Thus, as in the case of natural languages, the pattern language is generative. It not only tells us the rules of arrangement, but shows us how to construct arrangements as many as we want which satisfy the rules.

We know from modern neuroscience that prediction is a core property of human intelligence. Perhaps the game of predict-the-next-word is what children unconsciously play when they are acquiring language themselves: listening to what initially seems to be a random stream of phonemes from the adults around them, gradually detecting patterns in that stream and testing those hypotheses by anticipating words as they are spoken. Perhaps that game is the initial scaffolding beneath all the complex forms of thinking that language makes possible.

“pattern language” to describe the show’s plot formulas, which they and ultimately other users would then apply to a variety of programs.

With Lotus Notes, I can combine a hierarchically organized outline view of the documents, with full text searching, hypertext links and traditiona l relational database like reports (for example, a sorted view of items to do).

Before the publication of the ‘Gang of Four’ book that popularised software patterns [4], Richard Gabriel described Christopher Alexander’s patterns in 1993 as a basis for reusable object‐oriented software in the following way:Habitabilityisthecharacteristicofsourcecodethatenablesprogrammers,coders,bug­fixers,andpeoplecomingtothecodelaterinitslifetounderstanditsconstructionandintentionsandtochangeitcomfortablyandconfidently.

Connected to this are Andy Matuschak’s comments about contextual backlinks bootstrapping new concepts before explicit definitions come into play.

Easily updated pages: don’t worry about precisely naming something at first. Let the meaning emerge over time and easily change it (propagating through all references).

Cognitive Overhead (aka Cognitive Load): often the task of specifying formalism is extraneous to the primary task, or is just plain annoying to do.

The basic intuition is described well by the Shipman & Marshall paper: users enter information in a mostly informal fashion, and then formalize only later in the task when appropriate formalisms become clear and also (more) immediately useful.

It’s important to notice something about these examples of synthesis representations: they go quite a bit further than simply grouping or associating things (though that is an important start). They have some kind of formal semantic structure (otherwise known as formality) that specifies what entities exist, and what kinds of relations exist between the entities. This formal structure isn’t just for show: it’s what enables the kind of synthesis that really powers significant knowledge work! Formal structures unlock powerful forms of reasoning like conceptual combination, analogy, and causal reasoning.

Systems which display backlinks to a node permit a new behavior: you can define a new node extensionally (rather than intensionally) by simply linking to it from many other nodes—even before it has any content.

Fundamental to any science or engineering discipline is a common vocabulary for expressing its concepts, and a language for relating them together. The goal of patterns within the software community is to create a body of literature to help software developers resolve recurring problems encountered throughout all of software development. Patterns help create a shared language for communicating insight and experience about these problems and their solutions. Formally codifying these solutions and their relationships lets us successfully capture the body of knowledge which defines our understanding of good architectures that meet the needs of their users. Forming a common pattern language for conveying the structures and mechanisms of our architectures allows us to intelligibly reason about them. The primary focus is not so much on technology as it is on creating a culture to document and support sound engineering architecture and design.

“participation architectures.”