What is the difference between RDF and OWL?

Question

I am trying to grasp the concept of Semantic Web. I am finding it hard to understand what exactly is the difference between RDF and OWL. Is OWL an extension of RDF or these two are totally different technologies?

Answer 1

I am trying to grasp the concept of Semantic Web. I am finding it hard to understand what exactly is the difference between RDF and OWL. Is OWL an extension of RDF or these two are totally different technologies?

In short, yes you could say that OWL is an extension of RDF.

In more detail, with RDF you can describe a directed graph by defining subject-predicate-object triples. The subject and the object are the nodes, the predicate is the edge, or by other words, the predicate describes the relation between the subject and the object. For example :Tolkien :wrote :LordOfTheRings or :LordOfTheRings :author :Tolkien, etc... Linked data systems use these triples to describe knowledge graphs, and they provide ways to store them, query them. Now these are huge systems, but you can use RDF by smaller projects. Every application has a domain specific language (or by DDD terms ubiquitous language). You can describe that language in your ontology/vocabulary, so you can describe the domain model of your application with a graph, which you can visualize show it to business ppl, talk about business decisions based on the model, and build the application on top of that. You can bind the vocab of your application to the data it returns and to a vocabulary known by the search engines, like microdata (for example you can use HTML with RDFA to do this), and so search engines can find your applications easily, because the knowledge about what it does will be machine processable. This is how semantic web works. (At least this is how I imagine it.)

Now to describe object oriented applications you need types, classes, properties, instances, etc... With RDF you can describe only objects. RDFS (RDF schema) helps you to describe classes, inheritance (based on objects ofc.), but it is too broad. To define constraints (for example one kid per chinese family) you need another vocab. OWL (web ontology language) does this job. OWL is an ontology which you can use to describe web applications. It integrates the XSD simpleTypes.
So RDF -> RDFS -> OWL -> MyWebApp is the order to describe your web application in a more and more specific way.

Answer 2

RDFS allows you to express the relationships between things by standardizing on a flexible, triple-based format and then providing a vocabulary ("keywords" such as rdf:type or rdfs:subClassOf) which can be used to say things.

OWL is similar, but bigger, better, and badder. OWL lets you say much more about your data model, it shows you how to work efficiently with database queries and automatic reasoners, and it provides useful annotations for bringing your data models into the real world.

1st Difference: Vocabulary

Of the differences between RDFS and OWL, the most important is just that OWL provides a far, far larger vocabulary that you can use to say things.

For example, OWL includes all your old friends from RDFS such as rdfs:type, rdfs:domain, and rdfs:subPropertyOf. However, OWL also gives you new and better friends! For example, OWL lets you describe you data in terms of set operations:

Example:Mother    owl:unionOf     (Example:Parent, Example:Woman)

It lets you define equivalences across databases:

AcmeCompany:JohnSmith  owl:sameAs    PersonalDatabase:JohnQSmith

It lets you restrict property values:

Example:MyState     owl:allValuesFrom     (State:NewYork, State:California, …)

in fact, OWL provides so much new, sophisticated vocabulary to use in data modeling and reasoning that gets its own lesson!

2nd Difference: Rigidity

Another major difference is that unlike RDFS, OWL not only tells you how you can use certain vocabulary, it actually tells you how you cannot use it. By contrast, RDFS gives you an anything goes world in which you can add pretty much any triple you want.

For example, in RDFS, anything you feel like can be an instance of rdfs:Class. You might decide to say that Beagle is an rdfs:Class and then say that Fido is an instance of Beagle:

Example: Beagle    rdf:Type    rdfs:Class

Example:Fido    rdf:Type    Example: Beagle

Next, you might decide that you would like to say things about beagles, perhaps you want to say that Beagle is an instance of dogs bred in England:

Example:Beagle    rdf:Type    Example:BreedsBredInEngland

Example: BreedsBredInEngland    rdf:Type    rdfs:Class

The interesting thing in this example is that Example:Beagle is being used as both a class and an instance. Beagle is a class that Fido is a member of, but Beagle is itself a member of another class: Things Bred in England.

In RDFS, all this is perfectly legal because RDFS doesn't really constrain which statements you can and cannot insert. In OWL, by contrast, or at least in some flavors of OWL, the above statements are actually not legal: you're simply not allowed to say that something can be both a class and an instance.

This is then a second major difference between RDFS and OWL. RDFS enables a free-for-all, anything goes kind of world full of the Wild West, Speak-Easies, and Salvador Dali. The world of OWL imposes a much more rigid structure.

3rd Difference: Annotations, the meta-meta-data

Suppose that you've spent the last hour building an ontology that describes your radio manufacturing business. During lunch, your task is to build an ontology for your clock manufacturing business. This afternoon, after a nice coffee, your boss now tells you that you'll have to build an ontology for your highly profitable clock-radio business. Is there a way to easily reuse the morning's work?

OWL makes doing things like this very, very easy. Owl:Import is what you would use in the clock-radio situation, but OWL also gives you a rich variety of annotations such as owl:versionInfo, owl:backwardsCompatibleWith, and owl:deprecatedProperty, which can easily be used link data models together into a mutually coherent whole.

Unlike RDFS, OWL is sure to satisfy all of your meta-meta-data-modeling needs.

Conclusion

OWL gives you a much larger vocabulary to play with, which makes it easy to say anything you might want to say about your data model. It even allows you to tailor what you say based on the computational realities of today's computers and to optimize for particular applications (for search queries, for example.) Further, OWL allows you to easily express the relationships between different ontologies using a standard annotation framework.

All these are advantages as compared to RDFS, and are typically worth the extra effort it takes to familiarize yourself with them.

Source : RDFS vs. OWL

Answer 3

In short:

• RDF defines how to write stuff
• OWL defines what to write

As previous poster wrote, RDF is a specification which tells you how to define triples.

The problem is that RDF allows you to define everything, so you could compose a declaration like this:

| subject | predicate | object |
|---------|-----------|--------|
| Alex    | Eats      | Apples |
| Apples  | Eats      | Apples |
| Apples  | Apples    | Apples |

These triples form valid RDF documents.

But, semantically, you understand that these statements are incorrect and RDF cannot help you to validate what you have written.

This is not a valid ontology.

OWL specification defines exactly what you can write with RDF in order to have valid ontology.

Ontologies can have several properties.

Thats why OWL (ver 1) defines several versions like OWL DL, OWL Lite, OWL Full.

Answer 4

Firstly, an as has been pointed out before, owl can be serialised in RDF.

Secondly, OWL adds ontological capability to RDF (which on its own only provides extremely limited capability for formal knownledge representation), by providing the apparatus to define the components of your triple using formal computable first order description logic. That is what posters here mean by when they talk about "semantic richness".

Thirdly, it's important to realise that in OWL-Full (for OWL 1) rdfs:class and owl:class are equivalent and in OWL-DL, owl:class is a subclass of rdfs:class. In effect, this means that you can use an OWL ontology as a schema for RDF (which does not formally require schemata).

I hope that helps to clarify further.

Answer 5

I personally found this slide deck quite useful and understandable: http://www.slideshare.net/rlovinger/rdf-and-owl

Answer 6

RDF is a way to define a triple 'subject','predicate', 'value'. For example, if I want to say,

"my name is Pierre"

I would write

<mail:[e-mail]> <foaf:name> "Pierre"

See the <foaf:name> ? it is part of the FOAF ontology. An ontology is a formal way to describe the properties, the classes of a given subject and OWL is a (RDF) way to define an ontology.

You use C++, Java, etc... to define a Class, a subclass, a field, etc...

class Person
{
    String email_as_id;
    String name;
}

RDF uses OWL to define these kinds of statements.

Another place to ask this kind of question: http://www.semanticoverflow.com/