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Object Oriented Features that OWL lacks

At some level OWL seem to be very similar to UML, but there are important differences that you have to keep in mind. In this post I detail features you will have to do without coming from a coding or object orientation perspective when you start using OWL. These are:

  1. classes do not have attributes,
  2. classes do have class variables (but not in the way you think),
  3. you have to live without methods,
  4. there are no interfaces, and
  5. neither are there any abstract classes.

Classes do not have Attributes

Programmers are used to classes that have attributes or properties. This is also referred to as instance/member variables of the class. In OWL classes do not have properties. Rather, properties can be used to model relations that exist between classes and data types. You can however state that a class is a subclass of something that has some property. I.e.,

Class: Course
    hasSubject some Subject 

which states that a Course is a subclass of things that have some
Subject. I explain this here and here.

Classes do have Class Variables (but not in the way you think)

In programming class variables are values that describe the class rather than instances of the class. In OWL this is achieved trough annotations. There exist pre-defined annotation properties and you can define your own annotation properties. Interestingly annotation properties can be specified for any class, individual or axiom, as well as the ontology itself. Annotations are purely used to specify additional information and no reasoning is done over them.

There are no Methods nor Interfaces

This may seem like silly a comment, but is worth making it explicit: “OWL does not have methods”. Why not? Well, OWL is not a programming language nor a modelling language for designing software. It is a conceptual modelling language. Can you model methods in OWL? Yes, I have done it here to find software modelling heuristic violations, but it is not trivial. However, even if you can define the conceptual notion of a method, there is no way to execute methods in OWL. Again, because it is not a programming language.

What about interfaces? Well, since there are no methods in OWL, there are no interfaces either. In programming the idea is that an interface defines the signature of an interaction, usually in terms of method signatures, without specifying how the methods are actually implemented. This allows for the same interface to have different implementations.

Neither are there Abstract Classes

Abstract classes in programming are used to enable programmers to only implement a subset of the interfaces specified, thereby forcing subclasses to do the implementation. However, again since interfaces do not exist, and there are no methods, it does not make sense for OWL to support abstract classes.

What about the case where in programming an abstract class is defined that only consist of member/instance variables? In programming this has the effect that no instances of this class can be created directly. The only way an instance can be created is by creating an instance of a subclass of the abstract class. Importantly these instances created of the subclass are still instances of the abstract class. In OWL there is no way to force that individuals cannot be created of a class, but only for its subclasses. The closest to not being able to create individuals for a class is the class ‘owl:Nothing‘, but that really means the class has zero individuals, which is not what is meant by an abstract class in programming.


In this post I detailed some object oriented features programmers may feel OWL lacks. However, OWL is a conceptual modelling language with reasoning capability. Thinking about it causes one to realize it makes as little sense to say OWL lacks some object oriented feature as saying that Java or C# lacks reasoning capability.

Associations between Classes

This far we have only considered UML classes where the attributes are primitive types rather than classes. Here we will consider UML classes that have classes as attributes. Assume we want to model projects. Assume a project must have one name, one sponsor that must be a manager and it must have a team of between 3 and 10 employees. In UML this can be stated using attributes (see Fig.1(a)) or associations (see Fig. 1(b)). For interest sake Wazlawick [1] suggests using attribute notation for data types and associations for classes. His motivation is that associations makes dependencies between classes more apparent. I usually follow this guideline myself.

Fig. 1

Fig. 1

The OWL representation for these 2 class diagrams is given in Fig. 2. The first thing to notice is that we use ObjectProperty instead of DataProperty to represent the sponsor attribute/association. Similar for the team attribute/association. Our property definitions also now have Domain and Range restrictions. When we say that Susan is the sponsor for ABC, we can infer that Susan is a manager and ABC is project. This information can be captured through Domain and Range restrictions. For the purpose of finding modeling errors in it is preferable to add Domain and Range restrictions.

Association between Classes Manchester

Fig. 2

To limit the number of employees on a team to between 3 and 10 employees we use the property cardinality restrictions team min 3 owl:Thing and team max 10 owl:Thing. It may seem strange that we use team max 10 owl:Thing rather than team max 10 Employee. Surely we want to restrict team members to employees? Well true, but that is achieved through our range restriction on the team object property. Here we restricting our team to 10 whatever classes and the range restriction will infer that the team must be of type Employee.


1. R. S. Wazlawick, Object-oriented Analysis and Design for Information Systems: Modeling with UML, OCL and IFML, Morgan Kaufmann, 2014.



In this post we will look at how different types of inheritance can be translated to OWL. We consider the case where Person is specialized by Employee and Client (Fig. 1). In a UML class diagram if inheritance is not annotated the default annotation {incomplete, disjoint} is assumed. incomplete means there are instances of Person which are neither of type Employee nor Client. disjoint means there is no instance of Person that is both of type Employee and of type Client. The set representation is given in Fig. 2 and the OWL translation in Fig. 3.


Fig. 1


Fig. 2


Fig. 3

The annotation {complete, disjoint} means every instance of Person is either a instance of Employee or an instance of Client(Fig. 4). The corresponding Venn diagram is  given in Fig. 5 and the OWL translation in Fig. 6.


Fig. 4


Fig. 5


Fig. 6

When overlapping is used rather than disjoint it means an instance of Person may be both of type Employee and of type Client.  Fig. 7 – 9 provides a UML class diagram, Venn diagram and OWL translation as example for the annotation {incomplete, overlapping}. Fig. 10 – 12 provides a UML class diagram, Venn diagram and OWL translation as example for the annotation {complete, overlapping}.


Fig. 7


Fig. 8


Fig. 9


Fig. 10


Fig. 11


Fig. 12

A Brief Introduction to Protégé and Reasoners

A question you rightfully may be pondering is: Why translate object oriented classes into OWL? The answer is that it can help you to find logical inconsistencies in your class designs. In this post I will introduce the tools that will eventually enable you to find logical inconsistencies in your class designs.

The tool we will use is called Protégé. Download and installations instructions for Protégé can be found at https://protegewiki.stanford.edu/wiki/Install_Protege5.

In this post I will provide two screencasts:

  1. In the first screencast I will show you how to enter the OWL representation of the Person class introduced in the previous post.
  2. In the second screencast I will show you how to run a reasoner and how an inconsistency can arise.

On to the first screencast:

  1. Create a Person class.
  2. Create the data properties.
    1. name
    2. surname
    3. age
  3. Through sub-classing state that the Person class necessarily have a
    1. name,
    2. surname and
    3. age.
  4. If we run the reasoner on this ontology, no inconsistencies will be found.

In the second screencast I show how an inconsistency can arise. The steps are as follows:

  1. Create an individual called sarah of type Person.
  2. Run the reasoner. You will see the reasoner give no errors (nothing happened). This may come as a surprise to you since we have not set the name, surname or age data properties for the individual called sarah. In OWL this behaviour is expected due to what is called the open world assumption. OWL makes no assumption with regards to knowledge that is not stated explicitly. Since we did not state that the sarah individual does not have, for example, a name, the reasoner found no error in our ontology. This is different from typical database behaviour where absence of information is often assumed to indicate that the information does not exist, which is referred to as the closed world assumption.
  3. Now let us change our sarah individual to state that it does not have a name. This is achieved by stating that the sarah individual is of type name max 0 xsd:string. This states that the sarah individual can have a maximum of 0 name data properties of type xsd:string.
  4. If we run the reasoner now it shows that we have an inconsistency. We can ask Protégé to explain the inconsistency.ExplainSarahInconsistency
  5. The explanation states that sarah is of type Person and of type name max 0 xsd:string. But Person is a subclass of name some xsd:string. This states that individuals of type Person must have at least 1 name property of type xsd:string. Hence, the reason for the inconsistency.


Admittedly this example is contrived: there is not much sense in creating a Person class which we state must have a name and then create an individual of type Person which we then state does not have a name. But this was done here to show you how to use a reasoner to find inconsistencies in your ontology and to show you what information you can expect when your ontology is inconsistent.

Add Some More Attributes

Person with added attributes


In this post what I want to do is add some attributes to the Person class of the previous post. The important thing to understand is that as you add attributes to a class, what you are doing in effect is adding additional constraints that will cause the number of objects that can be of that type to shrink. This is illustrated in the Venn diagram below. Note that our Person class is now a subset of the intersection of the sets of objects with name as attribute, surname as attribute and age as attribute.


Person with more attributes subset


If we now consider the OWL 2 representation of this class in Manchester syntax, it matches our Venn diagram exactly. It further states that name, surname and age are properties. It states that individuals of the Person class have a name property of type xsd:string, a surname property of type xsd:string and a age property of type xsd:integer.


Add some attributes OWL

A Simple Class

A Simple Class

Let us start with a simple example. Assume we have a Person class, which models a person that has a name. Let us just think about what this means. If we think of our domain of interest and we list all the objects of the domain, some objects will belong to a set that is a subset of the domain of interest, which is called the Person set, which is represented by our Person class. Our Person class also has a name attribute of type String, but it is likely that we will have other classes in our domain that may have a name attribute of type String. Thus, the Person class represents objects that are a subset of all the objects in the domain that have a name attribute of type String. This is shown in the Venn diagram below.

Person Subset


Note that the Person class is not necessarily a strict subset of the objects that have a name attribute of type String. It is possible that the Person class is the only class in our domain that has a name attribute of type String, in which case these two sets are in fact equal.

The OWL 2 equivalent representation in Manchester syntax is given in the image below. Note that for the name attribute in the UML class we have defined a related DataProperty. Furthermore, a Person class is also defined, which is defined as SubClassOf: name some xsd:string. What this means is that individuals that belongs to the Person class also belongs to the class of individuals that have a name property of type xsd:string. Thus, the Person class is a subclass of the class representing individuals that have a name property of type xsd:string.

Person Manchester

The Correspondence between DLs/OWL and OO

The analogy between DLs and object-orientation can be observed when it is considered that the basic task in constructing an ontology is classification. Explicit subsumption relationships between concepts can be defined in the TBox. In object-orientation this can be achieved by definition of an inheritance hierarchy between classes. Classification is further solidified as the basis of DLs in that the core reasoning capabilities they provide are subsumption and instance checking. Subsumption computes a subsumption hierarchy, which essentially categorizes concepts into superconcept/subconcept relationships. Instance checking verifies whether a given individual is an instance of a specific concept [1].

In object-orientation the domain of interest is described in terms of classes that have properties, which are defined via attributes and/or associations. Classes in essence have a set-theoretic semantics, i.e. a class represents a set of objects in the domain of interest which shares attributes. Objects that are classified by a class are called instances of the class. The analogy with DLs is that classes, attributes/associations and instances (or sometimes called objects) correspond respectively with concepts, roles and individuals in DLs, which in OWL corresponds respectively to classes, properties and individuals.

This correspondence between object orientation, DLs and OWL 2 is summarized in the table below.

Object orientation DLs OWL 2
Class Concept Class
Attribute/association Role Property
Object Individual Individual


[1] F. Baader, D. Calvanese, D. L. McGuinness, D. Nardi and P. F. Patel-Schneider, The Description Logic Handbook: Theory, Implementation and Applications, Cambridge University Press, 2007.