Month Year

April 1998

Issue: 1

Editor's Notes: Welcome!
by Scot A. Becker

Welcome to the premiere issue of the Journal of Conceptual Modeling! Please allow me to introduce myself: I am Scot Becker, an Associate of InConcept and editor of this journal. This is the "From the Editor" section. I'll use this area to rant about things, ask for help, talk about some news items, and promote some things now and then. I'll also provide a synopsis of each issue (see that last section below). I've got a lot to cover for this issue, so this edition may be a bit longer than normal.

UML Data Models from an ORM Perspective (Part 1)
by Dr. Terry Halpin

Abstract: Although the Unified Modeling Language (UML) facilitates software modeling, its object-oriented approach is arguably less than ideal for developing and validating conceptual data models with domain experts. Object Role Modeling (ORM) is a fact-oriented approach specifically designed to facilitate conceptual analysis and to minimize the impact on change. Since ORM models can be used to derive UML class diagrams, ORM offers benefits even to UML data modelers. This multi-part article provides a comparative overview of both approaches.

Composite Objects in Relational and Object Relational
Constructs Using InfoModeler 3.1 (Part One)
by Pat Hallock

Object Role Modeling creates a conceptual model, which can be used with different drivers giving different logical and physical models. Presented here are two simple examples of composite ORM objects. The first is a "Room" where a class is held. The second is an "Address" playing a "ship to" and a "bill to" role with a company.

Sharp Informatics Example Problem
by Dr. John K. Sharp

The following simplified example shows how Natural Language Modeling can be used to express three distinct kinds of knowledge that results in 1) database requirements, 2) derivation rules for knowledge presentation to humans or automated rule enforcement, and 3) instructions for humans to follow. Natural Language Modeling always starts with example(s) of the problem that is to be modeled. In this case the examples are taken from an instruction manual for security guards and a legacy security application. Subject matter expert(s) are asked to create a true sentence based on the example information. Results from the analysis are presented here. The NLM procedure will turn any true declarative sentence into instance(s) of valid fact type(s). For brevity the example is not wholly defined. This analysis technique scales linearly. That means that knowledge is defined only once. Then as the scope of a project expands, previously defined knowledge does not need to be reanalyzed.

Death and Taxes
by John M. Miller

It has been said that the only certainties in life are death and taxes. If this is true, then everything else is liable to change at one point or another. If you exclude death and taxes then change is the third certainty.

InfoModeler Tips and Tricks: General Tips, Issue One
by Dr. Anthony Bloesch

Common Model Fragments: People and Organizations
by Scot A. Becker

A good portion of data modeling can be pretty routine. Often, organizations tend to track the same things: people, organizations, hierarchies, contacts, products, invoices, etc. Now I won't presume to make the best model for all situations. (Heh…actually, I won't presume to even have them totally correct!) I will try to address some generic issues, however, and provide you with a starting point