Rdfs example file

A prefix is a short name that is mapped to a long namespace. A prefixed name is the sequence of the prefix and the local name separated by a colon :.

The empty string is a valid prefix and called the default namespace for a graph. The first declaration is a user-defined default namespace used to identify almost all the nodes and the edges in the graph.

Default namespace means the empty or bare prefix, which is why those IRIs all start with the : symbol. When working with an RDF graph there are typically only a handful of namespaces one needs to use. Stardog allows these prefix mappings to be stored in the database metadata so you do not need to repeat the prefix declarations in every file, database, or query. The commonly used namespaces like RDF and XSD are included by default so in practice you may not need to use a single prefix declaration.

This is a common source of confusion since URLs are used to locate web pages and many common IRIs in fact reference web pages that provide additional information about the corresponding resource. For example, we could have used a tag IRI like tag:stardog. The key takeaway is that IRIs are designed be be globally unique which makes it the easier to unify knowledge graphs created by different teams without worrying about naming clashes. Suppose we extend our example.

We can introduce a blank node between the album and the song to attach this data:. Blank nodes do not have globally unique identifiers so when they are serialized a locally unique, non-persistent label is used. In Turtle serialization we can avoid using these names completely by using the [] abbreviation. When a [ symbol is used in the object position it denotes a new bnode which will be the subject of a subsequent predicate list until the matching ] symbol.

Bnodes are optional and using them makes most sense when there is no identifier that can be used to distinguish nodes from one another. It is considered good practice to avoid bnodes as much as possible so that all nodes can be referenced directly in queries and transactions.

Some of the XSD datatypes can be serialized without the explicit datatype or the quotes. The following table shows examples of serializing different datatypes:. Sometimes it is useful to assign a name to an RDF graph for the purposes of sane data management, access control, or to attach metadata to the overall graph rather than to individual nodes. The notion of named graphs in RDF allows us to do that. Exactly one default graph: The default graph does not have a name and may not contain any triples.

Zero or more named graphs: Each named graph is a pair consisting of a resource IRI or a blank node , which is the the graph name, and an RDF graph. So the example we have been looking at so far was technically an RDF dataset with just a default graph and no named graphs. If we decide to separate the artists, albums, and songs into separate named graphs, then we can group the triples under a GRAPH block in the serialization 3. The next example shows this along with some metadata attached to the graph names in the default graph triples outside the GRAPH blocks are in the default graph :.

Note that it is the triples that are separated into named graphs, not the nodes, and different named graphs can share some common nodes, e. So it is possible to traverse the edges starting from one named graph and continue into another named graph via these shared nodes.

When you parse the example above, the result will look something like this. It also contains a reference to the RDF namespace:. RDF defines only the framework. The elements, artist, country, company, price, and year, must be defined by someone else company, organization, person, etc. In the example above, the property artist does not have a value, but a reference to a resource containing information about the artist. In the examples above we have talked about "list of values" when describing the container elements.

In RDF these "list of values" are called members. As seen in the previous chapter, a container says that the containing resources are members - it does not say that other members are not allowed. In addition, RDF also needs a way to define application-specific classes and properties. However note that object properties need not be two way - they may be one way. And, just as importantly, need not be between instances of the same OWL class.

They may be completely different OWL classes. We do not warrant the correctness of its content. The risk from using it, or any software downloaded from the site, lies entirely with the user. While using our site, you agree to have read and accepted our terms of use and privacy policy.

Contact Us. You have completed this lesson. How OWL headers are constructed and some example uses. How to implement your own OWL classes, subclasses, individuals and properties. How to build your own basic ontology. You should now be able to start the following tutorial: Tutorial 5: Querying Semantic Data. Community Register to download software from our site and interact with other users as you learn semantic web.

Next: Querying Semantic Data Having introduced the advantages of modeling vocabulary and semantics in data models, let's introduce the actual technology used to attribute RDF data models with semantics.

After this tutorial, you should be able to: Understand how RDF data models are semantically encoded using RDFS and OWL Understand that OWL ontologies are RDF documents Understand OWL classes , subclasses and individuals Understand OWL properties Build your own basic ontology, step by step Estimated time: 5 minutes You should have already understood the following tutorial and pre-requisites before you begin: Tutorial 3: Semantic Modeling In the last lesson, we compared some of the more popular traditional forms of modeling data with the semantic model, and then introduced a situation where data sharing was enhanced and made significantly easier by using a semantic web approach.

The planttype class is the highest level class of all plant types. Taxonomy - A Hierarchy Of Terms What we've done is define our semantic terms, or classes, in a hierarchy. Note that class and a set of instances does not have to be the same. The set of instances is the extension of the class, and two different classes may contain the same set of instances. For example, looking at the RDF example graph , class of people having mailbox mailto:joe. In RDFS a class may be an instance of a class.

All resources are instances of the class rdfs:Resource. All classes are instances of rdfs:Class and subclasses of rdfs:Resource.