Entity–relationship model

A sample ER diagram

In software engineering, an Entity-Relationship Model (ERM) is an abstract and conceptual representation of data. Entity-relationship modeling is a database modeling method, used to produce a type of conceptual schema or semantic data model of a system, often a relational database, and its requirements in a top-down fashion.

Diagrams created using this process are called entity-relationship diagrams, or ER diagrams or ERDs for short.

The definitive reference for entity relationship modelling is generally given as Peter Chen's 1976 paper. However, variants of the idea existed previously (see for example A.P.G. Brown) and have been devised subsequently.

Overview

The first stage of information system design uses these models during the requirements analysis to describe information needs or the type of information that is to be stored in a database. The data modeling technique can be used to describe any ontology (i.e. an overview and classifications of used terms and their relationships) for a certain area of interest. In the case of the design of an information system that is based on a database, the conceptual data model is, at a later stage (usually called logical design), mapped to a logical data model, such as the relational model; this in turn is mapped to a physical model during physical design. Note that sometimes, both of these phases are referred to as "physical design".

There are a number of conventions for entity-relationship diagrams (ERDs). The classical notation mainly relates to conceptual modeling. There are a range of notations employed in logical and physical database design, such as IDEF1X.

The building blocks: entities, relationships, and attributes

Two related entities

An entity with an attribute

A relationship with an attribute

Primary key

An entity may be defined as a thing which is recognized as being capable of an independent existence and which can be uniquely identified. An entity is an abstraction from the complexities of some domain. When we speak of an entity we normally speak of some aspect of the real world which can be distinguished from other aspects of the real world.

An entity may be a physical object such as a house or a car, an event such as a house sale or a car service, or a concept such as a customer transaction or order. Although the term entity is the one most commonly used, following Chen we should really distinguish between an entity and an entity-type. An entity-type is a category. An entity, strictly speaking, is an instance of a given entity-type. There are usually many instances of an entity-type. Because the term entity-type is somewhat cumbersome, most people tend to use the term entity as a synonym for this term.

Entities can be thought of as nouns. Examples: a computer, an employee, a song, a mathematical theorem. Entities are represented as rectangles.

A relationship captures how two or more entities are related to one another. Relationships can be thought of as verbs, linking two or more nouns. Examples: an owns relationship between a company and a computer, a supervises relationship between an employee and a department, a performs relationship between an artist and a song, a proved relationship between a mathematician and a theorem. Relationships are represented as diamonds, connected by lines to each of the entities in the relationship.

The model's linguistic aspect described above is utilized in the database query language ERROL.

Entities and relationships can both have attributes. Examples: an employee entity might have a Social Security Number (SSN) attribute; the proved relationship may have a date attribute. Attributes are represented as ellipses connected to their owning entity sets by a line.

Every entity (unless it is a weak entity) must have a minimal set of uniquely identifying attributes, which is called the entity's primary key.

Entity-relationship diagrams don't show single entities or single instances of relations. Rather, they show entity sets and relationship sets. Example: a particular song is an entity. The collection of all songs in a database is an entity set. The eaten relationship between a child and her lunch is a single relationship. The set of all such child-lunch relationships in a database is a relationship set. In other words, a relationship set corresponds to a relation in mathematics, while a relationship corresponds to a member of the relation.

Certain cardinality constraints on relationship sets may be indicated as well.

Diagramming conventions

Entity sets are drawn as rectangles, relationship sets as diamonds. If an entity set participates in a relationship set, they are connected with a line.

Attributes are drawn as ovals and are connected with a line to exactly one entity or relationship set.

Cardinality constraints are expressed as follows:

• a double line indicates a participation constraint, totality or surjectivity: all entities in the entity set must participate in at least one relationship in the relationship set;
• an arrow from entity set to relationship set indicates a key constraint, i.e. injectivity: each entity of the entity set can participate in at most one relationship in the relationship set;
• a thick line indicates both, i.e. bijectivity: each entity in the entity set is involved in exactly one relationship.
• an underlined name of an attribute indicates that it is a key: two different entities or relationships with this attribute always have different values for this attribute.

Attributes are often omitted as they can clutter up a diagram; related diagram techniques often list entity attributes within the rectangles drawn for entity sets.

Two related entities shown using Crow's Foot notation

Chen's notation for entity-relationship modeling uses rectangles to represent entities, and diamonds to represent relationships appropriate for first-class objects: they can have attributes and relationships of their own.

Other diagramming convention techniques:

• Bachman notation
• EXPRESS
• IDEF1X
• Martin notation
• (min, max)-notation of Jean-Raymond Abrial in 1974
• UML

Crow's Foot

Crow's Foot notation is used in Barker's Notation, SSADM and Information Engineering. Crow's Foot diagrams represent entities as boxes, and relationships as lines between the boxes. The ends of these lines are shaped to represent the cardinality of the relationship.

Usage of Chen notation is more prevalent in the United States, while usage of Crow's Foot notation was used primarily in the UK. Crow's Foot notation was used in the 1980s by the consultancy practice CACI. Many of the consultants at CACI (including Barker) subsequently moved to Oracle UK, where they developed the early versions of Oracle's CASE tools, introducing the notation to a wider audience. Crow's Foot notation is used by these tools: ARIS, System Architect, Visio, PowerDesigner, Toad Data Modeler, DeZign for Databases, Devgems Data Modeler, OmniGraffle, MySQL Workbench and Dia.

ER diagramming tools

There are many ER diagramming tools. Some of the proprietary ER diagramming tools are ARIS, Avolution, dbForge Studio for MySQL, DeZign for Databases, ConceptDraw, ER/Studio, Devgems Data Modeler, ERwin, MEGA International, Metastorm ProVision[1], OmniGraffle, Oracle Designer, PowerDesigner, Rational Rose, SmartDraw, Sparx Enterprise Architect, SQLyog, System Architect, Toad Data Modeler, SQL Maestro, Microsoft Visio, and Visual Paradigm. A freeware ER tool that can generate database and application layer code (webservices) is the RISE Editor.

Some free software ER diagramming tools that can interpret and generate ER models, SQL and do database analysis are StarUML, MySQL Workbench, Mogwai, Power*Architect, SchemaSpy, and SchemaCrawler.

Some free software diagram tools just draw the shapes without having any knowledge of what they mean, nor do they generate SQL. These include Kivio and Dia. DIA diagrams, however, can be translated with tedia2sql.

See also

• Associative entity
• Data structure diagram
• Enhanced Entity-Relationship Model
• Object Role Modeling
• Three schema approach
• Unified Modeling Language
• Value range structure diagrams

Further reading

• Richard Barker (1990). CASE Method: Tasks and Deliverables. Wokingham, England: Addison-Wesley.
• Paul Beynon-Davies (2004). Database Systems. Houndmills, Basingstoke, UK: Palgrave
• Peter Chen (March 1976). "The Entity-Relationship Model - Toward a Unified View of Data". ACM Transactions on Database Systems. 1 (1): 9–36. doi:10.1145/320434.320440.

External links

• An Entity Relationship Diagram Example. Demonstrates the crow's feet notation by way of an example.
• "Entity-Relationship Modeling: Historical Events, Future Trends, and Lessons Learned" by Peter Chen.
• "English, Chinese and ER diagrams" by Peter Chen.
• Case study: E-R diagram for Acme Fashion Supplies by Mark H. Ridley.
• Logical Data Structures (LDSs) - Getting started by Tony Drewry.
• Introduction to Data Modeling