Setting up an RDF server in VirtualBox, part 2

This is the second part of a two-part (maybe N-part?) series about setting up an RDF server in a VirtualBox instance with the Ubuntu 12.04 server distribution. In this part, I'll set up Mediawiki as a place to conveniently edit RDF/Turtle documents.

You might be thinking, what about Semantic Mediawiki? Doesn't this already exist? My experience with SMW was disappointing. The source syntax for creating links is pretty straightforward, and the silly naming scheme for importing external ontologies doesn't seem too bad. But when you want to do any real work with external ontologies, it gets difficult. After a few days of hacking around I couldn't find a way to say that a predicate defined in my SMW instance was owl:sameAs some predicate defined externally. At that point, I decided to strike out on my own.

The results of that effort are on GitHub at https://github.com/wware/stuff/tree/master/semantic-wiki. The setup script is to be run in the VirtualBox instance after the Ubuntu 12.04 server installation (with LAMP and SSH servers enabled) has completed.

This is a work in progress. When I've got it beaten into presentable shape, I'll put it up at http://willware.net with more explanatory material.

Jena: Node versus RDFNode

The Jena code has two representations for nodes in an RDF graph. One is the class Node, which has several subclasses: Node_Variable, Node_Literal, Node_URI, etc. The other is the interface RDFNode, which has many subinterfaces: Literal, Resource, Property, etc.

These two node representations have very different roles and very different idiomatic usages, and this doesn't appear to be spelled out in the Jena documentation anywhere. RDFNode is in the com.hp.hpl.jena.rdf.model package, where Node is in the com.hp.hpl.jena.graph package, but I don't think the packaging by itself is a big enough hint.

The Jena tutorials mostly talk only about the RDFNode variants, usually instantiating them by calling a "create" method on the Model. The poorly documented distinction between RDFNode and Node extends to the distinction between Model and Graph, and between Statement and Triple.

Since this information didn't appear in the documentation, we need to look at the Jena mailing list to find it.

A key difference between Resource and Node is that Resources know which model they are in, and Nodes are general. That's what makes resource.getProperty() work. Now in a query that is not a concept that has any meaning in the general case and patterns can span graphs.

We have found that Model/Statement/RDFNode (the API) works as an application interface but it's not the right thing for storage abstractions and the Graph/Triple/Node (the SPI) works better where the regularity is more valuable. That is, we have split the application-facing design from the sub-system-facing design.

So an instance of RDFNode is associated with a specific Model, where an instance of Node is free-floating, and is used to build Rules, which are also model-independent. The two representations can be connected by URIs. If you have a Node and a Model, and you want the corresponding RDFNode, do this (or use createProperty or createLiteral as needed):

Resource r = model.createResource(uri1);

and if you have an RDFNode, you can do this to get a Node:

Node uriNode = Node.createURI(
        ((Resource)rdfNode).getURI());

So I can understand that there are two very different appropriate interfaces for writing Jena apps and for interfacing to a storage system. What I don't get is why I would ever see the latter while writing an application. If I define a Rule, I need to deal in Nodes. Presumably this is because I've been constructing Rules programmatically rather than just reading them in from a file. Maybe I should stick with the latter.

Playing with the Jena semantic web framework

I've begun tinkering with Jena, a semantic web framework written in Java. It embodies a lot of ideas and technologies that were once considered AI or expert systems, and which I neglected at the time (1980s).

• Jena homepage: http://jena.sourceforge.net/
• Docs: http://jena.sourceforge.net/documentation.html
• Javadoc: http://jena.sourceforge.net/javadoc/index.html

The semantic web frames a body of knowledge as a collection of three-word sentences called triples. These can be diagrammed as a directed graph such as the one below.

The corresponding three-word sentences appear below, written in N3, a human-readable formal language used by the semantic web community.

@prefix :  <#> .
:Cat :has :Fur .
:Bear :has :Fur .
:Cat :is-a :Mammal .
:Bear :is-a :Mammal .
:Mammal :has :Vertebrae .
:Whale :is-a :Mammal .
:Whale :lives-in :Water .
:Mammal :is-a :Animal .
:Fish :is-a :Animal .
:Fish :lives-in :Water .

In Jena, a Model is one of these things. Having constructed it (or having loaded it from either a file on the internet or a file on your computer), you can apply rules that allow you to draw conclusions. So let's step through that proecess. First we need to read in the file.

private static final String baseUri =
    "file:///home/wware/wware-autosci/" +
    "semweb/java/simpleNet.n3#";
private static void modelReadFile(String filename,
                                  Model model) {
    try {
        File f = new File(filename);
        FileReader fr = new FileReader(f);
        model.read(fr, baseUri);
    } catch (FileNotFoundException e) {
        e.printStackTrace();
    }
}

To print the contents of a model, we can use the SPARQL query language, which looks a lot like SQL.

private static void printModel(Model model) {
    String queryString = 
        "SELECT ?x ?y ?z " +
        "WHERE {" +
        "    ?x ?y ?z . " +
        "}";
    Query query = QueryFactory.create(queryString);
    QueryExecution qe =
      QueryExecutionFactory.create(query, model);
    ResultSet results = qe.execSelect();
    ResultSetFormatter.out(System.out, results, query);
    qe.close();
}

and we'll call that method from our main method. I personally find it appalling that the graph above fails to recognize that fish have vertebrae, so we'll add a triple for that.

public static void main(String[] args) {
    Model model = ModelFactory.createDefaultModel();
    modelReadFile("simpleNet.rdf", model);
    model.createResource(baseUri + "Fish")
         .addProperty(model.createProperty(
                         baseUri + "has"),
                      model.createResource(
                         baseUri + "Vertebrae"));
    printModel(model);
}

and the RDF file that imports the model was translated from the N3 above, using CWM.

<rdf:RDF
xmlns="file:///home/wware/wware-autosci/semweb/java/simpleNet.n3#"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
    <rdf:Description rdf:about="#Bear">
        <has rdf:resource="#Fur"/>
        <is-a rdf:resource="#Mammal"/>
    </rdf:Description>
    <rdf:Description rdf:about="#Cat">
        <has rdf:resource="#Fur"/>
        <is-a rdf:resource="#Mammal"/>
    </rdf:Description>
    <rdf:Description rdf:about="#Fish">
        <is-a rdf:resource="#Animal"/>
        <lives-in rdf:resource="#Water"/>
    </rdf:Description>
    <rdf:Description rdf:about="#Mammal">
        <has rdf:resource="#Vertebrae"/>
        <is-a rdf:resource="#Animal"/>
    </rdf:Description>
    <rdf:Description rdf:about="#Whale">
        <is-a rdf:resource="#Mammal"/>
        <lives-in rdf:resource="#Water"/>
    </rdf:Description>
</rdf:RDF>

There is a Model.write(OutputStream) method, so we can write a model directly to a file instead of stepping through the triples explicitly.

So how about some actual reasoning? We should be able to conclude that a cat is an animal, and has vertebrae. This will require that we define two rules of inference, rule1 ("is-a" is transitive) and rule2 (a member of a species has the things the species has).

String rules =
        "[ rule1: (?x " + baseUri+"is-a ?y) " +
                 "(?y " + baseUri+"is-a ?z) -> " +
                 "(?x " + baseUri+"is-a ?z) ] " +
        "[ rule2: (?x " + baseUri+"is-a ?y) " +
                 "(?y " + baseUri+"has ?z) -> " +
                 "(?x " + baseUri+"has ?z) ]";
Reasoner reasoner = new
    GenericRuleReasoner(Rule.parseRules(rules));
reasoner.setDerivationLogging(true);
InfModel inf =
  ModelFactory.createInfModel(reasoner, model);
printModel(inf);

Simply creating the InfModel is enough to draw all the relevant inferences. The Reasoner's setDerivationLogging method tells the model to remember the derivations that led to any new conclusions, and these derivations can be examined for debugging purposes.

PrintWriter out = new PrintWriter(System.out);
for (StmtIterator i = inf.listStatements();
             i.hasNext(); ) {
    Statement s = i.nextStatement();
    for (Iterator id = inf.getDerivation(s);
             id.hasNext(); ) {
        Derivation deriv = id.next();
        deriv.printTrace(out, true);
    }
}
out.flush();