In the last post I introduced the RDF Model to define assertions as triple statements. But how does a stupid machine understand what a certain property describing a certain resource means?
The RDF Model provides only a mechanism to describe data as statements, but it can say nothing about the content of the assertion and the properties used in triples. It is clear that something is missing, and here is where the RDF Schema (RDFs) comes into play.
The RDF Schema (RDFs) is the way to describe the meaning of classes and properties to help machines process data efficiently. RDFs Vocabulary extends RDF model to provide primitives to write light schemas for RDF triples allowing describing taxonomies of classes and properties to create and define what is called the ontology of the domain of interest. RDFS provides some constructs to organize classes in a hierarchy providing mechanisms to extend them in subclasses and to create new schemas through incremental changes. The meaning of each resource is expressed through the reference to a specific vocabulary.
Using the RDFS Vocabulary, we can define for example the class Person
and the class Book to define the http://example.org/mfowler
resource
as an instance of the class Person, and the http://example.org/umld
resource as an instance of the class Book.
So, we can define the http://example.org/hasAuthor
resource as a
new property stating that it relates an instance of Book to an instance
of Person.
One of the interesting features of RDF Schema is the simplicity with
which it can be extended by the namespace mechanism. Not only can
we use different RDF Schema vocabularies, but we can also extend a
standard version without the need of redefining all concepts.
The most important RDFS items to define metadata schemas or ontologies are:
- rdfs:Resource: it is the class of everything. All things described by RDF are resources, instance of rdfs:Resource.
- rdfs:Class: the Class resource is one of the most important RDFS
vocabulary constructs because it allows to create new classes, as a
category or a model, of anything concrete or abstract. It is importan
to note the reflexive nature of this resource; instancing a new
class using the
rdf:type
property, the rdfs:Class instances obtained are themselves class objects, then again classes to instantiate. - rdfs:Property: this resource is used to instantiate a new property or a new property subclass. Again, also this one, is a rdfs:Resource subclass.
- rdfs:Literal: an rdfs:Literal is an rdfs:Resource subclass and represents a typed primitive value borrow from XML Schema Datatypes (string, date, float, etc.)
- rdf:type: the property is used to say that a certain resource, instance
of rdfs:Resource is an instance of a certain class. If it is
present in the statement predicate, the object resource must be
an
rdfs:Class
resource or anrdfs:Class
instance. In the first case the subject resource will be a new class type, otherwise it will be a generic typed class instance. -
rdfs:subClassOf: the property rdfs:subClassOf is an instance of rdf:Property and it is used to state that all the instances of one class are instances of another. A triple of the form:
C1 rdfs:subClassOf C2
states that C1 is an instance of
rdfs:Class
, C2 is an instance ofrdfs:Class
and C1 is a subclass of C2. The resource specifies the inheritance relationship between classes and can be a subclass of one or more classes (multiple inheritance). - rdfs:domain: used to say that a certain resource, instance of
rdfs:Property
has domain instances of a certain class. For example, the property identified by thehttp://example.org/hasAuthor
URI, instance ofrdfs:Property
, has to have as subject type the Book class. - rdfs:range: used to say that a certain resource, instance of
rdfs:Property
, has as range instances of a certain class. For example, the property identified by thehttp://example.org/hasAuthor
URI, instance ofrdfs:Property
, has to have as object type the Person class.
The following figure represents the relationship graph of the most important RDFS classes:
Let us now see how to apply what we have just described in our previous
statement. At the beginning we define two new classes: ex:Book
and ex:Person
instances of the rdfs:Class
resource. Then, we can typify
the ex:umld
and the ex:mfowler
resources, through the
rdf:type
property. As done with classes, we instanciate the property
resources (ex:authorOf
, ex:firstname
, ex:lastname
, ex:title
, ex:isbn
) as
rdfs:Property
instances, using again the rdf:type
property. Also, we
can describe some relations between properties, for example, establishing
the domain and the range for the authorOf property. For example,
we can explicit the authorOf property that must join instances of Book
with instances of Person, and so forth.
Let us show now RDFS Schema serialization. For semplicity I will adopt the N3 notation
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>.
@prefix ex: <http://example.org/>.
ex:Book rdf:type rdfs:Class.
ex:Person rdf:type rdfs:Class.
ex:fistname rdf:type rdfs:Property.
ex:lastname rdf:type rdfs:Property.
ex:title rdf:type rdfs:Property.
ex:isbn rdf:type rdfs:Property.
ex:hasAuthor rdf:type rdfs:Property;
rdfs:domain ex:Book;
rdfs:range ex:Person.
ex:umld rdf:type ex:Book;
ex:hasAuthor ex:mfowler;
ex:title "UML Distilled";
ex:isbn "0201325632".
ex:mfowler rdf:type ex:Person;
ex:firstname "Martin";
ex:lastname "Fowler".