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8. CONCEPTUAL DATA MODELING:FUNDAMENTAL CONCEPTS

First step in designing a database: specifying conceptualschema.

2009 John P. Shewchuk ISE 3024 Course Notes 8 1

This is a critical step. Without an accurate conceptualschema, resulting information system may not meet ourneeds or even function properly.

Conceptual schema is blueprint for informationsystem design.

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Lets first describe fundamental data modeling concepts,so that we know how to specify a conceptual schema.

We will do this in the context of an old-fashionedbookstore.


Well then see how we can use the discovery processtodevelop conceptual schema.

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8.1 Entities, Entity Classes, Attributes andAttribute Values

Entity = some particular object of interest to us.

e.g., a book having ISBN 0-13-056517-2


Thomson International

shelf s4

(a book supplier)

(a shelf at Annas Books which holdsbooks)

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Entity Class= collection of similar entities

e.g., Book entity class

Customer entity class

Supplier entity class


Shelf entity class

We can also think of entities as instances of a given class.

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Attributes= characteristics used to define similar entities.

e.g., Book entities defined by ISBN,title,author,publisher,year,price,bookId


Customer: lastname,firstname,address

Supplier: name,state,phone,rating

Shelf: shelfId

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Attribute Values= values for attributes for a particularentity.

e.g., Book entities:

12 Star Wars: Jedi Trial Dan Cra Random House 0-3454-6115-0 2005 $6.99

book

Id title author publisher ISBN year price


27 Band of Brothers Stephen Ambrose Simon & Schuster 0-7432-2454-X 2001 $17.829 Circle of Friends Maeve Binchy Dell Publishing 0-4402-1126-3 1995 $7.99

37 Message In A Bottle Nicholas Sparks Time Warner 1-5948-3636-1 1999 $7.50

23 The Long Road Home Danielle Steel Dell Publishing 0-4402-4344-0 2006 $14.99

4 Star Wars: Jedi Trial Dan Cragg Random House 0-3454-6115-0 2005 $6.99

18 Beyond Valor Patrick ODonnell Simon & Schuster 0-6848-7385-0 2001 $8.99

32 Curious George Margret and H.A. Rey Houghton Mifflin 0-3951-5023-X 1973 $14.00

17 Beyond Valor Patrick ODonnell Simon & Schuster 0-6848-7385-0 2001 $8.99

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Customer entities:

address

lastName firstName street city state zip

Smith John 214 Church St. Blacksburg VA 24073

Davis Diane 185 Clay St. Blacksburg VA 24073


Smith John 24 Range Road Radford VA 24141

Morgan Leslie 240 Kent St., Apt. 27 Christiansburg VA 24061

Carter Brian 14 2nd Street Lafayette IN 47096

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Supplier entities: Shelf entities:

name state phone rating

Thomson International CA (216)-175-5065 A

ABC Books IN (216)-831-9175, A

(704)-668-2203

shelfId

s1

s2

s3


BookWorld VA (331)-791-4982, C(501)-773-7381

s4s5

s6

:

s40

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8.2 More on Attributes

Every attribute is one of three types:

single-valued, e.g., title

multivalued, e.g.,phone

(attribute of Book)

(attribute of Supplier)


compos e, e.g., address

Additionally, every attribute is either a key or non-keyattribute.

Key Attribute(s) = set of one or more attributes whichuniquely identify entities within a class.

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Possible key attributes for our book store entity classes:Book:

Customer:

Supplier:Shelf:

bookId

{lastName, firstName, address}


I an entity class has more than one key (i.e., sets o keyattributes), one of the keys is designated the primary key.The other keys are then called secondary keys.

Specification of key attributes for entity classes is animportant part of data modeling. So be careful!

Primary key: single attribute, value unlikely to change

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Key attributes must always have values. But what aboutthe remaining (i.e., non-key) attributes?

Such attributes should normally always have values as

well. The special case of an empty space (field) is calleda null value(or simply null ).


e nu va ues are some mes necessary, ey s oube avoided if possible due to the ambiguity they create.For example, null could mean

the attribute is not applicable for that entity

the value is known but missing (i.e., not recorded).

the value is unknown.

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e.g.,address

lastName firstName street city state zip

Smith John 214 Church St. Blacksburg VA 24073

Davis Diane

OKeefe Patrick 35 Cambria St. VA 24061

Smith John 24 Range Road Radford VA 24141


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8.3 Defining Attributes

Every attribute is defined via the following:

i) a name

ii) a data type

- e.g., integer, string, currency, date


a engiv) a format

v) a domain, or set of possible values

vi) a description

- e.g., - g n eger, -c arac er s r ng

- e.g., #.## for decimal

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Data

Name Type Length Format Domain Description Example

title string unbounded none none Title of a book Beyond Valor

address composite Two strings of none none An address con- 214 Church St.,string 36 characters, sisting of street, Blacksburg,

one 2-char city, state, and VA, 24073string, one zipcode

e.g.,


5-char string

phone string 10 char xxx-xxx-xxxx none A phone number 216-175-5065

price currency 5 digits $xxx.xx none Price ($,cents) 17.42

shelfId string 2 char none s1s6 Shelf identifier s3

year integer 4 digits none Values Year (Julian 19941900-2010 calendar)

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Attribute values may also have constraints as follows: Key values for associated attributes must be

unique for every entity in that class.

- this constraint on key values known as akey constraintor entity integrity constraint.

- database system responsible for enforcing.


Not Null

Derived attribute is not entered directly, but rather is

calculated from some other information.

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8.4 Relationships and Relationship Types

In many situations, entities are related to one another.

e.g., whenever a customer buys a book, a relationship iscreated between that customer and that book.


Important part of data modeling: establishing what kindsof relationships can occur and incorporating thisinformation into the data model.

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Relationship Type= specification of the nature of anassociation that one entity may havewith another (entities of differentclasses usually)

e.g., Customer Purchases Book


Relationship = specific association between two actualentities, per given relationship type.

e.g., John Smith buys Band of Brothers

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We can also think of relationships as instances of a givenrelationship type.

How are relationship types designated? Each relationship

type consists of a verb phrasewhich can be used in asentence with the entity classes, e.g.,

Phrase Relationshi T e Between


A customer buys a book Purchases Customer, BookBooks are found on shelves FoundOn Book, Shelf

We can also specify relationship types in reverse order.

e.g., Shelf Holds Book

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Relationship types may have their own attributes.


whenever a customer buys a book, we may want torecord the date of the sale.

the corresponding attribute, saleDate, only exists


or a g ven sa e, .e., cus omer an oo .

e.g., Book AvailableFrom Supplier

price = cost of that book from that supplier

=attribute of relationship typeAvailableFrom

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8.5 Constraints on Relationship Types

Cardinality Ratio Constraint specification of how manyentities from either class, can

be involved in a relationshipof a given type.


Three types of cardinality ratio constraints.

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One-to-One (1:1) an entity from either class may berelated to at most one entity fromthe other class.

e.g., relationship type isMarriedTo betweenManandWoman


Man toWoman is 1:1

ac man may e marr e o a mos one woman.

Each woman may be married to at most one man.

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One-to-Many (1:M) an entity from the first class maybe related to multiple entries fromthe second: an entity from thesecond may be related to at most

one entity from the first.



Customer to Book is 1:M

Each customer may purchase many books.

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Many-to-Many (M:N) an entity from either class maybe related to multiple entriesfrom the other class.

e.g., Book AvailableFrom Supplier

Each book may be available from multiple


Book to Supplier is M:N

.

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Other types of constraints on relationships: Min/Max Constraints specifies how many relationships

of a given type an entity may have.

e.g., Shelf Holds Book. Each shelf can hold nomore than 60 books.


-

- min cardinality of Book = 0

every Shelf entity can be associated withbetween 0 and 60 Book entities.

some Shelf entities may not be associatedwith any Book entities.

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Each book, however, is found in exactly one shelf.- max cardinality of Shelf = 1

- min cardinality of Shelf = 1

every Book entity can be associated withbetween 1 and 1 Shelf entity.


one Shelf entity.

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Participation Constraints specify whether or not entitiesmust participate in associated relationship types.


- participation of Customer is optional(Customer can exist without any books)

- participation of Book is optional


e.g., Shelf Holds Book

- participation of Shelf is optional

(Some shelves may not have any books)- participation of Book is mandatory

(Every book must be located on some shelf)

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Note that optional participation when min cardinality of related

entity class = 0= 0= 0= 0.

mandator artici ation when min cardinalit of

e.g., cardinality of Book = (0..60) participation ofShelf optionaloptionaloptionaloptional


related entity class > 0> 0> 0> 0.

Thus, we can use min cardinality to determine and/orspecify whether participation is mandatory or optional.

e.g., cardinality of Shelf = (1..1)

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8.6 The Discovery Process

To obtain the data needed to construct a conceptualschema, the discovery processis used.

This consists of interviewing the people involved with thedata management application, analyzing current


, .,

the user requirements. What kind of operations arethe users interested in performing on the data? Whattypes of querieswill they be interested in?

the objects of interest (entities), their characteristics(attributes), and how they interact (relationships), interms of satisfying the user requirements.

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The result of interviews, document collection, etc., arenarrative descriptions of how the system (or some part ofit) works or what information must be extracted from it.

Such descriptions are often incomplete, conflicting,ambiguous, and/or contain irrelevant information.


,

compile, and analyze the descriptions to identify entityclasses, attributes, and relationship types.

This is often an iterative process, and can result intensions and conflicts. So good people skills are critical tothis step.

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Note also that the discovery process often results ininformation describing how the data managementapplication must behave.

While not part of the conceptual schema, thisinformation must still be documented as it will beneeded later on in developing the database application.


Such information is often referred to as the behavioralmodel of the system.

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8.7 Example: Conceptual Data Modeling for AnnasBooks

Annas BooksAnnas BooksAnnas BooksAnnas Books is a small, locally-operated bookstore

which sells books the old-fashioned way (i.e., person-to-person, with no online sales).


The store owner has hired you as a consultant to designand implement an information system to aid in sellingbooks.

The discovery process has resulted in the followingdescription of user requirements and system operation:

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Annas Books is a small bookstore which sells books towalk-in customers. The owner wants computer support in

locating where (i.e., on what shelf) a given book can be

found.

determining how many copies of a given title are on


.

tracking customer sales, and

keeping track of what books are available from whichsuppliers, and at what price.

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Customers purchase one or more books at a time: for each

purchase, the date must be recorded. The first and last name ofeach customer is known: it is desirable to also know eachcustomers address (for advertising purposes). The title, author,publisher, year, price, and ISBN # are recorded for each book.

Books are located on one of forty shelves. Each shelf can hold upto sixty books. All books of the same type (i.e., title) are to be kept

_________ _____

______


.

Books are obtained from different suppliers, each of whom has arating (A, B, or C), is located in a particular state, and can becontacted via one or more phone numbers. Every book is available

from at least two different suppliers: a single supplier may supplymany different books. Suppliers not able to provide any booksshould still be kept on record. For each book and possible supplier,we need to know the book price.

________

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(a) Entity classes, attributes, and additional attribute information:

Entity Class AttributeAttribute Type and/or

Constraints

Customer firstName

lastNameaddress

Partial key

Partial keyPartial key; compositeattribute consisting ofstreet, city,


s a e, z p

Book bookId

title

author

publisher

yearprice

ISBN

Key

Currency; not null

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Constraints

Supplier name

statephone

rating

Key

Multivalued attributeValue from {A, B, C}

Shelf shelfId Key


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(b) Relationship types, cardinality ratio constraints, and attributes:

Relationship Type andEntity Classes

CardinalityRatio Attributes

Customer Purchases Book 1:M saleDate

Book AvailableFrom Supplier M:N price

Shelf Holds Book 1:M


Note that as (i) Shelf has no other attributes besides key,and (ii) has only a simple relation with Book, we couldsimply make shelfIdan attribute of Book.

Best to leave as a separate entity, however: meaning clearer.

may want to provide additional shelf information later.

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(c) Participation constraints and min/max cardinality constraints:

Relationship Type Entity Class ParticipationConstraint

Min/MaxCardinality

Purchases Customer optional (0..1)

Book optional (0..M)


AvailableFrom Book mandatory (0..M)Supplier optional (2..N)

Holds Shelf optional (1..1)

Book mandatory (0..60)

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You are an IE at JA IndustriesJA IndustriesJA IndustriesJA Industries, a company employing

cellular manufacturing.

8.8 Example: Conceptual Data Modeling for JAIndustries


e p an manager as c arge you w mprov ng

productivity on the shop floor.

The discovery process has resulted in the followingdescription of user requirements and system operation.

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JA Industries produces various machined components viathe use of manufacturing cells. The company aims toimprove productivity on the shop floor.

Typical questions arising in support of this effort:

Where (i.e., what machine and/or cell) are parts located?


What is the status (e.g., busy) of each machine? What processes are required for a given part?

Which machines are capable of a given process?

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Each cell at JA Industries has a unique cell number, is of a

specific type, and consists of 2-4 machines. Some cells alsocontain a robot for loading/unloading machines, in which casethe single robot handles all machines in the cell. Every robothas a particular number, and is of a specific type and model.

Shop workers perform load/unload if there is no robot in a cell.

Each machine has a unique name, and is of a specific type. A


separa e num er en es e mac ne amongs a mac nes

of that type (e.g., 3rd machine of type T4).

Every machine can perform up to 5 different processes, whereeach process is defined by a unique identifier and a process

description. Every process can be performed by at least onemachine: some can be done by multiple machines. Not allmachines perform a given process equally: the efficiency mayvary from one machine to another.

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Each part produced in the facility has a unique serial number

(SN) and is of a given type. For each part type, a unique processplan exists. The process plan specifies the sequence ofoperations (between 1 and 4) for that part type, where eachoperation is defined by machine, process, setup time, and run

time.

Also associated with each process plan is a list of the planners


respons e or e p an. ome processes an mac nes may no

be required for any operations.

At any given time during production, every part in the system islocated at a machine (i.e., in process or waiting to be processed).

A given machine may not have any parts, however. Additionally,at any time, each machine is either busy, idle, or down.

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Constraints

Cell cellNo Key

cellType

Robot robotNo Key

(a) Entity classes, attributes, and additional attribute information:


ro o ype

robotModel

Machine machName Key

machNo Partial secondary key

machType Partial secondary keystatus Values from {busy, idle, down}

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Entity Class Attribute

Constraints or Further

Description

Part partSN Key

Op

Process processId Keyprocess

Description


ey

partType

planners Multivalued attribute

date

Operation opno Keysetup

run

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Relationship Type andEntity Classes

CardinalityRatio Attributes

Cell Has Machine 1:M

Cell Contains Robot 1:1

Robot Serves Machine 1:M

(b) Relationship types, cardinality ratio constraints, and attributes:


ac ne as ar :

Process DoneAt Machine M:N efficiency

Process DoneVia Operation 1:M

Machine Performs Operation 1:M

ProcessPlan Has Operation 1:MProcessPlan For Part 1:M

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RelationshipType

Entity Class ParticipationConstraint

Min/MaxCardinality

Has Cell mandatory (1..1)

Machine mandatory (2..4)

(c) Participation constraints and min/max cardinality constraints:


Conta ns Ce opt ona ..

Robot mandatory (0..1)

Serves Robot mandatory (0..1)

Machine optional (2..4)

Has Machine optional (1..1)

Part mandatory (0..M)

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RelationshipType

Entity Class ParticipationConstraint

Min/MaxCardinality

DoneAt Process mandatory (1..5)

Machine mandatory (1..M)

DoneVia Process optional (1..1)

Operation mandatory (0..M)


..

Operation mandatory (0..M)

Has ProcessPlan mandatory (1..1)

Operation mandatory (1..4)

For ProcessPlan optional (1..1)

Part mandatory (0..M)

Documents

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