Digitalization and reasoning over engineering textual data stored in spreadsheet tables

Abstract

Much textual engineering knowledge is captured in tables, particularly in spreadsheets and in documents such as equipment manuals. To leverage the benefits of artificial intelligence requires industry to find ways of extracting the data and relationships captured in these tables. This paper demonstrates the application of an ontological approach to make explicit the classes and relations held in spreadsheet tables. Ontologies offer a pathway, as they are used to define machine-interpretable definitions of shared concepts, and relations between concepts, using formal descriptions. We illustrate this with a case study on a Failure Modes and Effects Analysis (FMEA) table, using an example from the IEC 60812 FMEA Standard. Our example demonstrates how the relationship between rows and columns in a table can be represented in logic. Further, we give relationships in the FMEA and asset hierarchy spreadsheets an explicit representation, so that OWL-DL reasoning can infer final failure effects at the system level from component failures. The prototype ontologies described in this paper are modular and aligned to a Top Level Ontology, and hence can be applied to other use cases. Our contribution is to show engineers needing to make data captured in spreadsheet tables machine readable, how ontologies can be applied using a real example.