Authors:
Juliette Mattioli
1
;
Dominique Tachet
2
;
Fabien Tschirhart
2
;
Henri Sohier
3
;
Loic Cantat
3
and
Boris Robert
3
;
4
Affiliations:
1
Thales, France
;
2
IRT SystemX, France
;
3
IRT SystemmX, France
;
4
IRT Saint Exupery, France
Keyword(s):
Body-of-Knowledge, Knowledge Graph, Knowledge Extraction, Knowledge Fusion, ML Engineering.
Abstract:
A body of knowledge (BoK) can be defined as the comprehensive set of concepts, terminology, standards, and activities that facilitate the dissemination of knowledge about a specific field, providing guidance for practice or work. This paper presents a methodology for the construction of a body of knowledge (BoK) based on knowledge-based artificial intelligence. The process begins with the identification of relevant documents and data, which are then used to capture concepts, standards, best practices, and state-of-the-art. These knowledge items are then fused into a knowledge graph, and finally, query capacities are provided. The overall process of knowledge collection, storage, and retrieval is implemented with the objective of supporting a trustworthy machine learning (ML) end-to-end engineering methodology, through the ML Engineering BoK.