Augmented Intensional Reasoning in Knowledge-Based Accounting Systems

Abstract

A limitation of existing accounting systems is their lack of knowledge sharing and knowledge reuse, which makes the design and implementation of new accounting systems time-consuming and expensive. An important requirement for knowledge sharing and reuse is the existence of a common semantic infrastructure. In this article we use McCarthy's (1982) Resource-Event-Agent (REA) model as a common semantic infrastructure in an accounting context. The objective is to make knowledge-intensive use of REA to share accounting concepts across functional boundaries and to reuse these concepts in different applications and different systems, an approach we call augmented intensional reasoning. Intensional reasoning is the active use of conceptual structures in information systems operations such as design and information retrieval. For augmented intensional reasoning, the conceptual structures are extended with domain-specific REA knowledge. Sections II and III describe different dimensions of augmented intensional reasoning: the REA primitives, the technological features needed to support augmented intensional reasoning, the need for epistemologically adequate representations to make augmented intensional reasoning feasible, and the practical necessity of implementation compromises. Sections IV and V explore two uses of augmented intensional reasoning: design and operation of knowledge-based accounting systems. The example in Section V explains how augmented intensional reasoning works: (1) define the conceptual schema, (2) structure the conceptual schema in terms of REA (knowledge augmentation), (3) define a shareable and reusable accounting concept (claim), and (4) use the concept (claim) to derive information in different accounting cycles (revenue and acquisition).

REA2: A unified formalisation of the Resource-Event-Agent ontology

“…To a minor extent, we will also focus on the design cycle by presenting an artefact -namely the exemplar -that will serve as our proof of concept and allow for a scenario-based analysis of our approach presented shortly. This paper addresses research rigour by refactoring the Prolog 1 code found in Geerts and McCarthy (2000a) with notions from the REA formalisation developed by Gailly, Laurier and Poels (2008). That formalism is stereotyped in turn with OntoUML stereotypes (Guizzardi, 2014) instead of OWL stereotypes, and notions from the original ResourceEvent-Agent (REA) data model published by McCarthy (1982) and Hruby et al's (2006) book on REA.…”

“…The exemplar is a set of statements written in Prolog able to transform dependent view Prolog statements into independent view Prolog statements and vice-versa. To emphasise this paper's embedding in the REA literature, the code in Appendix C and E also shows how an opposing and independent perspective could be derived from Geerts' and McCarthy's (2000a) code. These reference older REA artefacts but nonetheless illustrate this paper's embedding of REA's design science tradition; the illustration is accordingly reinforced by an informed argument.…”

“…Since the duality axiom requires inflow and outflow semantics, it depends on the perspective of a trading-partner. The compliance of data with the duality axiom thus cannot be verified without reference to the perspective of a specific trading-partner (Geerts and McCarthy, 2000a;2005).…”

“…The code can be found in the Appendix. Since the code covers the entire value chain, it is more elaborate than the Prolog code in Geerts and McCarthy's (2000a) intensional reasoning paper, which exclusively covers the revenue cycle. The test scenario will be introduced and visualised in the remainder of this section.…”

“…This alternative independent view has no access restrictions, which means that all persons can access the information, and includes transformation roles and relators in its vocabulary, which means that traceability of product components is enabled through the publication of production transformation processes. Finally, in order prove that the approach presented above can be applied to traditional REA data, Appendix E tests whether an independent and opposing dependent view can be derived from the Prolog code found in Geerts and McCarthy's (2000a) intensional reasoning paper. The relevant 9 part of Geert's and McCarthy's Prolog code can be found in Appendix C. Appendix E demonstrates that the logic introduced in this paper can transform dependent view data into independent view data that can in turn be transformed into the dependent view of a trading-partner with an opposing perspective (i.e., the other trading-partner).…”