Entity Relationship Diagram An entity-relationship diagram or model is a data modeling tool that allows representing the relevant entities of an information system as well as their interrelationships and properties.
In a Relationship Entity Diagram concepts such as diagram, relationship entity, relationship entity model, rentity, attribute, relationship, set of relationships, restrictions, correspondence of cardinalities, participation restrictions, representation of the object of study in the world of data are defined , obtaining the entity relationship diagram, components and entity relationship diagram, steps to follow for the entity relationship diagram and operations on graphic objects of the Entity Relationship diagram.
Summary
[ hide ]
- 1 Entity Relationship Diagram
- 2 The Entity-Relationship Model
- 3 Theoretical and Conceptual Basis
- 1 Entity
- 2 Attributes
- 3 Relationship
- 4 Relationship set
- 4 Restrictions
- 5 Correspondence of cardinalities
- 1 Participation restrictions
- 2 Keys
- 6 Entity-relationship diagram
- 1 Entity
- 2 Attribute
- 3 Relationships
- 7 Representation of the Study Object in the Data World
- 8 Source
Entity relationship diagram
Denominated by its initials as ER . This model represents reality through a graphic scheme using the terminology of Entities, which are objects that exist and are the main elements that are identified in the problem to be solved with the diagram and are distinguished from others by their particular characteristics called Attributes .
The link that governs the union of the entities is represented by the relationship of the model. In a DER, each entity is represented by a rectangle, each relationship by a rhombus and each domain (set where the attribute takes values) by a circle.
Entities with relationships are connected by lines, just like entities with domains, representing attributes.
Key Attributes are represented by underlining the corresponding set of values. Sometimes an entity cannot be identified solely by the value of its own attributes. In these cases, relationships with attributes are used together to achieve the required unique identification. These entities are called weak entities and are represented in the DER with a double rectangle.
The MER restricts the relationships to be used to identify weak entities to binary relationships of type 1: N. Thus, for example, an occurrence of “worker” can have N associated “person-dependent” occurrences, where in addition, the existence of occurrences in the second entity depends on the existence of a corresponding occurrence in the first entity.
For example, in the model there will be people dependent on a worker only if that worker exists. To indicate this dependence on existence, a bolt is used in the DER.
The key of a weak entity is formed by combining the key of the regular entity that determines it with some other attribute that uniquely defines each weak entity associated with a given regular entity. (An entity is called a regular if it is not weak.) In a relationship, the key is the combination of the keys of all associated entities.
For each relationship, its type is determined (simple or complex) and the type of correspondence is written in the DER. For example, a company may have several (n) associated workers and a worker belongs to a single company (1).
In the Worker-Machine-Part relationship, a worker can work on n machines, producing p parts, or a part can be produced by m workers on n machines. Here, m, n and p do not identify a specific number, but only the type of correspondence established in the relation.
The Entity-Relationship Model
- The entity-relationship diagram (or diagrams) is prepared.
2. The model is completed with lists of attributes and a description of other restrictions that cannot be reflected in the diagram.
Given the rudimentary nature of this technique, some training and experience are required to achieve good data models.
Data modeling does not end with the use of this technique.
Other techniques are necessary to achieve a model that can be directly implemented in a database. Briefly:
Transformation of multiple relationships into binary.
Normalization of a relationship database (some relationships can be transformed into attributes and vice versa).
Conversion into tables (in case of using a relational database).
Theoretical and Conceptual Basis
The entity-relationship model is based on the concepts described below to represent a real-life model.
Entity
An entity is an object that exists and is distinguished from other objects according to its characteristics called Attributes . The entities can be concrete or abstract as a person as a date. Represents a “thing” or “object” of the real world with independent existence, that is, it is univocally different from any other object or thing, even being of the same type, or the same entity.
Some examples:
- A person. (It differs from any other person, even being twins).
- A car. (Although they are of the same brand, the same model, …, they will have different attributes, for example, the frame number).
- One house (Although it is exactly the same as another, it will still differ in its direction).
An entity can be an object with physical existence such as: a person, an animal, a house, etc. (concrete entity), or an object with conceptual existence such as: a job, a class assignment, a name, etc. (abstract entity).
An entity is described and represented by its characteristics or attributes. For example, the Person entity can carry with it the characteristics: Name, Surname, Gender, Height, Weight, Date of birth, etc …
Attributes
Attributes are the properties that describe each entity in a set of entities.
A set of entities within an entity, has specific values assigned for each of its attributes, thus, its unique identification is possible.
Examples:
To the collection of entities Students, with the following set of attributes in common, (id, name, age, semester), the entities belong:
(1, Sofia, 18 years old, 2)
(2, Josefa, 19 years old, 5)
(3, Gabriela, 20 years old, 2)
Each of the entities belonging to this set differs from the others by the value of their attributes. Note that two or more different entities can have the same values for some of their attributes, but never for all.
In particular, identifying attributes are those that make it possible to differentiate one instance of the entity from another. For example, the identifying attribute that distinguishes one student from another is their id number.
For each attribute, there is a domain of it, this refers to the type of data that will be stored or to restrictions on the values that the attribute can take (Character strings, numbers, only two letters, only numbers greater than zero, only integers …).
When an entity does not have a value for a given attribute, it takes the null value, either it is not known, it does not exist or nothing is known about it.
Relationship
Relationship: A relationship is an association or mathematical relationship between various Entities. Relationships are also named. They are represented in the Diagram_Entity_Relation, also represented by ER using arrows and diamonds. Each entity intervenes in a relationship with a certain cardinality.
The cardinality (number of instances or elements of an entity that can be associated with an element of the other related entity) is represented by a data pair, in lowercase, of the form (minimum cardinality, maximum cardinality), associated with each of the entities involved in the relationship. The following cardinalities are possible: (0,1), (1,1), (0, n), (1, n), (m, n). The maximum cardinalities with which the entities intervene in the relationship are also reported. ER Diagrams are graphical languages to describe concepts. Informally, they are simple Drawings or Graphicsthat describe the information that an information system treats and the Software that automates it. The type of relationship is defined by taking the maximums of the cardinalities involved in the relationship.
Relationship set
It consists of a collection, or set, of relationships of the same nature.
Restrictions
They are rules that must keep the data stored in the database. They should not be broken unless you have another one-to-many table relationship.
Cardinality correspondence
Given a set of relationships involving two or more sets of entities, the cardinality mapping indicates the number of entities to which a given entity may be related.
One by one (1: 1). In a one-to-one relationship, each record in Table A can only have one matching record in Table B and vice versa.
This type of relationship is not usual, since most of the information related in this way would be in a single table. You can use the one-to-one relationship to split a table with many fields, to isolate part of a table for security reasons, or to store information that only applies to a subset of the main table.
For example, you can create a table that records employees participating in a charity soccer game. Each Soccer player in the Soccer Players table has a matching record in the Employees table.
Example: Nation and Capital
One-to-many (1: N). The one-to-many relationship is the most common type of relationship. In this type of relationship, a record in Table A can have many matching records in Table B, but a record in Table B only has one matching record in Table A. Example: customer and orders. Many to One : An entity in A relates exclusively to an entity in B. But an entity in B can relate to 0 or many entities in A. Many to many(N: N). In a many-to-many relationship, a record in Table A can have many matching records in Table B, and vice versa. This type of relationship is only possible if you define a third table (called a join table) whose primary key (Primary key: one or more fields (columns) whose values uniquely identify each record in a table. A primary key cannot Allow Null values and must always have a unique index.
Participation restrictions
Given a set of relations R in which a set of entities A participates, said participation can be of two types:
- Total: When each entity in A participates in at least one relationship of R.
- Partial: When at least one entity in A does NOT participate in any relationship of R.
Keys
It is a subset of the set of common attributes in a collection of entities, which makes it possible to uniquely identify each of the entities belonging to said collection. They also allow the relationships of a set of relationships to be distinguished from one another.
Within the entity sets there are the following types of keys:
- Superkey: It is a subset of attributes that allows to distinguish univocally each one of the entities of a set of entities. If an attribute is added to the previous subset, the result will still be a superkey. * Candidate key : Given a superkey, if it ceases to be so by removing only one of the attributes that make it up, then this is a candidate key. * Primary key : It is a candidate key, chosen by the designer of the database, to uniquely identify the entities in a set of entities.
The values of the attributes of a key cannot all be the same for two or more entities.
In order to univocally distinguish the relations in a set of R relations, two cases must be considered:
- R has NO associated attributes: In this case, the union of the primary keys of all participating entity sets is used as the primary key of R. * R has associated attributes : In this case, the union of the associated attributes and the primary keys of all the sets of participating entities is used as the primary key of R. If the set of relations, R, on which the primary key is to be determined is made up of binary relations, with the sets of participating entities A and B, the following cases are considered, according to their cardinalities: * R is many to one from A to B then only the primary key of A is taken, as the primary key of R. * R is one to many from A to Bthen only the primary key of B is taken, as the primary key of R. * R is one to one from A to B then either of the two primary keys is taken, as the primary key of R. * R is many to many from A to B then the union of the attributes that make up the primary keys of A and B is taken as the primary key of R.
Entity relationship diagram
ER diagrams are a graphical language to describe concepts. Informally, they are simple drawings or graphics that describe information that an information system handles and the software that automates it.
Entity
Entities are the foundation of the entity relationship model. We can adopt as an entity definition anything or part of the world that is distinguishable from the rest. For example, in a banking system, people and bank accounts could be interpreted as entities. Entities can represent specific entities, such as a person or a plane, or abstract entities, such as a loan or a reservation.
Attribute
They are represented by a circle or ellipse labeled by a name inside. When an attribute is identifying the entity, this tag is usually underlined.
Relations
It is represented by a rhombus labeled inside with a verb. This rhombus must be joined by lines with the entities (rectangles) that it relates. Attributes are not usually represented on an entity-relationship diagram for readability, but are described verbatim in other accompanying documents.
Representation of the Study Object in the Data World
- Entities.
- Entities Attributes.
- Key attribute.
- Relations between the Entities.
- Graphic model of the Entities and their Relationships. (Entity relationship diagram)
- Logical Data Model.
Obtaining the Entity Relationship Diagram
Components and ER Diagram Regular Entity : A strong Entity (also known as a regular entity is one that can be uniquely identified. In cases where it is required, a strong entity can be “lent” some of its Attributes to an entity weak so that the latter can be identified.
Weak entity : It is one that cannot exist without participating in the relationship, that is, one that cannot be uniquely identified only by its attributes as Key. Relationships: The relationship between the entities. Each entity is entered in a Feature Set . A set of entities within an entity, has specific values assigned for each of its attributes, thus, its unique identification is possible.
Examples:
To the collection of entities Students, with the following set of attributes in common, (id, name, age, semester), the entities belong: (1, Sofia, 18 years old, 2) (2, Josefa, 19 years old, 5) (3, Gabriela, 20 years old, 2. Connector: Separator A Primary Key is used to relate a table to foreign keys from other tables.) It consists of two fields: Foreign Keys Foreign Key: one or more table fields (columns) that refer to the primary key field or fields of another table. A foreign key indicates how the tables are related.) Of Tables A and B. A Many-to-many relationship is but two One-to-many relationships with a third table. For example, the Orders table and the Products table have a Many-to-Many relationship that is defined by creating two One-to-Many relationships with the Order Details table. An order can include many products, and each product can appear in many orders. Example: people and houses.
Steps to follow for the Entity Relationship Diagram
- An entity is related to another entity with a continuous line, since it does not have arrows, it is only a continuous direction. 2. Every relationship must have a cardinality (determines the level of cardinality). 3. A relationship between two entities is always going to be given by means of a rhombus (if you have a student entity, another subject, draw a line in the middle of the line you put a rhombus, inside the rhombus you put “the student is enrolled “, the level would be one to many since the student enrolls in various subjects). 4. Each entity must have its elements.
Operations on graphical objects of the Entity Relationship diagram
Generalization / Specialization : It allows to form a new entity, through the union of other entities. The reverse process is called specialization.
Aggregation: It allows to form a new entity, based on a relationship.
Grouping : Defines a new entity, where each occurrence is a group of occurrences of the source entity.
Generalization and specialization is the result of the union of 2 or more (low-level) entity sets to produce a higher-level entity set. Generalization is used to highlight the similarities between lower-level entity types and to hide their differences. The generalization consists of identifying all those equal attributes of a set of entities to form a global entity (ies) with such similar attributes, said global entity (ies) will remain at a higher level than the origin entities. . The aggregation arises from the limitation that exists in the modeling of ER, by not allowing to express the relations between relations of an ER model in the case that a relation X wants to unite with any entity to form another relation.
Entity Relationship Diagram An entity-relationship diagram or model is a data modeling tool that allows representing the relevant entities of an information system as well as their interrelationships and properties.
In a Relationship Entity Diagram concepts such as diagram, relationship entity, relationship entity model, rentity, attribute, relationship, set of relationships, restrictions, correspondence of cardinalities, participation restrictions, representation of the object of study in the world of data are defined , obtaining the entity relationship diagram, components and entity relationship diagram, steps to follow for the entity relationship diagram and operations on graphic objects of the Entity Relationship diagram.
Summary
[ hide ]
- 1 Entity Relationship Diagram
- 2 The Entity-Relationship Model
- 3 Theoretical and Conceptual Basis
- 1 Entity
- 2 Attributes
- 3 Relationship
- 4 Relationship set
- 4 Restrictions
- 5 Correspondence of cardinalities
- 1 Participation restrictions
- 2 Keys
- 6 Entity-relationship diagram
- 1 Entity
- 2 Attribute
- 3 Relationships
- 7 Representation of the Study Object in the Data World
- 8 Source
Entity relationship diagram
Denominated by its initials as ER . This model represents reality through a graphic scheme using the terminology of Entities, which are objects that exist and are the main elements that are identified in the problem to be solved with the diagram and are distinguished from others by their particular characteristics called Attributes .
The link that governs the union of the entities is represented by the relationship of the model. In a DER, each entity is represented by a rectangle, each relationship by a rhombus and each domain (set where the attribute takes values) by a circle.
Entities with relationships are connected by lines, just like entities with domains, representing attributes.
Key Attributes are represented by underlining the corresponding set of values. Sometimes an entity cannot be identified solely by the value of its own attributes. In these cases, relationships with attributes are used together to achieve the required unique identification. These entities are called weak entities and are represented in the DER with a double rectangle.
The MER restricts the relationships to be used to identify weak entities to binary relationships of type 1: N. Thus, for example, an occurrence of “worker” can have N associated “person-dependent” occurrences, where in addition, the existence of occurrences in the second entity depends on the existence of a corresponding occurrence in the first entity.
For example, in the model there will be people dependent on a worker only if that worker exists. To indicate this dependence on existence, a bolt is used in the DER.
The key of a weak entity is formed by combining the key of the regular entity that determines it with some other attribute that uniquely defines each weak entity associated with a given regular entity. (An entity is called a regular if it is not weak.) In a relationship, the key is the combination of the keys of all associated entities.
For each relationship, its type is determined (simple or complex) and the type of correspondence is written in the DER. For example, a company may have several (n) associated workers and a worker belongs to a single company (1).
In the Worker-Machine-Part relationship, a worker can work on n machines, producing p parts, or a part can be produced by m workers on n machines. Here, m, n and p do not identify a specific number, but only the type of correspondence established in the relation.
The Entity-Relationship Model
- The entity-relationship diagram (or diagrams) is prepared.
2. The model is completed with lists of attributes and a description of other restrictions that cannot be reflected in the diagram.
Given the rudimentary nature of this technique, some training and experience are required to achieve good data models.
Data modeling does not end with the use of this technique.
Other techniques are necessary to achieve a model that can be directly implemented in a database. Briefly:
Transformation of multiple relationships into binary.
Normalization of a relationship database (some relationships can be transformed into attributes and vice versa).
Conversion into tables (in case of using a relational database).
Theoretical and Conceptual Basis
The entity-relationship model is based on the concepts described below to represent a real-life model.
Entity
An entity is an object that exists and is distinguished from other objects according to its characteristics called Attributes . The entities can be concrete or abstract as a person as a date. Represents a “thing” or “object” of the real world with independent existence, that is, it is univocally different from any other object or thing, even being of the same type, or the same entity.
Some examples:
- A person. (It differs from any other person, even being twins).
- A car. (Although they are of the same brand, the same model, …, they will have different attributes, for example, the frame number).
- One house (Although it is exactly the same as another, it will still differ in its direction).
An entity can be an object with physical existence such as: a person, an animal, a house, etc. (concrete entity), or an object with conceptual existence such as: a job, a class assignment, a name, etc. (abstract entity).
An entity is described and represented by its characteristics or attributes. For example, the Person entity can carry with it the characteristics: Name, Surname, Gender, Height, Weight, Date of birth, etc …
Attributes
Attributes are the properties that describe each entity in a set of entities.
A set of entities within an entity, has specific values assigned for each of its attributes, thus, its unique identification is possible.
Examples:
To the collection of entities Students, with the following set of attributes in common, (id, name, age, semester), the entities belong:
(1, Sofia, 18 years old, 2)
(2, Josefa, 19 years old, 5)
(3, Gabriela, 20 years old, 2)
Each of the entities belonging to this set differs from the others by the value of their attributes. Note that two or more different entities can have the same values for some of their attributes, but never for all.
In particular, identifying attributes are those that make it possible to differentiate one instance of the entity from another. For example, the identifying attribute that distinguishes one student from another is their id number.
For each attribute, there is a domain of it, this refers to the type of data that will be stored or to restrictions on the values that the attribute can take (Character strings, numbers, only two letters, only numbers greater than zero, only integers …).
When an entity does not have a value for a given attribute, it takes the null value, either it is not known, it does not exist or nothing is known about it.
Relationship
Relationship: A relationship is an association or mathematical relationship between various Entities. Relationships are also named. They are represented in the Diagram_Entity_Relation, also represented by ER using arrows and diamonds. Each entity intervenes in a relationship with a certain cardinality.
The cardinality (number of instances or elements of an entity that can be associated with an element of the other related entity) is represented by a data pair, in lowercase, of the form (minimum cardinality, maximum cardinality), associated with each of the entities involved in the relationship. The following cardinalities are possible: (0,1), (1,1), (0, n), (1, n), (m, n). The maximum cardinalities with which the entities intervene in the relationship are also reported. ER Diagrams are graphical languages to describe concepts. Informally, they are simple Drawings or Graphicsthat describe the information that an information system treats and the Software that automates it. The type of relationship is defined by taking the maximums of the cardinalities involved in the relationship.
Relationship set
It consists of a collection, or set, of relationships of the same nature.
Restrictions
They are rules that must keep the data stored in the database. They should not be broken unless you have another one-to-many table relationship.
Cardinality correspondence
Given a set of relationships involving two or more sets of entities, the cardinality mapping indicates the number of entities to which a given entity may be related.
One by one (1: 1). In a one-to-one relationship, each record in Table A can only have one matching record in Table B and vice versa.
This type of relationship is not usual, since most of the information related in this way would be in a single table. You can use the one-to-one relationship to split a table with many fields, to isolate part of a table for security reasons, or to store information that only applies to a subset of the main table.
For example, you can create a table that records employees participating in a charity soccer game. Each Soccer player in the Soccer Players table has a matching record in the Employees table.
Example: Nation and Capital
One-to-many (1: N). The one-to-many relationship is the most common type of relationship. In this type of relationship, a record in Table A can have many matching records in Table B, but a record in Table B only has one matching record in Table A. Example: customer and orders. Many to One : An entity in A relates exclusively to an entity in B. But an entity in B can relate to 0 or many entities in A. Many to many(N: N). In a many-to-many relationship, a record in Table A can have many matching records in Table B, and vice versa. This type of relationship is only possible if you define a third table (called a join table) whose primary key (Primary key: one or more fields (columns) whose values uniquely identify each record in a table. A primary key cannot Allow Null values and must always have a unique index.
Participation restrictions
Given a set of relations R in which a set of entities A participates, said participation can be of two types:
- Total: When each entity in A participates in at least one relationship of R.
- Partial: When at least one entity in A does NOT participate in any relationship of R.
Keys
It is a subset of the set of common attributes in a collection of entities, which makes it possible to uniquely identify each of the entities belonging to said collection. They also allow the relationships of a set of relationships to be distinguished from one another.
Within the entity sets there are the following types of keys:
- Superkey: It is a subset of attributes that allows to distinguish univocally each one of the entities of a set of entities. If an attribute is added to the previous subset, the result will still be a superkey. * Candidate key : Given a superkey, if it ceases to be so by removing only one of the attributes that make it up, then this is a candidate key. * Primary key : It is a candidate key, chosen by the designer of the database, to uniquely identify the entities in a set of entities.
The values of the attributes of a key cannot all be the same for two or more entities.
In order to univocally distinguish the relations in a set of R relations, two cases must be considered:
- R has NO associated attributes: In this case, the union of the primary keys of all participating entity sets is used as the primary key of R. * R has associated attributes : In this case, the union of the associated attributes and the primary keys of all the sets of participating entities is used as the primary key of R. If the set of relations, R, on which the primary key is to be determined is made up of binary relations, with the sets of participating entities A and B, the following cases are considered, according to their cardinalities: * R is many to one from A to B then only the primary key of A is taken, as the primary key of R. * R is one to many from A to Bthen only the primary key of B is taken, as the primary key of R. * R is one to one from A to B then either of the two primary keys is taken, as the primary key of R. * R is many to many from A to B then the union of the attributes that make up the primary keys of A and B is taken as the primary key of R.
Entity relationship diagram
ER diagrams are a graphical language to describe concepts. Informally, they are simple drawings or graphics that describe information that an information system handles and the software that automates it.
Entity
Entities are the foundation of the entity relationship model. We can adopt as an entity definition anything or part of the world that is distinguishable from the rest. For example, in a banking system, people and bank accounts could be interpreted as entities. Entities can represent specific entities, such as a person or a plane, or abstract entities, such as a loan or a reservation.
Attribute
They are represented by a circle or ellipse labeled by a name inside. When an attribute is identifying the entity, this tag is usually underlined.
Relations
It is represented by a rhombus labeled inside with a verb. This rhombus must be joined by lines with the entities (rectangles) that it relates. Attributes are not usually represented on an entity-relationship diagram for readability, but are described verbatim in other accompanying documents.
Representation of the Study Object in the Data World
- Entities.
- Entities Attributes.
- Key attribute.
- Relations between the Entities.
- Graphic model of the Entities and their Relationships. (Entity relationship diagram)
- Logical Data Model.
Obtaining the Entity Relationship Diagram
Components and ER Diagram Regular Entity : A strong Entity (also known as a regular entity is one that can be uniquely identified. In cases where it is required, a strong entity can be “lent” some of its Attributes to an entity weak so that the latter can be identified.
Weak entity : It is one that cannot exist without participating in the relationship, that is, one that cannot be uniquely identified only by its attributes as Key. Relationships: The relationship between the entities. Each entity is entered in a Feature Set . A set of entities within an entity, has specific values assigned for each of its attributes, thus, its unique identification is possible.
Examples:
To the collection of entities Students, with the following set of attributes in common, (id, name, age, semester), the entities belong: (1, Sofia, 18 years old, 2) (2, Josefa, 19 years old, 5) (3, Gabriela, 20 years old, 2. Connector: Separator A Primary Key is used to relate a table to foreign keys from other tables.) It consists of two fields: Foreign Keys Foreign Key: one or more table fields (columns) that refer to the primary key field or fields of another table. A foreign key indicates how the tables are related.) Of Tables A and B. A Many-to-many relationship is but two One-to-many relationships with a third table. For example, the Orders table and the Products table have a Many-to-Many relationship that is defined by creating two One-to-Many relationships with the Order Details table. An order can include many products, and each product can appear in many orders. Example: people and houses.
Steps to follow for the Entity Relationship Diagram
- An entity is related to another entity with a continuous line, since it does not have arrows, it is only a continuous direction. 2. Every relationship must have a cardinality (determines the level of cardinality). 3. A relationship between two entities is always going to be given by means of a rhombus (if you have a student entity, another subject, draw a line in the middle of the line you put a rhombus, inside the rhombus you put “the student is enrolled “, the level would be one to many since the student enrolls in various subjects). 4. Each entity must have its elements.
Operations on graphical objects of the Entity Relationship diagram
Generalization / Specialization : It allows to form a new entity, through the union of other entities. The reverse process is called specialization.
Aggregation: It allows to form a new entity, based on a relationship.
Grouping : Defines a new entity, where each occurrence is a group of occurrences of the source entity.
Generalization and specialization is the result of the union of 2 or more (low-level) entity sets to produce a higher-level entity set. Generalization is used to highlight the similarities between lower-level entity types and to hide their differences. The generalization consists of identifying all those equal attributes of a set of entities to form a global entity (ies) with such similar attributes, said global entity (ies) will remain at a higher level than the origin entities. . The aggregation arises from the limitation that exists in the modeling of ER, by not allowing to express the relations between relations of an ER model in the case that a relation X wants to unite with any entity to form another relation.
