VINE

Purpose – Modelling complex knowledge resources can be problematical as there is currently no formalism that can represent the nature of the data-seeking process at a conceptual level. The purpose of this paper is to develop a knowledge representation formalism, the functional entity relationship diagram (FERD), which comprises a set of extensions to the industry standard entity relationship diagram established by Chen.

Design/methodology/approach – The research uses a design science approach to extend the existing ER formalism using the question-answering (QA) paradigm. It is an extension of standard data modelling theory and is consistent with category theory.

Findings – The authors defined the functional entity, an encapsulated data resource that acts as a QA system and enumerated a typology of nine functional entities generated from two established principles to produce a modelling framework that can depict all existentially quantifiable relations, and demonstrated a satisficing extension to that framework (non-Aristotelian functional entities) for those situations that do not permit such relations. Further, the authors discussed the system of knowledge mixins for qualifying the relations, and presented an adjunct to the framework, cartographic functional entities, to permit formally verifiable documentation.

Research limitations/implications – Future research will address the pragmatic/sociological dimensions of FERD modelling, and test its utility in field case studies.

Practical implications – The FERD conceptualisation incorporates traditional IS modelling as one aspect of a richer modelling system, and thereby includes all of traditional IS repositories as first class, unmediated sources of knowledge. The establishment of standard types of functional entities can provide a framework for the methodical conversion of the declarative design level to the imperative implementation level. It thus has significant practical implications for the management and use of knowledge in organisations.

Originality/value – The research is original and provides a valuable contribution to conceptual modelling and representation of complex knowledge systems.