## focus and context, part IVa: Codes and context

codes are a – more or less – systematic way of arranging symbols to convey meaning. They can be sometimes rather fuzzy, like e.g. in the art world (example) or very precise like in mathematics. Among others the preciseness of a code depends on how much an agreement (“a key” ?) had been made on symbols and syntax in particular with respect to context sensitivity (the fans in fuzzy fan post constitute a very fuzzy syntax) .

In this post it was already indicated that the blurryness or fuzzyness of a code may be related to the issue of subjectivity and objectivity. Or in other words subjective assertions/experiences/meanings have to be blurry because they cant be empirically proven (repeated in experiments) as they are ultimately linked to the individuum/small collective (i.e. the “subjective”, “the observer”) and thus in this case very few agreements can be made on linking the meaning to a code. Here often analogies play a big role.

An example: If you have a paper in a certain color, lets say red then you can repeatedly show that paper around and call the color red. All people seeing the color (and knowing what a color is) may then agree to call it red or pantone something and therefore agree on the code (here: the symbol red). However the e.g. emotional content of that color (which is linked to the individuum) can be conveyed only in relation to something else (“looks aggressive, looks warm”) and this link to a certain analogy depends on the individuum or the collective. The link may be similar in a certain culture. It may be sometimes even similar on a global scale, like this seems to be the case for facial expressions (a smile – usually means that “the smiling person expresses emotion” which explains to a part the raise of emoticons (a code for emotions) in the U.S. satirical magazine Puck).

Moreover it is a very difficult task (i like that proof on the site about the length of sentences) to connect these “global links” with proper and sound brain functions.

A first step in shedding light into this complicated issue is to look at the symbols themselves.

The project decodeunicode.org

is an independent platform for digital type culture, conceived and developed under the lead of professor Johannes Bergerhausen in cooperation with the designer Siri Poarangan at the University of Applied Sciences Mainz. The project is supported by the Federal Ministry of Education and Research (BMBF) and has the objectives of creating a basis for fundamental typographic research and facilitating a textual approach to the characters of the world for all computer users. That way, expert knowledge can be systematically collected and made accessible to the general public.

decodeunicode places itself as an open science project that specifically builds upon the participation of online users. The submission of information follows the WIKI-principle that’s been used successfully for years by the free online encyclopedia Wikipedia. At decodeunicode.org every interested keyboarder can comfortably do research, write new articles or edit those already existing. For quality assurance the entries for the various character sets are additionally monitored by moderators that can delete entries if required.

->info on talk by Professor Johannes Bergerhausen via the always interesting typography blog slanted
->Basic Multilingual Plane (BMP) Map

The project is interesting not only from the perspective of research, but also from a organisatorial view point. It displays that an open source project may be especially sucessful if experts have an eye on it. This is by the way also true for Wikipedia I think (see e.g. this discussion by Aaron Swartz). I have the suspect that lot of the fundamental contributions to Wikipedia entries (at least on the science side) are made by university members (in fact in very specialized subjects one can often guess who the writing person may be). It is a secret voluntary work, which is based on the expertise and on the secure living conditions university members often have. It is clear that cutting down university budgets and increasing the work load of university members will have an influence on this.

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