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IB DP Computer Science Study Notes

A.2.8 Constructing Entity-Relationship Diagrams

Entity-Relationship Diagrams (ERDs) provide a detailed and structured visual representation of the data requirements for a system. They form a critical part of the database design process, particularly in the context of relational databases where clear definitions of entities, attributes, and relationships are crucial for efficient storage and retrieval of data.

Understanding Entity-Relationship Diagrams

ERDs are essential tools for data modelling, designed to capture the types of information that are to be stored in a database, the relationships among these pieces of information, and the cardinality and optionality of these relationships.

Components of ERDs

  • Entities: Represent real-world objects or concepts, depicted as rectangles and named with singular nouns to capture the essence of the things of interest in the system.
  • Attributes: Characteristics or properties of entities, illustrated by ovals. Attributes provide necessary details about the entities and are connected to them by lines.
  • Relationships: Diamonds that graphically represent how two entities share information in the database. These can be named with active verbs to depict the nature of the association.

Entity Sets and Relationship Sets

  • Entity Sets: Groups of entities that share the same properties, or attributes, such as a set of all students or a set of all courses.
  • Relationship Sets: Collections of similar relationships, wherein each relationship set involves the same number of participating entity sets with the same relationship types.

Techniques for Constructing ERDs

Constructing an ERD requires a methodical approach, starting from requirements gathering to the detailed design.

Identifying Entities and Attributes

  • Carefully analyse the scenario to list potential entities and their associated attributes, considering the purpose and scope of the database.

Defining Relationships

  • Determine the type of relationship (one-to-one, one-to-many, or many-to-many) by examining how entities relate to each other in the scenario. This step is crucial to ensure the ERD reflects accurate connectivity.

Applying Third Normal Form (3NF)

  • To ensure that the ERD is in 3NF, check for redundancy and dependencies. Each attribute must depend only on the primary key and not on other non-key attributes.

Steps in Constructing ERDs

Step 1: Requirements Gathering

  • Begin with an extensive requirements gathering process. This involves understanding the information needs of the system from all stakeholders.

Step 2: Identify Entities

  • After gathering requirements, identify the key entities of the system. These should be substantial elements that have relevance to the database's context.

Step 3: Identify Relationships

  • Analyse the interactions between entities. Each relationship should define how entities are related and how they interact within the system.

Step 4: Identify Attributes

  • Pinpoint the information that needs to be stored about each entity. Ensure that these attributes are sufficient to describe the entity fully.

Step 5: Determine Primary Keys

  • For each entity, determine the primary key that uniquely identifies each instance of the entity. This is a critical step in avoiding data redundancy.

Step 6: Draw the Diagram

  • With entities, attributes, and relationships defined, begin drawing the ERD. Start with entities, connect attributes, and establish relationships with appropriate symbols.

Step 7: Validate with Stakeholders

  • Validation involves checking the ERD against requirements and with stakeholders to ensure that it accurately represents the needed data structure.

Step 8: Apply Normalisation Rules

  • Review the diagram to ensure that the entities and relationships conform to the rules of 3NF to ensure the database's integrity and efficiency.

Representing Specific Scenarios in ERDs

Scenario Interpretation

  • Scenarios must be interpreted with a critical eye, determining the underlying structure of the data that needs to be represented in the database.

Scenario Representation

  • Transform the narrative scenario into a structured representation, ensuring that all identified entities, attributes, and relationships are included.

Scenarios and Normalisation

  • Scenarios often contain implicit redundancies that must be resolved by applying normalisation principles to ensure the database is optimised.

Common Mistakes and Considerations

Avoiding Redundancy

  • Avoid duplicating data across multiple entities. This requires a careful analysis to ensure that each piece of data is stored only once.

Ensuring Flexibility

  • Design ERDs with an eye toward future modifications. Systems often evolve, and the database should be capable of adapting to these changes without a complete redesign.

Consistency and Clarity

  • Maintain a uniform naming convention and clear labels throughout the ERD. This practice increases the diagram’s readability and understandability.

Practical Tips for ERD Construction

Software Tools

  • Choose ERD software that provides features for automatic consistency checks, as this can greatly facilitate the design process.

Sketching Drafts

  • Drafting preliminary sketches allows for exploration and refinement of ideas before settling on a final ERD.

Collaboration and Feedback

  • Collaborate with others to gain various perspectives, and solicit feedback to refine the ERD further.

Incremental Design

  • Approach ERD construction incrementally, building and validating pieces of the diagram progressively to ensure accuracy.

Constructing ERDs is an iterative and skill-based process that requires regular practice. These notes aim to facilitate the construction of ERDs that are not only accurate but also conform to 3NF for relational databases, ensuring that the data structure is optimised for both integrity and performance. Engaging with different scenarios and incorporating feedback are essential to mastering the creation of effective ERDs.


Recursive relationships occur when an entity has a relationship with itself. For instance, in an organisational chart, an 'Employee' might be supervised by another 'Employee'. To indicate a recursive relationship in an ERD, you draw a relationship line directly from the entity back to itself. This relationship is often annotated with roles to clarify the nature of the relationship, such as 'supervises' and 'is supervised by'. When dealing with recursive relationships, it is important to clearly define the rules and constraints of the relationship to avoid confusion and ensure data integrity.

Weak entities are a type of entity that cannot be uniquely identified by their attributes alone. They require a foreign key in addition to their attributes to form a primary key, usually because they have a dependency on another, stronger entity. To identify a weak entity, look for an entity that has a total participation (existence dependency) on its parent entity. In an ERD, weak entities are typically represented with a double rectangle and connected to their owning entity with a double diamond relationship symbol. Their primary key is a combination of their own unique attribute(s) and the primary key of the owning entity.

Denormalisation is the process of strategically introducing redundancy into a database design to improve performance, often at the expense of some loss in data integrity. You would consider denormalisation in scenarios where performance requirements outweigh the strict need for normalisation, such as when dealing with large volumes of data that need to be accessed quickly. However, this comes with consequences: it can lead to data anomalies, increase the complexity of database maintenance, and make the update processes more cumbersome. Denormalisation should be undertaken with caution and only when the benefits significantly outweigh the potential drawbacks.

Associative entities, also known as junction tables or bridge tables, are used in an ERD when you have a many-to-many (M:N) relationship between two entities. They serve to break down this complex relationship into two one-to-many (1:M) relationships, which are easier to represent and manage in a relational database. An associative entity contains the primary keys from each of the two entities it connects, which together form its composite primary key. It is used when additional information about the association needs to be stored. For example, in a 'Students' and 'Classes' M:N relationship, an associative entity 'Enrollment' might include attributes like 'EnrollmentDate' and 'FinalGrade'.

Cardinality refers to the number of elements in one entity that can be associated with the number of elements in another entity. To determine the cardinality of a relationship, you must analyse the business rules or the nature of the interactions between the entities. For example, if an entity 'Student' enrolls in 'Courses', you must ask, can a student enroll in multiple courses? Can a course have multiple students? The answers define the cardinality, which could be one-to-one, one-to-many, or many-to-many. The cardinality is then visually represented on the ERD using standard notation, such as a line ending with a crow's foot to indicate 'many', or a single line for 'one'.

Practice Questions

Given a scenario where a library system requires tracking of books, members, and loans, construct a simplified ERD that includes at least three entities, their relevant attributes, and the relationships between them. Ensure your ERD reflects the 3NF.

Book, Member, and Loan. The Book entity would have attributes such as ISBN, Title, Author, and Genre, with ISBN being the primary key to ensure uniqueness. The Member entity would include MemberID, Name, Address, and ContactNumber, with MemberID as the primary key. The Loan entity would link books and members, with attributes including LoanID, ISBN (foreign key), MemberID (foreign key), LoanDate, and ReturnDate. LoanID would be the primary key. The relationships between Book and Loan would be one-to-many, as a book can have multiple loans, and between Member and Loan, also one-to-many, as a member can have multiple loans. This ERD avoids redundancy and ensures that all attributes are dependent only on their respective primary keys, complying with 3NF.

Describe the process of transforming a given scenario into an ERD that adheres to 3NF. Explain the steps involved and the considerations you must take to ensure the resulting ERD is normalised and reflects the scenario accurately.

Transforming a scenario into a 3NF-compliant ERD involves several steps. Firstly, we identify the entities represented in the scenario and then define their attributes, ensuring there are no multivalued attributes to comply with 1NF. Next, we establish relationships between these entities, determining the cardinality and ensuring that there are no partial dependencies, which satisfies 2NF. We then review the ERD for transitive dependencies to meet 3NF criteria, meaning no attribute is dependent on another non-primary attribute. It is essential to iterate over the design, verifying at each step that the entities and their relationships are modelled correctly and reflect the scenario. The final ERD should depict all entities, attributes, and relationships without redundancy, and every non-key attribute should be fully functionally dependent on the primary key of its entity.

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Written by: Alfie
Cambridge University - BA Maths

A Cambridge alumnus, Alfie is a qualified teacher, and specialises creating educational materials for Computer Science for high school students.

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