The innovative spiral is driven by cycles of examplary concretion, abstraction and reconcretion. In the rather new philosophy movement of speculative realism Quentin Meillassoux says (paraphrased): if we do not know more properties of a real world behavior than represented in our models, our models ARE reality.
We often think, physical modeling in contrast to, say, social or economical, is "real". But this is not always true. The prediction of physical effect is not so easy as we often think. The theory of complex systems come into play…It matters what context we write into our models.
"Invert, always Invert" (to solve a problem) said the famous mathematician Jacobi. But inverse problems are ill-posed. To solve a real problem, you often need to ride the waves of a real behavior and use tricky inversion techniques to recalibrate your models…this is required from metal forming to pricing derivatives…
In quantitative fields, programming is essential. Constructor theory, a new fundamental theory of physics tells us: there's no such thing as an abstract program. It needs to run on something physical.
In a birds view, we see that in low tech societies, a few people took the lead and explained to the rest what is "true". Technology may help to explore and use helpful information without taking a special lead.
This is why I find low-abstraction - high abstraction type definitions very helpful assessing an innovation.
Factualism - systems that refer to facts. Curated data, knowledge, proven algorithms…they are often represented in (library)tools, engines, platforms, servers…the top reference Wolfram|Alpha the computational knowledge engine.
Realism - systems that refer to real world and real life problems…they're usually solvers driven by implementation, efficiency....They can go deep or offer a broad coverage. Calculate stress, heat, mechanisms dynamics, elasto-plastic behavior, fluid dynamics, magnetism, ray-tracing…or all of these…control functional complexes or complex flow processes…manage risk and return dynamics…for different sectors or cross-sectoral…
They're usually combing evaluation and data management relying on intelligent combinations of (mathematical)modeling and data science…
It's subject of a later post, but I want to mention it here. IMO. it is required for those kind of real world problem solvers to organize their objects, models mad methods (solvers) strictly orthogonally. This is one of the conventions, I suggest in The Innovation Mesh.
It's so simple, but often suppressed: in many fields you need multi-model and multi-method approaches - what's the use of a complicated model that's extra information gets lost in the numerical jungle?
Idealism - systems that support the problem solving process itself . They're usually offering a programming environment with language constructs that provide abstraction, exptessiveness...in the sense of language cascades (one developed atop the other). Examples are Modelica or Wolfram Language in combination sold as System Modeler.
Fantasy - systems that provide information and knowledge in a virtual, speculative "world" and with special effects. They're often representing results of design, analysis, simulation...in creative ways. In design, arts, entertainment...but increasingly important in science.
I often read: those systems will replace the "scientific method" (in the exabyte age). I could not disagree more. They're extending the expressiveness. And this is a lot.
In the near future, I'll come to Style Types.