1. Semantic Object Modeling (SOM)
Methodology for modeling data requirements
Similar to ERM:
represents entities of interest (called semantic objects)
represents characteristics of these objects
represents relationships
uses graphical language

2. SOM Concepts Semantic object (collection of attributes) Attribute
simple attribute
formula attribute
group attribute
semantic object link (SOL) attribute
consists of a semantic object
also called paired attribute
Identifiers
unique, nonunique, surrogate

3. SOM Concepts Subtype semantic objects Cardinality Domain
represent a specialization
subtype object inherits attributes from supertype object
exclusive and nonexclusive
Cardinality
minimum, maximum
relationships between attributes and objects or attributes
multivalued, single-valued attribute
Domain
describes the kinds of values an attribute can have
physical properties, semantic description

4. Domain: Physical Properties and Semantic Description

5. Semantic Object Diagram
Simple Attribute
Unique Identifier
SOL Attribute
Group Attribute
Nonunique Identifier

6. Semantic Object Diagram (cont.)
Group Attributes
Formula Attributes

7. Modeling Subtypes

8. Object View Window
Displays all possible paths from a selected object to other objects to which it is related.
This is essentially SALSA’s way to display relationships but we can only see relationships of one entity at a time.

9. Model-Building Process
Examine application’s attributes and semantic objects; sketch a rough first draft
Start SALSA
Build a profile list
Build the semantic object diagram
Customize the attribute properties
Validate the model
Generate a database schema

10. Comparison of SOM to ERM
Similarities:
Represents conceptual view of data
Supports subtypes
Differences:
Presents attributes, more detailed
Cardinalities between an attribute and another attribute
Domain specification
Formula, group and SOL attributes
“Implicit” presentation of relationships, objects self-contained