owl:Thing lanl:Human {
lanl:Institution lanl:worksFor[0..1]; xsd:nil lanl:quit(lanl:Institution x) {
this.worksFor =- x;
}
}
The above code defines the class lanl:Human. Any instance of lanl:Human can have either 0 or 1 lanl:worksFor relationships (i.e. owl:maxCardinality of 1). Furthermore, when the method lanl:quit is executed, it will destroy any lanl:worksFor triple from that lanl:Human instance to the provided lanl:Institution x.

Fhat is a virtual machine encoded in an RDF network and processes Fhat triple-code. This means that a Fhat's program counter, operand stack, variable frames, etc., are RDF sub-netwoks. Figure 3 denotes a Fhat processor (A) processing Neno triple-code (B) and other RDF data
(C).

![0_image_0.png](0_image_0.png)

With Neno it is possible to represent both the system model and its algorithmic processes in a single RDF network. Furthermore with Fhat, it is possible to include the virtual machine that executes those algorithms in the same substrate. Given that the Semantic Web is a distributed data structure, where sub-networks of the larger Semantic Web RDF network exist in different triple-stores or RDF documents around the world, it is possible to leverage Neno/Fhat to allow for distributed computing across these various data sets. If a particular model exists at domain X and a researcher located at domain Y needs to utilize that model for a computation, it is not necessary for the researcher at domain Y to download the data set from X. Instead, a Fhat processor and associated Neno code can move to domain X to utilize the data and return with results. In Neno/Fhat, the data doesn't move to the process, the process moves to the data.

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