The semantic web comes in layers. This is a quick summary of the ones I think you’re interested in.
Update: Please note that RDFS is used to define the structure of the data, not OWL. OWL describes semantic relationships which normal programming, such as a C struct, isn’t fussed about and is closer to AI research & set theory.
Triples & URIs
Subject - Predicate - Object
These describe a single fact. Generally URI’s are used for the subject and predicate. The object is either another URI or a literal such as a number or string. Literals can have a type (which is also a URI), and they can also have a language. Yes, this means triples can have up to 5 bits of data!
For example a triple might describe the fact that Charles is Harrys father.
<http://example.com/person/harry> <http://familyontology.net/1.0#hasFather> <http://example.com/person/charles> .
Triples are database normalization taken to a logical extreme. They have the advantage that you can load triples from many sources into one database with no reconfiguration.
RDF and RDFS
The next layer is RDF – The Resource Description Framework. RDF defines some extra structure to triples. The most important thing RDF defines is a predicate called “rdf:type”. This is used to say that things are of certain types. Everyone uses rdf:type which makes it very useful.
RDFS (RDF Schema) defines some classes which represent the concept of subjects, objects, predicates etc. This means you can start making statements about classes of thing, and types of relationship. At the most simple level you can state things like http://familyontology.net/1.0#hasFather is a relationship between a person and a person. It also allows you to describe in human readable text the meaning of a relationship or a class. This is a schema. It tells you legal uses of various classes and relationships. It is also used to indicate that a class or property is a sub-type of a more general type. For example “HumanParent” is a subclass of “Person”. “Loves” is a sub-class of “Knows”.
RDF Serialisations
RDF can be exported in a number of file formats. The most common is RDF+XML but this has some weaknesses.
N3 is a non-XML format which is easier to read, and there’s some subsets (Turtle and N-Triples) which are stricter.
It’s important to know that RDF is a way of working with triples, NOT the file formats.
XSD
XSD is a namespace mostly used to describe property types, like dates, integers and so forth. It’s generally seen in RDF data identifying the specific type of a literal. It’s also used in XML schemas, which is a slightly different kettle of fish.
OWL
OWL adds semantics to the schema. It allows you to specify far more about the properties and classes. It is also expressed in triples. For example, it can indicate that “If A isMarriedTo B” then this implies “B isMarriedTo A”. Or that if ” C isAncestorOf D ” and ” D isAncestorOf E ” then ” C isAncestorOf E “. Another useful thing owl adds is the ability to say two things are the same, this is very helpful for joining up data expressed in different schemas. You can say that relationship “sired” in one schema is owl:sameAs “fathered” in some other schema. You can also use it to say two things are the same, such as the “Elvis Presley” on wikipedia is the same one on the BBC. This is very exciting as it means you can start joining up data from multiple sites (this is “Linked Data”).
You can also use the OWL to infer implicit facts, such as “C isAncestorOf E“.