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of content, and therefore know exactly how it is built. We don’t do that with human brains, or not yet.

Content is in fact organized in repetitive layers, each describing the previous one, and each time in two parts, that of the description, and that of the data themselves. In the computer world, the description of data is called metadata. For example, let’s consider a music piece registered on a hard disk. What we have here is the first level of content data, that representing the notes of music. What the description associated with those data does is make the format explicit, so that we know how to decode the signal on the disk. For example, the description can say that the music is represented using the familiar MP3 format. Thus we have a first piece of content, the combination of the music and the description of the format used to represent it. Therefore, we will go one step further, by describing that new content, giving it a name, say Like a Virgin, the song by Madonna. Here we go: we have a yet another, more elaborate piece of content, one that is identified by name. Let’s go another step up, by combining that song of Madonna with another song, say Material Girl; we can describe the assembly of the two songs, and give that a description, that of the second album of Madonna. What was its title? In fact, it was Like a Virgin; the album had the same name as the song of its first track. But the computer is not confused, because in one case Like a Virgin is associated with a single song, in the other it’s associated with an assembly of songs, in this case an album. So here we’ve seen how content is built up, in an elegant architecture taking simpler elements, structuring each layer into description and content, and then going up from there.

Network

It is only recently that a model of the world of computer networks has been developed that encompasses all aspects of network development in a single framework. That has come by the meeting of two disciplines of computer science, in the end of the 1990’s and the beginning of the 2000’s. The first discipline is the Web and its progressive structuring, with the alluring presence of its founder, Tim Berners-Lee. Berners-Lee invented the Web and to this day has been a major influence on its development. The second discipline is Artificial Intelligence, and particularly the part of it which is concerned by the representation of knowledge in computers. You guessed it; the convergence is that of making the network knowledgeable.

Central to the discipline of Web development is Berners-Lee’s invention of the Resource Description Framework. The idea goes as follows. If I have an album of Madonna on the hard disk of a computer somewhere, how does another computer on the network know about it? Is there any way to devise a universal scheme that allows identifying any resource in the world, anywhere on the network? Because Berners-Lee is such a prescient thinker, he made the question even larger. If a computer wants to designate something that is not in a computer, why shouldn’t that be possible also? So here it is: Berners-Lee wanted to have a way to name anything in the world, whether on a computer or not, so that computers could have access to all the knowledge in the world. Of course, since we humans are the ultimate users of the computers, thanks to Berners-Lee’s invention, we too can describe any piece of content in the world, be it a song by Madonna, the description of a tree in the Amazon or a black hole far away in the universe. So, Berners-Lee called his invention a Uniform Resource Identifier (URI). The genius in the invention is that he had disconnected the naming of things from the description of the things themselves. What he really did is bring to the computer world something that is very natural to humans. We can talk about a bird without speaking about a particular bird, that bird. When we talk about a bird in general, with no specific bird in mind, we are using what’s known in linguistics as the connotation

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