3 Extended Data Modeling

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Silke Eckstein Benjamin Köhncke

Institut für Informationssysteme Technische Universität Braunschweig www.ifis.cs.tu-bs.de

Relational

Database Systems 1

• Alternative ER Notations

• Extended ER –Inheritance

–Complex Relationships

• UML

2 Relational Database Systems 1 – Wolf-Tilo Balke – Institut für Informationssysteme – TU Braunschweig

3 Extended Data Modeling

• There is a plethora of alternative notations for ER diagrams

–Different styles for entities, relationships and attributes

–No standardization among them –Also, notations are often freely mixed

•ER diagrams can look completely different depending on the used tool / book

• In the following, we introduce the (somewhat popular) crow’s foot notation

Relational Database Systems 1 – Wolf-Tilo Balke – Institut für Informationssysteme – TU Braunschweig 3 EN 3.5

3.1 ER – Alternative Notations

• Crow’s foot notation was initially developed by Gordon Everest

–Derivate of 3.1 ERD notation –Main Goal

•Consolidate graphical representation

•Provide a better and faster overview

•Allow for easier layouting

–Widespread use in many current tools and documentations

3.1 ER – Crow’s Foot Notation

• Entity Types

–Entity Types are modeled with a named box –Attribute names are written inside the box separated

by a line

•Key attributes are marked with a leading asterisk

•Composite attributes are represented with indentation

3.1 ER – Crow’s Foot Notation

Book

isbn author

firstName

lastName

title

Book

* isbn author firstName lastName title

• Relationship Types

–Relationship types are modeled by lines connecting the entities

–Line is annotated with the name of the relationship which is a verb

–Cardinalities are represented graphically

•(0, 1) : Zero or one

•(1, 1) : Exactly one

•(0, *) : Zero or more

•(1, *) : one or more

•ATTENTION: Cardinalities are written on the opposite side of the relationship (in contrast to “classic ER”)

3.1 ER – Crow’s Foot Notation

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3.1 ER – Crow’s Foot Notation

owns

Person (0, *) (1, *) Cat

Person owns Cat

• What happens to n-ary relationships or relationship attributes?

* _supplies *

Supplier Costumer

Part

*

number

• Problem

–N-ary relationship types are not supported by crow’s foot notation, neither are relationship attributes

• Workaround solution:

–Intermediate entities must be used

•N-ary relationships are broken down in a series of binary relationship types anchoring on the intermediate entity

Relational Database Systems 1 – Wolf-Tilo Balke – Institut für Informationssysteme – TU Braunschweig 8

3.1 ER – Crow’s Foot Notation

R

A C

B

Ra

A R

B

RB C

Rc

3.1 ER – Crow’s Foot Notation

* *

Supplies number

supplies

Supplier Customer

Part

*

number

Customer Supplier

Part

is used provides

contains

• Originally, ER diagrams were intended to be used on a conceptual level

–Model data in an abstract fashion independent of implementation

• Crow’s foot notation sacrifices some conceptual expressiveness

–Model is closer to the logical model (i.e. the way the data is later really stored in a system)

–This is not always desirable and may obfuscate the intended semantics of the model

3.1 ER – Crow’s Foot Notation

3.1An example (cf. last week)

Student Professor

registration number

name

title credits

id

name department

Lecture

Course of Study enrolls

name part of

prereq.

curriculum semester

id

attends teaches

instantiates time

day of

week room

semester

Lecture instance 1

N N

N N 1

N

1

N N N

• The same example using Crow’s Foot Notation –Note that the “part of” relationship had to use an

intermediate entity

3.1 An example

Student +registrationNumber name

CourseOfStudy +name

Lecture +id title credits Lecture Instance

time dayOfWeek room semester

PartOf curriculumSemester

Professor +id name department attends

enrolls

has has

hasPrerequisite instanciates

teaches

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• Barker’s notation

–Based on Crow’s Foot Notation

–Developed by Richard Barker for Oracle’s CASE modeling books and tools in1986

–Cardinalities are represented differently

•(0, 1) : Zero or one

•(1, 1) : Exactly one

•(0, N) : Zero or more

•(1, N) : one or more

•Cardinalities position similar to Crow’s Foot notation and opposite to classic ER

–Different notation of subtypes

3.1 ER – Even more notations…

• Black Diamond Notation –Cardinalities are represented differently

•Cardinality annotation per relationship, not per relationship end

•1:1

•1:N

•N:M

–Also, N-ary relationships possible

•ternary

3.1 ER – Even more notations…

1 1

1 N

N M

N 1

1

• Traditional ER modeling proved to be very successful in classic “DB” domains:

–Accounting –Banking –Airlines

–Business and industry applications in general –…

3.2 Extended Data Modeling

• However, in the late 70s, popularity of DBs extended into fields with more

complicated data formats

–Computer-aided design and manufacturing (CAD/CAM)

–Geographic information systems (GIS) –Medical information systems –…

• Expressiveness of ERD is not sufficient here

3.2 Extended Data Modeling

• Extended entity relationship (EER) models provide many additional features for more accurate conceptual modeling

–Refinement of relationship types

•Specialization and generalization

•Class, subclass, and inheritance

–Entity sets with existence dependencies –Extended modeling of domains and constraints

• Extended ER contains all features of “classic” ER

3.2 Extended Data Modeling

• Problem:

–Model secret lairs to base highly secret research activities

–Secret island and secret space station are special kinds of secret lairs, share many attributes, but still need some unique attributes

3.2 Subclasses / Superclasses

SecretSpace Station

id name

staff capacity style factor orbital speed mass SecretIsland

id name

staff capacity

style factor location

climate zone

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• Solution: Subclasses and superclasses

• A subclass entity type inherits all attributes and constraints from its superclass entity type

–Subclasses may add additional attributes, constraints or relationship types –In EER, subclass relationship types

are annotated with an open arc, which is opened to the super class (think of set inclusion)

–Describes an “is-a” relationship

3.2 Subclasses / Superclasses

Secret Lair

id name

staff capacity

style factor

orbital speed mass

Secret Space Station

Climate zone location

Secret Island Lair

• Subclass entity types represent subsets of the entity set of the superclass’ entity type

–That is, an entity which is contained in the subclass is also contained in the superclass

–In particular, no entity can only exist in a subclass set

3.2 Subclasses / Superclasses

Secret Lair e1

e3 e4

e6 e5 e2 Secret Lair

• Possible implementation: Two distinct database entries that represent the same instance

–The same instance appears as a database entry in the superclass and subclass sets, and they are related to each other –1:1 relationship on entity level

•Linking two database entries of the same entity in a specialized role –Often, this solution is easier and more flexible to implement

3.2 Subclasses / Superclasses

Secret Lair e1

e4 e6 Secret Lair

e3 e5 e3 e2

e5 e2

• The process of defining a set of subclasses for a superclass is called specialization

–Specialized entity types supplement additional attributes and relationships –“Secret lair” can be specialized into

“secret space station” and “secret island”

• The inverse process is generalization –Generalization suppresses differences

among specialized subclasses

–“Secret space station” and “secret island”

are generalized to “secret lair”

3.2 Specialization / Generalization

Secret Lair

id name

staff capacity

style factor

orbital speed mass Secret Space Station Secret Island

location climate

zone

• Specialization and generalization usually result in the same model

–However, the process of how to reach the model is different

–Specialization: top-down conceptual refinement

•Start with super classes, find suitable subclasses –Generalization: bottom-up conceptual synthesis

•Model sub classes, find proper generalized super class

3.2 Specialization / Generalization

• Specializations can be constrained and modeled in further detail regarding two properties

–Exclusiveness (indicated by a labeled circle)

•Disjoint: Subclasses are mutually exclusive (default, label d)

•Overlapping: Each entity may be contained in more than one subclass (label o)

–Completeness

•Total: No entity is member of the superclass without being member of a subclass (denoted by double line)

•Partial: There are entities that are not contained in any subclass (default)

3.2 Constraints on Specialization

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• Examples

–Disjoint and total:

“A secret lair may either be a secret island or a secret space station (but nothing else).”

Secret Lair

id name

staff capacity

style factor

orbital speed mass Secret Space Station Secret Island Lair

location climate

zone d

• Examples

–Overlapping and partial:

“A villain is a mad scientist, or a super villain, any combination of both, or something else (just a villain).”

Villain id name

Super Power Super Villain Mad Scientist

Scientific Field

o

• Specializations may be predicate-defined –A subclass is predicate-defined if there is a predicate

(condition) that implies an entity’s membership –Condition is added to the specialization line

–Predicate-defined specialization are not necessarily total

Person

id name

Hero Villain

d evilness

Hero Squad evilness > 10

AND ambition > 50 evilness < -10 AND ambition > 50 ambition

• Specializations may be attribute-defined –Attribute-defined is a special case of predicate-defined,

where the membership in subclasses depends on a single attribute value

–Attribute is added to line connecting circle and superclass, condition added to lines connecting circle and subclasses

Person

id name

Hero Villain

d evilness

Hero Squad

< 0 ≥ 0

evilness

• Consequences of specialization

–Deleting an entity from the superclass also deletes it from all subclasses

–Inserting an entity in a superclass automatically inserts it into all matching predicate-defined subclasses

–In a total specialization, inserting one entity into a superclass implies that it has to be inserted into at least one subclass, too

• A subclass may be further specialized

• If every subclass has just one superclass, the inheritance structure is a

specialization hierarchy

• If there are subclasses having

more than one superclass at the same time, the structure is a specialization lattice

–Shared subclasses possible with multiple inheritance

• Subclasses recursively inherit all attributes and relationships of their superclasses up to the root

3.2 Hierarchies and Lattices

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3.2 Hierarchies and Lattices

Villain id name

Scientific Field

o

Villain id name

Scientific Field

o

Evil Mad Super Scientist

Hierarchy Lattice

• An Evil Mad Super Scientist is a Mad Scientist as well as a Super Villain

–Inherits attributes and

relationships of both superclasses

• Science and philosophy always strived to explain the world and the nature of being

–First formal school of studies:

Aristotle’s metaphysics

(“beyond the physical,” around 360 BC) –Traditional branches of metaphysics

•Ontology

–Study of being and existence

•Natural theology

–Study of God, nature and creation

•Universal science –“First Principles” and logics

3.2 Taxonomies & Ontologies

• Ontology tries to describe everything which is (exists), and its relation and categorization with respect to other things in existence

–What is existence? Which things exists? Which are entities?

–Is existence a property?

–Which entities are fundamental?

–What is a physical object?

–How do the properties of an object relate to the object itself?

What features are the essence?

–What does it means when a physical object exists?

–What constitutes the identity of an object?

–When does an object go out of existence, as opposed to merely change?

–Why does anything exist rather than nothing?

• Parts of metaphysics evolved into natural philosophy

–Study of nature and the physical universe –In the late 18^th century, it became just “science”

–Ontology is still a dominant concept in science

•Representation of all knowledge about things

• Ars Generalis Ultima –Created in 1305 by Ramon Llull

–“Ultimate” solution for the Ars Magna (Great Art)

•Mechanical combination of terms to create knowledge

•Base hope: all facts and truths can be created in such a way –Heavy use of Arbor Scientiae (Tree of Knowledge)

•Tree structure showing an hierarchy of philosophical concepts

•Together with various “machines” (paper circles, charts, etc.) reasoning was possible

• Taxonomies (τάξις : arrangement) are part of ontology

–Groups things with similar properties into taxa –Taxa are put into an hierarchical structure

•Hierarchy represents supertype–subtype relationships

•Represents a specialization of taxa, starting with the most general one

–Taxonomies can be modeled with ER using specialization hierarchies

•Taxa are represented by entity types

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• Example: Linnaean Taxonomy

–Classification of all living things by Carl von Linné in 1738

–Classification into multiple hierarchy layers

•Domain, Kingdom, Phylum, Subphylum, Class, Cohort, Order, Suborder, Infraorder, Superfamily, Family, Genus, Species –Each layer adds additional

properties and restrictions

3.2 Taxonomies

• Domain: Eukaryotes

–Organisms having cell membranes

3.2 Taxonomies

Domain

Kingdom Sub-Domains

Animals Here

• Example: Red Squirrel

(Binomial Name: Tamiasciurus hudsonicus) –Kingdom: Animals

–Phylum: Chordata (with backbone)

–Class: Mammalia (with backbone, nursing its young)

–Order: Rodentia (backbone, nursing its young, sharp front teeth) –Suborder: Scriuomorpha (backbone, nursing its young, sharp front

teeth, like squirrel)

–Family: Scriudae (backbone, nursing its young, sharp front teeth, like squirrel, bushy tail & lives on trees (i.e. real squirrel))

–Genus: Tamiasciurus (backbone, nursing its young, sharp front teeth, like squirrel, bushy tail & trees, from N-America)

–Species: Hudsonicus (backbone, nursing its young, sharp front teeth, like squirrel, bushy tail & trees, from N-America, brown fur with white belly)

3.2 Taxonomies

• Example: Edible Dormouse (Binomial Name: Glis Glis)

–Kingdom: Animals

–Phylum: Chordata (with backbone)

–Class: Mammalia (with backbone, nursing its young)

–Order: Rodentia (backbone, nursing its young, sharp front teeth) –Suborder: Scriuomorpha (backbone, nursing its young, sharp front

teeth, like squirrel)

–Family: Gliradae (backbone, nursing its young, sharp front teeth, like squirrel, sleeps long)

–Genus: Glis (backbone, nursing its young, sharp front teeth, bushy tail, like squirrel, eaten by Romans)

–Species: Glis (backbone, nursing its young, sharp front teeth, bushy tail, climbs trees, nothing more to classify)

3.2 Taxonomies

Rodentia (Rodents) d Sciuromorpha (Squirrel-like) Myomorpha

(Mouse-like) Castorimorpha

(Beaver-like) Hystricomorpha

(Hedgehog-like) Anomaluromorpha (Springhare-like) d

Sciuridae

(Squirrel) Aplodontiidae (Mountain Beaver) Gliridae

(Dormouse)

Glirinae (Real Dormouse) Graphiurinae

(African Dormouse) Leithiinae

(Other Dormice)

Glirulus

(Japanese DM) Glis

(Edible Dormouse)

Glis (Yummy) Ratufinae

(Giant Squirrel) Sciurillinae (Pygmy Squirrel) …

Hudsonicus

(Red Squirrel) Douglasi

(Douglas Squirrel) Tamiasciurus

(Pine Squirrel) Pteromyini (Flying Squirrel)

Sciurus

(Common Squirrel) Microsciurus (Micro Squirrel) … d

Scruinae (Real Squirrel)

Sciurini (Tree Squirrel)

d

d d d

• Recently, creating ontological models became fashionable in CS

–So called ontologies

–Widely used in medical informatics, bio-informatics, Semantic Web, etc.

• In addition to “normal” data models, ontologies offer reasoning capabilities

–Allow to classify instances automatically –Allow to extract additional facts from the model

• In CS, ontologies are usually modeled using special languages

–OWL, DAML+OIL, IDEF, …

3.2 Ontologies in CS

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• Inheritance may lead to two special problems –Polymorphism

–Multiple inheritance

• Polymorphism

–Usually, subclasses inherit all attributes and relationships of their supertypes

–Subtypes may define additional attributes/relationships –What happens if an attribute in the subtype means

something different?

–What happens if an attribute is not needed at all?

–What if some attribute should have a different name?

3.2 Polymorphism

• Example:

–Sovereign territory just doesn’t make sense for a space station

•Should be removed

–Geo coordinates are also useless

•But: Orbital trajectory somehow represents the same concept (location)

–Unfortunately, relational databases and ER don’t provide any useful support for polymorphism

•Avoid models where you need it!

•If it is really necessary, constraints and null-values may be used to help out…

3.2 Polymorphism

Secret Lair

id name

sovereign territory geo

Coordinates

mass Secret Space

Station

orbital trajectory

• Multiple inheritance

–A subclass may have multiple superclasses

•Inheritance lattice instead of inheritance hierarchy –But: What happens if superclasses define the

same attribute/relationship differently

•Which one should be inherited?

•Are both needed?

•ER provides no support for conflicting multi-inheritance

–Avoid models with such conflicts

3.2 Multiple Inheritance

Scientific Field

Evil Mad Super Scientist

• In a superclass–subclass relationship, the subclass inherits all attributes and relationships of the superclass(es)

• However, sometimes it is beneficial that a subclass inherits from only one superclass (chosen from a set of potential

distinct superclasses)

–Every space station has an owner

–A space station owner is either a space agency or a super villain

3.2 Union Types

• Solution: Union types –Denoted by a “u” in a circle

–Space agency and Super villain are neither related, nor of the same type

–An owner is either a space agency or a super villain

3.2 Union Types

Space Agency Super Villain

Owner U

owns

Space Station

• Alternative ER Notations

• Extended ER –Inheritance

–Complex Relationships

• UML

3 Extended Data Modeling

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• UML (Unified Modeling Language) is a set of multiple modeling languages and diagram types

–First standardized in 1997

–Unification of dominating object-oriented software design methods

•James Rumbaugh: OMT

•Grady Booch: Boochs Method

•Ivar Jacobsen: OOSE

3.3 UML

• UML provides support for various software modeling problems –Static structural diagrams

• Class diagram

• Component diagram

• Deployment diagram

• Composite structure diagram

• Object diagram

• Package diagram –Dynamic behavior diagrams

• Activity diagram

• State diagram

• Use-case diagram –Interaction diagrams

• Communication diagram

• Sequence diagram

• Timing diagram

• Interaction overview diagram

3.3 UML

• For data modeling, only class diagrams are used –Closely related to ER diagrams in crow’s foot notation

•Additional notations for logical design and operations

• Entity type becomes class

–Attributes written as in crow’s foot notation

•Usually, also domains are modeled –Operations are usually not needed in

pure data models

–Entity type instances are called objects

3.3 UML

CLASS NAME attribute 1 : domain attribute n : domain operation 1 operation m

…

• In UML, relationship types are called associations

• Simplest case: just a plain line

–Although using just a line is valid, a good model should provide additional information

•Name

•Direction

•Multiplicity

•Order

•Navigability

•Special Aggregation Types

3.3 UML

Super Hero Sidekick

• Better:

“A super hero may mentor multiple sidekicks”

–Careful: Multiplicity in opposite direction to Chen ER

3.3 UML

Super Hero Sidekick

mentors mentee mentor

1 *

Roles

Multiplicity (Cardinality) Association name Read direction

• Association navigability

–Denoted by an arrowhead and small cross

–Models how you can navigate among objects involved in the association

–One-way association –Example:

•For each hero, you can navigate to the substances which may kill him

•You cannot natively navigate from a substance to a hero

3.3 UML

Super Hero can kill Substance

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• UML does not allow to add attributes to associations directly

• Workaround: Association classes –Association classes belong to an association

(indicated by dashed line) –They share the association name

–Each instance of the association creates an according class object

3.3 UML

Hero membership Super Team

Membership since: Date

* *

• Association classes cannot directly be replaced by a “normal” class

–Introduces additional semantics

–The replacement model allows that a hero is assigned twice to the same super team!

3.3 UML

Hero membership Super Team

Membership since: Date

* *

Hero

Super Team Membership

since: Date

* *

1 1

• Qualified associations

–Associations may be qualified by an additional attribute

•Each association instance between objects is classified by this attribute

•Semantically stronger as a classifier than an attribute of an association class

–Within a programming language, the qualification attribute would end up as a key of a (hash) map

–Example: “Von Doom Industries employs Victor von Doom as CEO”

3.3 UML

Person employs position Evil Organization

• XOR restrictions on associations

–A class having multiple associations can be modeled in such a way that only one of these associations can be active at a time

–Example: “A villain lives either in a secret lair, or in a prison (but not in both).”

3.3 UML

is safely in custody in

Secret Lair Villain Prison

(xor) happily lives in

• For n-ary associations (n > 2), the diamond returns

3.3 UML

Super Hero Villain

Location fights against

Fights Against date : Date

• Aggregation

–The aggregation is a special association within UML –Colloquial: “is part of” or “consist of”

–Denoted by a small, empty diamond

–Aggregation just states that one class is part of another;

it poses no further restrictions

•Objects may still exist independently of each other

•Objects may be part of several other objects

–Example: “A plan to take over the world consists of several things that need to be done.”

3.3 UML

Plan to take over the world Stuff To Do

* *

whole part

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• Composition (also called strong aggregation) –Stricter version of aggregation

•Diagrammed by solid diamond –Based on multiplicity of the part-side

•1: An object is always part of just one other object.

If the “main” object is deleted, the part needs to be assigned to another “master” or is deleted.

•0..1: An object may be part of at most one other object.

May also exist alone.

•* : Not allowed. Part of one object max.

–Example: “A doomsday machine is made of multiple parts”

3.3 UML

Doomsday Machine Machine Part

1 0..1

• Generalization

–Induces a class-subclass relationship (“is-a”)

•Diagrammed with an hollow arrow –By default, generalization is disjoint

•Overlapping is additionally annotated in curly brackets –By default, generalization is

partial (incomplete in UML)

•Total (complete) is also annotated in curly brackets

3.3 UML

Villain

id : int name : string

Mad Scientist

scientific field : varchar

Super Villain

Super power: varchar

Evil Mad Super Scientist {overlapping}

• Classification attributes

–Similar to EER’s attribute-defined relationship types –Denoted by “:attributeName”

–All objects of a given subtype have the same value for the classifier attribute

3.3 UML

Super-Powered

ethical attitude : varchar

Super Hero Super Villain :ethical attitude

• Class (entity type)

• Associations (relationship types)

• Association class

3.3 UML: Summary

CLASS NAME attribute 1 : domain attribute n : domain operation 1 operation m

…

Class1 Class2

name role2 role1

m1 m2

Roles Multiplicity(Cardinality) Association name

Read direction

Class2 Class1

ACLass

• XOR restriction

• Qualifying attribute

• Aggregation

• Composition

• Navigable association

3.3 UML: Summary

Class 2 q-attr Class 1

Class 1 Class 2 Class 3

(xor)

Class 1 Class 2

Main Part

• Generalization / Specialization

3.3 UML: Summary

General

Special 1 Special 2 {overlapping, total} :attribute1

attribute1: Domain1 Classification Attribute Generalization Modifier

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• Design Patterns: General reusable solution to a commonly occurring problem

–Originated from architecture by Christopher Alexander in 1979

–Concept adopted by Beck and Cunningham for Software Engineering designs

–First great book of software design pattern: Elements of Reusable OO Software by Gamma et al.

–No “real” data model patterns exist

•We informally introduce some

3.3 Data Model Design Patterns

• Design Patterns

–Speed up development process by reusing proven and tested paradigms –Patterns are quite general and must be

instantiated to the actual problem

• Reading Patterns (excerpt) –Name: Name of the pattern

–Intend: What is the reasoning behind the pattern?

–Motivation: A scenario using the pattern

–Applicability: The situation/context the pattern can be used –Structure: Micro-model of the pattern (UML, ER)

–Participants: List and explanation of all classes/entity types used and their role in the design

–Collaboration: Description of the interaction among the classes –Consequences: List of side-effects and trade-offs of usage –…

• Pattern: Composite List

• Scenario:

–Consider a strong room having multiple shelf slots.

Each shelf slot is part of the room, it cannot exist alone nor can it separated. The room properties also affect the slot properties.

• Applicability:

–There is a composition. The whole has multiple parts of the same type which are assigned to the whole and cannot exits alone. There is at least one part.

Properties of the whole also affect the parts.

List 1 1..* List Item

StrongRoom +name +location +securityLevel

StorageSlot +rackNo +slotNo +currentValue

1 1..*

• Pattern: Exemplar–Type

• Scenario:

–Consider a library. You have book titles, and of each title the library owns several actual book exemplars which you can borrow independently.

–There is a simple association. Object associations stay fixed. Class names usually contain terms like type, group, description, etc. A description can, for a short time, exist alone. Without the exemplar class, you would just have a higher degree of redundancy.

Type Description 1 * Exemplar

BookDescription +title +author +publisher +isbn

BookExemplar +inventoryNo +rackNo +borrowedTo +dateOfPurchase

* 1

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• Pattern: Component assembly

• Scenario:

–Assume a car has to be modeled.

It has an engine and four wheels. Those parts are usually attached to the object.

Moving/selling the car usually also means moving/selling the engine and the wheels.

However, the individual parts can be replaced.

–There are physical objects which are composed into a larger object. The parts usually stay together.

Main

1 n Part 2 1 m Part 1

Car

Wheel

Engine Door

1

1 1

4 1

2..4

• Pattern: Coordinator

• Scenario:

–Assume an exam has to be modeled. A student is examined by an professor about a certain lecture.

This takes place at an specific time at a specific location.

–There are simple associations

–The coordinator replaces an n-ary (n ≥ 2) association with an association class (association is “materialized”) –The coordinator has only few attributes, but multiple

associations to exactly one object of other classes.

Student Professor

Lecture

Examination +dateTime +room 1 *

* 1

Class 1

Class 2 Association Class

Class 3 Class 1

Class 2

Coordinator Class 3

1 1

1

1 1

1

* *

* attrib1

attrib1

• Pattern: Roles

• Scenario:

–Consider a tutorial. Persons may participate as listeners. As well, there is one (or multiple) speakers (who are also persons and may also be a listeners).

–There are multiple associations between two classes.

–An object may have multiple roles in regard to the other at the same time.

–Objects have the same attributes independent of their role.

Class 1 role1 role2

Class 2

Person +name Tutorial

+location +dateTime

+speaker +participant

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• Pattern: Changing roles

• Scenario:

–Assume you model a CV. A person has changing occupations in different roles (types).

Depending on the role, different attributes are needed.

–An object can have different roles at different times.

Different roles imply different attributes.

–Roles are modeled by inheritance.

–Associations between object and roles are only extended, i.e. not deleted nor assigned to another object.

Person +name

Occupation +timespan

Employed +company +position

Self-Employed +fieldOfWork

Student +university +courseOfStudy

* 1

• Pattern: Group

• Scenario:

–Employees are part of an department.

–There is a single association

–Several objects belong, at the same time, to one group object.

–Associations between member and group can be created and be removed.

–Group can (for a short time) exist without members.

Employee +name +address +specialization

Department +name +abbreviation +address 0..1

*

• Pattern: Group history

• Scenario:

–Employees are part of an department. They can switch departments and an history has to be kept.

–An object belongs to different groups over time.

–The history is modeled using an associative class.

–Object associations are not changed when membership changes (a new one is added).

–Current group can be found by examining the association class objects.

3.3 Data Model Design Patterns 3.3 Data Model Design Patterns

Employee +name +address +specialization

Department +name +abbreviation +address

*

* Membership +timespan