An entity-relationship (ER) model describes the information a database needs to represent: the kinds of things involved, their properties, how they are associated, and the rules that govern those associations. An ER diagram is a visual way to show that model. ER modeling helps clarify requirements before they are translated into a logical database schema and implemented in a particular database system.
What an entity-relationship model describes
An ER model represents a domain’s data structure. It is concerned with facts such as which kinds of things matter, what details describe them, and which connections between them are valid. It does not describe an application’s screens or behavior, and it is not itself a running database.
The model has four core parts: entities, attributes, relationships, and constraints. Together, these let people discuss the required information and its rules before committing to tables or platform-specific implementation details.
The parts of an ER model
Entities and entity types
An entity is a distinguishable thing in the domain being modeled. An entity type, sometimes called an entity set in teaching materials, is a category of similar things. In a library, BOOK and USER might be entity types. A particular book or a particular user is an instance of a type, not a new type.
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Attributes
An attribute is a property used to describe an entity type. A book’s title is an attribute of BOOK. Attributes can also belong to a relationship when they describe the association itself—for example, the date a particular user borrowed a particular copy.
Relationships
A relationship expresses an association among entity types. It is often named with a verb or verb phrase, such as borrows or stars-in. A relationship may connect two entity types, as a binary relationship does, or more than two when the meaning depends on several participants together.
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Constraints
A constraint states which entity instances or combinations are valid. Cardinality, also called multiplicity, says how many associations are allowed. Participation or modality says whether involvement is required or optional. These are separate questions: “at most one” does not establish that a relationship must exist.
How to read cardinality and optionality
Common cardinalities include one-to-one, one-to-many (or many-to-one when read from the opposite side), and many-to-many. Read the rule from each side rather than assuming the same wording applies in both directions. For example, in a library, one BOOK can have multiple COPY instances, while each COPY is associated with exactly one BOOK.
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State minimum participation as well as maximum cardinality when the business rule requires it. For instance, saying that a book can have many copies sets a maximum pattern but does not, by itself, say whether every book must have at least one copy. DICOM PS3.4 (2017d) includes a case in which a source entity can be associated with “zero or more” destination entities; that is a convention within that standard, not a universal diagram rule. DICOM PS3.4, section 5.1.2
A library example
A basic library model might include BOOK, COPY, and USER. The relationship between BOOK and COPY records that one book title can be represented by several physical copies, with each copy belonging to one book.
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A loan connects a user to a copy. Because details such as loan date or due date describe a particular borrowing event—not the user or copy in general—they belong to that association. If the association needs its own identity or attributes in the eventual database design, it can be modeled as an associative entity such as LOAN. The right entities and constraints come from the actual library rules, not from a diagramming convention.
ER model versus ER diagram
The ER model is the conceptual description of the data and its rules; an ER diagram is one visual representation of that description. Diagram conventions differ, so identify the notation being used and explain its marks in plain language.
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In one classical E/R convention, rectangles represent entity sets, ovals represent attributes, diamonds represent relationships, and arrows express certain multiplicity constraints. Crow’s-foot notation and other approaches use different symbols. DICOM PS3.4 (2017d), for example, says that a relationship is depicted as a diamond within that standard; this is not a universal requirement for every ER diagram. DICOM PS3.4, section 5.1.2
Where ER modeling fits in database design
ER modeling is usually an early, conceptual step in database design. It helps people who understand the domain agree on what information matters and which rules apply. The design can then be made more specific in later stages:
- Conceptual model: describes the domain’s information and rules in terms people can discuss.
- Logical model: specifies a structure for a chosen data model, such as tables, columns, keys, and connections.
- Physical model: adapts the logical design to a particular database management system, including its data types, indexes, and constraints.
The ER model therefore informs a database schema but is not the same thing as a relational database or SQL implementation.
Choosing and explaining a notation
No single notation is universal. When creating or reading an ER diagram, make the intended rules understandable to its audience:
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Quick Recap
- Name the notation or explain what its symbols mean.
- Describe both maximum cardinality and whether participation is optional or required.
- Use plain-language descriptions alongside symbols when a relationship could be read in more than one direction.
- Represent an association’s own attributes where they belong, and consider an associative entity when that association needs its own identity or structure.
- Choose entities and constraints to match the real domain, then check that the conceptual model can be translated into the intended logical design.
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