Examples: 1 represents "on," 0 represents "off" (or as Liebniz would have it, God and Void, respectively); UML represents program, class, interaction, etc.; internal representations of an external world in AI.
Art, althrough it uses representation (musical notes), seems to have more focus on evocation - assisting the viewerlistenertaster... to recreate a memorystate of mind.
Evocation allows for styles in a way that representation does not. Instances of hyper-realism and cubism might evoke the same response in a viewer.
Evocation is a major shortcut for both sender and receiver in an information exchange.
Attempts to use evocation are evident in software - XP story cards, CRC cards - being obvious examples. The story text does not represent the requirements for the software, it evokes a memory of the discussions about the requirements that have taken place among the participants exploring and defining those requirements. Such efforts to use evocation are usually dismissed as "informal."
I presented a paper at an XP conference that suggested an "evocatory architecture" based on a Wheel of Life Thangka painting hanging in my office. Evocation made it possible to quickly construct a visual gestalt, full of detail and associations, that remained true to the XP philosophy while providing a much richer alternative to "System Metaphor."
What might we learn about evocation from art and artists and apply in computer science / software development? --DaveWest
Not to go way off tangent, but this had me considering where the notion arises that science is objective, devoid of bias and heavily weighted to "process over people" (to borrow the term briefly). For how does the scientific method work without the generation of hypotheses, and how do hypotheses arise without creativity, expressiveness and the reinterpretation of existing theories (theories as representations)? It seems that the hypothesis is where new ideas are framed within the context of that which is probable and that which is plausible. Many hypotheses may exist for a given domain, but the ones that evoke stronger responses in the scientist may have higher survival rates in the field.
The concept of a metaphor in XP is similar in nature to the hypothesis ("I propose that this system resembles a car"), but I see a problem lingering. "This system works like a car" is nice and simple-- easy to wrap ones head around, but how many applications really work like a car? Working with complex systems, I'm often surrounded by a collage of metaphors-- the car with cylinders that work like threading needles, etc. Taking another approach, "This pricing system works like RNA transcription" as a metaphor might be keen to the business at hand (and much more evocative to boot) but like commercial or mainstream art, the measure of a metaphor or hypothesis can be subject to common denominators of taste, appeal, and marketability. Keeping these things in check is the real trick.
--IvanMoscoso