Function Decomposition Tree with Causality-First Perspective and Systematic Description of Problems in Materials Informatics
This provides a systematic way to express knowledge and facilitate communication between scientists in various fields, though it appears incremental in its approach.
The study addressed the difficulty domain scientists face in constructing function decomposition trees for interdisciplinary communication in materials informatics by proposing a causality-first decomposition tree method and an automatic conversion program, demonstrating its usefulness for systematically representing expert knowledge.
As interdisciplinary science is flourishing because of materials informatics and additional factors; a systematic way is required for expressing knowledge and facilitating communication between scientists in various fields. A function decomposition tree is such a representation, but domain scientists face difficulty in constructing it. Thus, this study cites the general problems encountered by beginners in generating function decomposition trees and proposes a new function decomposition representation method based on a causality-first perspective for resolution of these problems. The causality-first decomposition tree was obtained from a workflow expressed according to the processing sequence. Moreover, we developed a program that performed automatic conversion using the features of the causality-first decomposition trees. The proposed method was applied to materials informatics to demonstrate the systematic representation of expert knowledge and its usefullness.