Semi-Automated Formalization and Representation of the Engineering Knowledge Extracted From Spreadsheet Data

Development of new methods and tools for formalization and representation of complex knowledge in the context of the creation of intelligent systems remains in the scope of scientific research. Modern trends aim to automate the knowledge formalization and representation by using various sources of information, in particular, spreadsheets. This paper proposes a novel approach to the semi-automatic formalization and representation of the engineering knowledge in the form of conceptual models and knowledge base codes from spreadsheet data. Our approach comprises three phases: (I) rule-driven data transformation source spreadsheet tables to a specific canonical form (data preprocessing), (II) domain knowledge formalization and representation via the extraction and aggregation of conceptual model fragments from canonicalized tables, (III) model-driven synthesizing knowledge base and source codes from a domain model. The approach is implemented by our tools: TABBYXL provides the development of a software application for the spreadsheet data canonicalization; Personal Knowledge Base Designer is used to build and aggregate conceptual models fragments, as well as to construct a target knowledge base and to generate source codes. Our case study on the industrial safety inspection (ISI) demonstrates that the approach is fully suitable for prototyping knowledge bases containing decision-making rules.