LAK11: The Connective Semantic Web?

In the whole discussion about semantic modeling, linked data is supposed to be a type of Graph data as opposed to object, hierarchical or relational data. Two sets of data can be related if they share intersecting vocabularies and ontologies.

Ontologies can be expressed using OWL. OWL extends RDF relationship vocabulary and allows you to define how classes and properties can also be related:

OWL adds more vocabulary for describing properties and classes: among others, relations between classes (e.g. disjointness), cardinality (e.g. “exactly one”), equality, richer typing of properties, characteristics of properties (e.g. symmetry), and enumerated classes.

So OWL allows us to model a domain. We may choose to model it hierarchically or relationally or in terms of a graph using a class-property structure. It is an object-relational model because it allows you to create ontologies that are distinct from their RDBMS level implementations.

Where it is deficient is that we still do not have any way of coding class behaviours. Remember when XML-RPC came in? It offered a way to programmatically extend XML to call methods over HTTP. Similarly, in object relational systems, class behaviours are scriptable allowing runtime changes to happen.

Since Linked Data is not totally object-relational at this point, it cannot benefit from scripts that can adjust properties and relationships on the basis of changes happening in related linked data.

Another aspect is that in the real world, vocabularies are dynamic. Ontologies change over time as well as specializations and inter-disciplinary areas emerge. Therefore the relationships also change and new ones are continually created.

Obsolescence also plays a big role in trimming vocabularies, so does their archival process. There is a management role and overhead complicated by constant new additions because of crawling the unstructured web. The scale itself renders this an impossible endeavour and therefore, we will end up creating vocabularies and ontologies not unlike the RDBMSs of today.

The next aspect is linguistic and cultural differences. The web is diverse and multi-cultural. Building semantic equivalence across these categories is going to be a complex ontological task in itself.

But these would matter if the Linked Data vision was to model the world. I don’t think it is or can be. The vision is to help build a more connected web. It is also to help build a more coherent web.

There is a great challenge in building coherence – take a look at the uneasy implicit alliance between Demand Media and Google – Ben Elowitz writes:

Demand Media probably pollutes Google’s results more blatantly and thoroughly than the top black-hat spammers of the Web.

The closest I have come to building a linked data web with behaviours and without using RDF and OWL, is when we built a simulation framework to model real life sales situations. We called RDF triples (loosely) Facts of Life (FoLs). Each FoL was related to other FoLs and could be described by a value or an enumeration or a range or an expression. Changes in one FoL could impact other FoLs using a set of business rules and computational expressions. FoLs could nest within each other. XML was the base platform for writing the FoLs and their relationships. We built probabilities across each FoL to reflect experienced customer profiles, but that is another story.

What Connectivism and Connectionism tell us is that there are mechanisms that operate in networks. Connections are not static. The graph keeps on changing over time and at varying rates. Not only that, complex and chaotic systems move in complex and chaotic ways.

Without an accommodation of this fact, the Semantic Web would be able to model entities (definitions) and relationships, but not behaviours.

On another related note, I still remember working on JINI http://www.jini.org/wiki/Main_Page when it was first brought out in competition with UDDI.

Jini technology is a service oriented architecture that defines a programming model which both exploits and extends Java technology to enable the construction of secure, distributed systems consisting of federations of well-behaved network services and clients. Jini technology can be used to build adaptive network systems that are scalable, evolvable and flexible as typically required in dynamic computing environments.

Jini is designed to help developers deal with The Eight Fallacies of Distributed Computing. Jini offers a number of powerful capabilities such as service discovery and mobile code.

A stronger model of a semantic web could possibly, in my opinion emerge, if we were to focus on building adaptive network systems that can help derive meaning using open and collaborative efforts. Allow ways for people to build skills and engage in sensemaking.

Rather than trying to model the world, let the world model itself.

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