Let us start from individual users, before we move to the corporate level. As a note on the potentially endless debate on what a point of view is, we can only recommend that you reflect once more on the concept of linguistic phase space. On treating "the right to hold one's point of view" we use a very similar concept called semantic phase space.

What we mean is that the profile "water" is not only emerging as a different entity depending on its current linguistic phase, but also depending on its current semantic phase. There is no particular warranty that two semantic phases will remain mutually intelligible within the same linguistic phase.

By all practical means, a user may well need a translation from English to English, in order to make any use of what was originally born in deeply specialized terms. It's indeed not many people who will immediately understand the scientific version of the common phrase "liquid water is wet". And even if they could understand it, chances are this is not what they are looking for. Both the individual and the corporate user may want to choose one or more preferred semantic phases.

What we aim to build is an adaptive content network. Something an end user may tune both in terms of linguistic and semantic phases. This implies some tool by which a user can tell the system what is relevant for him/her, and any such tool needs a well identified set of parameters on which it can operate.

We are not replicating the way human brains work. Human brains work as fractally complex parallel systems that simultaneously process a combination of analogue and digital information at an incredible amount of different levels. We have no such resource at hand because we are using a Von Neumann machine, so we simply try and make a practical use of the data we already have.

Now let's see what we can use to make a filter. We have linguistically dependant information, that is, the extended classification by which our system tracks any content's linguistic phase. We also have a linguistically independent vector, the thing saying that a tiger is a feline is a mammal is an animal. We shall call this a semantic vector.

A profile object, as we see on the graphic, has no direct knowledge of any of the two vectors. So a profile object is portable anyway, no matter what happens to the semantic and linguistic values that were attached to it. If there is nothing stopping us from sending it out, the next step is to define how a user will say whether he/she wants to receive the object or not.

Suppose a user speaks wonderful Thai and Khmer, but he/she has no notion whatsoever of English. This person may well decide to ignore whatever semantic classification other people made, as long as the involved class objects cannot manifest themselves in a linguistic phase he/she can use. This implies that such person's semantic content will be full of holes, holes that the user can fill by making his/her own new profile objects used as class objects for semantic classification. In short, since no แมว class object appears on the screen and emersions like cat, кот and ネコ were ignored as useless, the user proceeds to make a new แมว class object on his/her own.

Now wait a minute, isn't this a whole lot of silly dupes?? Well... yes, absolutely. Yet, we must live with this problem anyway, no matter whether we broadcast all content or not. Even if we sent this guy terabytes of classification just to make sure that "no holes are there" those holes would vanish only from his/her local database. The user's linguistic phase space would not extend a bit in the process (just think of the use most English speakers can make of emersions like кот, ネコ, قط ,חתול or შინაური კატა) and thus duplicate profile objects would still be created in huge lots.

This is something that only multilingual human personnel can solve, by patiently marking candidates for merging whenever they meet them. The process will always be long and difficult, since no person on earth speaks ALL the possible linguistic phases we can store.

We also have the case of someone who can use one or more languages that he/she doesn't want to download. Say this person is a translator from Bulgarian to Hindi, looking for a dictionary on construction engineering. This user will mostly ignore Dutch terminology, but maybe he/she can speak Dutch, if even just enough to make use of a class object emerging like Spoorweg (Rail transport). This user may well want to ignore all profile objects that cannot emerge in the Bulgarian or Hindi linguistic phase, but decide to accept class objects that can emerge in Dutch.

We encourage people to use the widest linguistic phase surface for semantic classification, as this dramatically accelerates  the process leading to a compact set of profile objects. Profiles that have the same kind of detailed semantic classification and no overlapping linguistic phase are automatically sent for evaluation to the admins. Maybe they are not "exactly the same thing", but they are somehow closely related anyway, so it's worth giving them a closer look.

With this goal in mind we offer our users an extended linguistic phase surface for the network synchronisation of class objects only. Users do not get any "plain content" on extension phases, so the process eats up very little bandwidth and space while providing them with the best linguistic support for their semantic vector. Hmmm.... extended linguistic phase surface!? Now what the heck is that?? Okay, okay... Let's translate it from English to English: you can state a number of additional languages the system can use to send you class objects. These languages' usual content is of no interest to you, but they can be succesfully used to give you classificatory information when such information is not available in any of your usual language of choice.

So much for the linguistic vector. Now if you apply exactly the same filter to the semantic vector, you find yourself telling the system that you want to receive those profile obejcts that are classified by the construction engineering class AND by the Spoorweg class, maybe NOT those classified by the Stone rails included class (say you are not interested in archaeological stuff).

When the network daemon connects to other nodes, it will know what to request based on such specifications. This is what OWm2 calls its subscription mechanism, which is the basic mechanism allowing individuals to pick their choice of available content. In the next chapter we shall finally see how this applies to corporate level, thus giving birth to our region objects.