Developing ontology-based EPA for representing accounting principles in a reusable knowledge component

Abstract

This study proposed an ontological EPA model (Event, Principle and Account) for describing accounting principles using a reusable knowledge component. The essential characteristics of the model include: (1) based on traditional accounting definitions for typical accounts (A) and business events (E), where the ontological properties of A and E can be identified. These characteristics can be further used to create a knowledge hierarchy for both A and E; (2) identifies the element P (accounting principle), which in turn can be used to measure the economic effects of events on accounts; (3) creates a relationship between E–P, which identifies how to adopt suitable principles for classifying events; and (4) the inferential (E–P)–A relationship, which identifies the effect of a classified event on resources (or accounts). Following typical knowledge engineering processes, hierarchical knowledge of accounting principles can be represented, stored and reused. EPA examples are demonstrated using OWL-based ontology. This study claims that the knowledge framework developed in EPA can provide a basis for full accounting knowledge creation, storage and sharing.

Introduction

Accounting is a set of general principles and rules for representing financial information related to business activities. These principles and rules are developed and accumulated by academic professionals and practitioners to provide a source of solid accounting knowledge. The “Capitalization of expenditures” and “Revenue recognition” rules are practical examples. Human accountants use these standardized principles and rules to systematically recognize diversified business transactions, measure their monetary effects, and record and summarize those effects using a predefined taxonomy system – “chart of accounts”. Owing to accounting knowledge being a highly dependable form of expertise, modeling these principles and rules into systematic and reusable artifacts is a challenge (Stefanou, 2006). For example, in most accounting systems, accounting knowledge cannot be represented as separate logical components, but rather is hidden in thousands of lines of programs, complex algorithms and data flows. From the information system perspectives, a missing knowledge model layer can be added above a solid foundation of accounting knowledge. Consequently, this study argues that, to enhance knowledge representation capability and share core knowledge with other domains, accounting knowledge must be revisited and restructured through knowledge-intensive approaches.

To better manage accounting knowledge models, knowledge-intensive approaches such as ontology technology are suited to address knowledge reuse and sharing. The previous literatures have discussed several approaches and implementation of ontology engineering (Guarino, 1997, Uschold and Grueninger, 1996). Ontology explicitly specifies a conceptualization that expresses shared human perspectives of the real world. Ontology has long been applied to artificial intelligence and expert system to express shared human understanding of information. The advantages of using ontology in this way include permitting more disciplined design and facilitating knowledge sharing and reuse (Chi, 2007). Like most knowledge-intensive approaches, building ontology is a form of knowledge engineering that generally includes several successive processes such as knowledge acquisition, modeling, and representation (Guarino, 1995). Accordingly, the main task in building ontology is translating goal-oriented or problem-solving activities into systematic knowledge required to solve problems.

To exploit the ontology approach in building accounting knowledge, this study endeavors to identify a general process to help systematically convert accounting principles and rules into ontology. Furthermore, this study selects several important cases as a task domain to demonstrate the knowledge conversion process. Three emphases of this paper are as follows. First, this study identifies several weaknesses of traditional accounting systems in representing accounting knowledge, and then it develops the EPA model based on the ontological accounting constructs. Besides event (E) and account (A), a single add-in element P, which represents the accounting principles, serves as the association between events and accounts. This study uses a separate and hierarchical design of accounting principles to demonstrate that most valuable accounting knowledge can be represented, stored and reused. Secondly, to demonstrate the construct validity of EPA model, this study adopts Web Ontology Language-Description Logic (OWL-DL) to create a set of reusable classes, representing key accounting principles, including revenue and expense recognition, matching principle and capitalization of expenditure, and so on. Thirdly, during the validation stage, this study employs the Protégé platform to generate instances of classes to serve as competency questions, and adopts the Pellet as an inference engine for testing the knowledge validity of the EPA. The ontology instances empirically suggest that the EPA model can enhance the semantic representation capability in modeling accounting principles, and the knowledge model can be further applied to describe more complex principles and rules developed in accounting.

This study presents a feasible approach to modeling accounting knowledge, which offers an alternative to building a practical knowledge base or expert system. This study proposes that larger projects can adopt the EPA model to complete more comprehensive bases of accounting knowledge.