Measuring the Semantic Web

The book Weaving the Web by Tim Berners-Lee [i] presents a plan to build what is called The Web. Basically, it can be described as a decentralised knowledge system that self-organises and evolves scaling to unforeseen conditions. The Semantic Web effort is introduced as the last step towards completing this idea, from the result of the World Wide Web effort. This knowledge system is not like previous ones. It is open and growths freely, without central control, and this can produce many undesired outcomes that can be also seen as opportunities. The World Wide Web is based on the same principles, e.g. there are link consistency problems, but has largely succeeded. However, these are only vague words. What have we really built with the World Wide Web? And what are we building with the Semantic Web? How near we are from the original plans and what is the metric? These are difficult questions. The WWW and the Semantic Web are acquiring a size and a complexity that puts them out of our control and even from our direct conception. What can we do? Just looking around we realise that the WWW and the Semantic Web are just as complex as many other systems. Other research communities have faced similar problems and found a common approach, which has properly been called the study of complex systems. Are they complex systems? Complex systems (CSs) are made up of the combination of a great amount of elements. However, their behaviour is not the sum of the behaviour of their parts. Examples of CSs are metabolic networks [i] acquaintance networks [ii], food webs [ii] or neural networks [ii]. Actually, it has also been shown that the WWW is a CS [ii]. What do all this systems have in common? How to identify a CS? Scientists have looked for a way to achieve this using some mathematical tools, concretely graphs and statistical mechanics. In the next section this methods are presented.