In this UML Activity Diagram, I propose a reconstruction of the scientific “business” process using the following Aristotelian (384-322 BC) concepts elaborated in the works Physics, Metaphysics, Posterior Analytics, related to psychology (see [1.3.6]), logic (see [1.3.9]), and scientific inquiry:
- sense perception
- observation
- memory
- induction (epagôgê)
- generalization
- intuition
- first things (archai) or priori, premise, hipothesis
- deduction, syllogism (sullogismos ) (see [1.3.9])
- causation (aition); four causes (material, efficient, formal, final) (see [1.3.4])
- knowledge (which is about universal, necessary things with identified causes) (epistemê)
| Activity | Action/Description |
| Start | |
| Careful OBSERVATION | • Sense-perception of object • Store & Recollect the facts |
| Inference using INDUCTION | “it is induction (epagôgê), or at any rate a cognitive process that moves from particulars to their generalizations, that is the basis of knowledge of the indemonstrable first principles of science.” (R. Smith) • Organize the facts • Sort out irrelevant facts • Generalization • Use bottom-up syllogism: “there is an induction as a kind of syllogism. We can describe it as a bottom-up syllogism. Induction in this sense means finding out an appropriate middle term where both extreme terms are given” (R. Smith) • Identify first things (archai; a priori; premise; hypothesis) with the help of intuition |
| Inference using DEDUCTION | “A deduction is speech (logos) in which, certain things having been supposed, something different from those supposed results of necessity because of their being so. Each of the “things supposed” is a premise (protasis) of the argument, and what “results of necessity” is the conclusion (sumperasma).” (R. Smith) In Aristotle’s model, there is no observational/experimental verification of the knowledge (loop back to the beginning of the process). • Generate new knowledge using dialectical syllogism • Identify the Four Causes with demonstrative syllogism (apodeixis): “The demonstrative syllogism, (apódixis) which produces genuine knowledge, science or epistemé, does not aim to lead from premises to a conclusion up to then unknown. On the contrary, in the demonstrative syllogism, also, the conclusion is an observed fact previously known. The scientific explanation, the reason why, the (dióti), or “cause”, will when found form the premise from which that observed fact can be demonstrated as a conclusion. Thus the scientific syllogism derives facts already known through observation, from reasons why, or archai. It is not a logic of the discovery of new facts, but a logic of proof, of formalizing or systematizing facts already known.” (S. Sfekas) • Record Scientific knowledge (episteme) |
| End |
NOTE: This is the first UML Activity Diagram I present on this blog. For modelling business processes there is an alternative standard also in use: BPMN, (Business Process Model and Notation) managed also by OMG.
Sources:
- Andersen, Hanne and Hepburn, Brian, “Scientific Method“, The Stanford Encyclopedia of Philosophy (Summer 2016 Edition), Edward N. Zalta (ed.)
- Galik, Dusan. “Induction in Aristotle’s System of Scientific Knowledge”. Organon F. 13. 495-505., 2006
- S. Sfekas: Aristotelian Fundamentals of the Practice of Knowledge and Information, conference paper, 2017
- Shields, Christopher, “Aristotle’s Psychology“, The Stanford Encyclopedia of Philosophy (Winter 2016 Edition), Edward N. Zalta (ed.)
- Smith, Robin, “Aristotle’s Logic“, The Stanford Encyclopedia of Philosophy (Winter 2018 Edition), Edward N. Zalta (ed.)
First published: 18/04/2019
Philosophy Models 