domain modeling, concept analysis, knowledge structure, ontology, "applying" knowledge and faith

domain modeling, concept analysis, knowledge structure, ontology, "applying" knowledge and faith

This blog is try to expand the perspective of "8 core techniques" + "3 questions" (high-level use cases, uses cases, domain model). More accurately, it is to expand "3 questions", because it is "3 questions" that expands "8 core techniques" into business process perspective. In this blog, I will continue to expand that into everyday life.

There are two questions: (a) can domain modeling be used as a general concept analysis tool? -- perhaps we need a concept of "knowledge structure"; (b) everything is knowledge, is that really true?

(a) Let's say, can we apply domain modeling in physics study? Putting it that way, to be frank, I doubt it. However, how about computational physics? Then, the difference between "ordinary" physics and computational physics? I believe there are three elements here.
(i) In domain modeling, the key is the multiplicity. Is multiplicity the key for other concept analysis? I really doubt it. However, is multiplicity really the whole story of domain analysis? No. Further, having a sense of multiplicity will help qualitative analysis.
(ii) It seems that when we do "ordinary" concept analysis, we tend to blur the border between the reality and the concept, i.e., the representation of the reality. It is not a good habit. When we do "domain modeling", we know the difference, because we know we are doing data modeling or in-memory-object modeling. However, "data" or "in-memory-object" are obvious too nerdy, too computer/software-centric. So, I believe "knowledge structure" (or, "ontology") is a good concept. It is more tangible than "concept analysis", and therefore can remind us the border between reality and the representation of reality, while it can be applied to "wet" brain, and used naturally everywhere and not (too) nerdy.
(iii) From academic point of view, "knowledge structure" should be a important concept in philosophy, more specifically, ontology, philosophy of language, philosophy of science, metaphysics, epistemology, and, my favorite (seriously, perhaps someday I will go back to study of psychology) psychology of sleep: http://pespmc1.vub.ac.be/KNOWSTRUC.html (the result of the googling after I wrote this blog).

more links from googling "ontology"

http://en.wikipedia.org/wiki/Ontology
http://ontology.buffalo.edu/
http://www-ksl.stanford.edu/kst/what-is-an-ontology.html
http://www.jfsowa.com/ontology/

---------------- a quote from wikipedia about the differences between the ontology studies of computer science and philosophy

What ontology has in common in both computer science and philosophy is the representation of entities, ideas, and events, along with their properties and relations, according to a system of categories. In both fields, one finds considerable work on problems of ontological relativity (e.g. Quine and Kripke in philosophy, Sowa and Guarino in computer science (Top-level ontological categories. By: Sowa, John F. In International Journal of Human-Computer Studies, v. 43 (November/December 1995) p. 669-85.), and debates concerning whether a normative ontology is viable (e.g. debates over foundationalism in philosophy, debates over the Cyc project in AI).

Differences between the two are largely matters of focus. Philosophers are less concerned with establishing fixed, controlled vocabularies than are researchers in computer science, while computer scientists are less involved in discussions of first principles (such as debating whether there are such things as fixed essences, or whether entities must be ontologically more primary than processes). During the second half of the 20th century, philosophers extensively debated the possible methods or approaches to building ontologies, without actually building any very elaborate ontologies themselves. By contrast, computer scientists were building some large and robust ontologies (such as WordNet and Cyc) with comparatively little debate over how they were built.

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(b) Let's say that we use "knowledge structure" (ontology) everywhere, but can we really do it in art experience, or, even better, religious experiences? Note that I am referencing to "experiences", not art theory/aesthetics or theology -- they can be treated as knowledge, obviously. This is just another form of the difference between reality and the representation of reality -- but more directly, and cannot be "postponed" anymore. By "postponed" I mean, in other places, for example, in technology or engineering or mathematics, or even business, we can "postpone" the differences between "reality" and "knowledge of reality" by "transforming" ("learning") "reality" to "knowledge of reality" -- it seems that it is OK that we do that -- actually, most of the time, in our more and more sophisticated world, it seems that it is the preferred way to do that -- when you do something, you must know what you are doing, do not "just do it".

However, in art it is not the case; it it even more "not the case" in the faith life (or "religious life" -- but it seems that "faith life" has a more positive tone).

It seems that knowledge and faith are not symmetric. Knowledge is a space-like, while faith is a singularity -- when you begin to talk about faith, then, the content of your talk is transformed into knowledge!

However, the singularity is the most active part of our life. Put it in another way, it is the "engine" of the "learning", and more importantly, "applying", of the huge space of knowledge -- obviously, you'd better "oil" the engine nicely!

OK, this blog is (still) a technical one, as result (and purely so), the point I am trying to make here is not about the faith life -- that is personal -- it is about "knowledge structure": except one and only one singularity that we cannot really talk (whenever we talk, it is changed into knowledge), everything is knowledge; consequently, everything can be covered by the concept of "knowledge structure". As a result, let's use "ontology" more often.