DOC PREVIEW
GSU CIS 8040 - 3. Semantic Modeling

This preview shows page 1-2-3-4-5 out of 16 pages.

Save
View full document
View full document
Premium Document
Do you want full access? Go Premium and unlock all 16 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 16 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 16 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 16 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 16 pages.
Access to all documents
Download any document
Ad free experience
Premium Document
Do you want full access? Go Premium and unlock all 16 pages.
Access to all documents
Download any document
Ad free experience

Unformatted text preview:

3 - 1 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] CIS 8040 – Semantic Data Modeling Conceptual Modeling Outline What is Conceptual Data Modeling Entity-Relationship (E-R ) Modeling Limitations of E-R Modeling Object-oriented Modeling: Another semantic model (discussed later in this course)3 - 2 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] What Is Conceptual Data Modeling? A process that represents the entities, relationships, and activities of an enterprise in terms of a set of abstract concepts of a chosen data model for specific purposes. Enterprise Modeling, Business Modeling Conceptual Perception of an Enterprise Bridge the Gap STUDENT( ID, Name, Age, Address, GPA ) INSTRUCTOR ( Emp#, Name, Rank, Dept ) COURSE ( Course#, Credits, Title ) CLASS ( Emp#, ID, Course#, Time, Room )3 - 3 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Data Semantics Static Information  Data -- Entities  Associations -- Relationships among entities Dynamic Information  Activities -- Operations/transactions  Integrity constraints -- Business rules/regulations and data meanings Conceptual Data Model Revisited A conceptual data model consists of:  A collection of formal concepts  A set of usage rules Different models have different modeling capability Conventional data modeling Semantic data modeling Object-Oriented data modeling -- Hierarchical -- Network -- Relational -- E-R -- EER -- etc. -- Relational3 - 4 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Entity Relationship (E-R) Modeling Introduced by Peter Chen in 1976 Basic modeling concepts:  Entities, entity types, and attributes  Relationships InstructorOfficeAssigned1 1 DepartmentWorks_forN 1 Teaches N M CourseDateLanguageEmp#NameFNameMInitLNameTimeLocationDateE-R Notation (there is no standard) Entity Relationship Attribute Primary Key3 - 5 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Entities An entity is a conceptual object Physically exists  Usually a noun in requirements specification Jose Alice Steve CIS 8040 CIS 3730 Acct CIS Student Class Department Entity Types A collection of similar entities An abstraction of "physical" entities  A noun in requirement specifications  Has "independent" meaning Student Course Department Jose Alice Steve CIS 8040 CIS 3730 Acct CIS3 - 6 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Attributes Properties or characteristics of entities and entity types (Attributes do not describe!)  Attribute values – Property values of entities which describe the entities  Value set - All acceptable attribute values  Attributes (definitions) -- Properties of entity types A noun or an adjective in requirement specifications No "independent" meaning ID Student Age Jose "123-45-6789" 25 Key Attributes  One or a group of attributes that can uniquely identify individual entities of an entity type  A key refers to one or a group of attributes as a whole  A key attribute is a component attribute of a key  Key changes with data semantics  An entity type may have several qualified keys  Primary key -- One of the candidate keys  Alternate key - Candidate keys not used as the primary key  Secondary key -- An identifier of records with similar properties of interest  The primary key attribute(s) is(are) underlined3 - 7 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] More Attributes Simple attribute Contains atomic values only Composite attribute Has component attributes _____________________________________ Single-valued attribute Has exactly one value per entity Multi-valued attribute Contains repeating values per entity _____________________________________ Derived Attribute can be created from existing attributes Student id age name degrees Fname Mname Lname StartDate YearsAttended Relationships Associations among entities  Relationships -- Associations among entities Usually a verb in requirement specification Student Course Takes Course Student Takes Joseph Alice Sue Tom Peter . . . CIS2010 CIS3210 CIS8600 CIS3730 CIS8140 . . . Occurrence Diagram3 - 8 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Relationship Cardinality (Occurrence diagram shown below) How entities are connected through a relationship  One-to-One -- An entity of E1 is connected to at most one entity of E2 and vice versa.  One-to-Many -- An entity of E1 may be connected to one or more entities of E2, but an entity of E2 can only be mapped to at most one entity of E1.  Many-to-Many -- An entity of E1 may be linked to one or more entities of E2, and vice versa. [ ][ ][ ]...abc...xyz...[ ][ ][ ]...abc...xyz......abc...xyz...E1 E2 R 1 1 1 M M N Structural Constraints • Main type of constraint on relationships is called multiplicity. • Multiplicity - number (or range) of possible occurrences of an entity type that may relate to a single occurrence of an associated entity type through a particular relationship. • Represents policies (called business rules) established by user or company.3 - 9 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Multiplicity  The minimum and maximum number of entities participating in the relationship  Must be shown in both directions Relationship Degrees The number of


View Full Document

GSU CIS 8040 - 3. Semantic Modeling

Download 3. Semantic Modeling
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view 3. Semantic Modeling and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view 3. Semantic Modeling 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?