas Vogt ◽  
...  

2021 ◽  
Vol 139 ◽  
pp. 105001 ◽  
Author(s):  
Yiyi Ju ◽  
Masahiro Sugiyama ◽  
Diego Silva Herran ◽  
Jiayang Wang ◽  
Akimitsu Inoue

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