Resource Event Agent (REA) Framework

This paper describes an approach, which uses formal specifications, for the classification of REA patterns and their building blocks. In general, classification is essential -especially when the number of patterns of a collection increases. Budgen [Bud03] stresses the need and importance of exploring and evaluating "the most effective ways to index and classify patterns." The number of patterns increases over time, and there is always the possibility of having either duplicate patterns or patterns whose relationships can be interpreted differently if these relationships are not clearly defined. In this short paper, we describe our approach in which REA patterns are specified formally using Alloy prior to being classified in the Zachman framework. For convenient references, these REA specifications are assigned numbers.

This paper presents a reference model for the registration of economic data that enables the tracking and tracing of product and money flows in the registered data. The model is grounded in the REA ontology, which has its origin in accounting and provides the conceptual foundation for the ISO open-edi transaction standard. The use of the reference model is illustrated with an example database that demonstrates the different usage scenarios covered by the model.

A number of modeling approaches have been proposed in the literature for designing business information systems. This paper critiques prior data modeling approaches and presents an integrated object-oriented modeling approach that captures both the structural and the behavioral aspects of the business domain. Although there is considerable interest in object-oriented (OO) technologies in practice and in the information systems literature, there is no widely accepted OO modeling approach that facilitates the identification of objects from a business information processing perspective. Based on McCarthy’s (1982) resources, events, agents (REA) framework, the business process focused object-oriented ontology presented in this paper identifies the key resources, events, and agents in an enterprise information systems context. Termed OOREA, the ontology extends McCarthy’s REA model by capturing both the structural aspects of modeling, in terms of the objects of interest in the domain, an...

Revenue Information System (RiS) is the product of a research project based on a case study on direct-selling sales point. This study is to determine the resources, events, and agents for Resource-Event-Agent (REA) data model as a technique of specifying and designing accounting information system and also to develop a system prototype based on the REA model. RiS is built based on the REA data model since it captures only essential aspects of economic phenomena. The idea is to build an information system application that supports business process in real-time and the REA data model is chosen to ease the understanding of the database. In this paper, the researchers described the approach and process in planning and performing the project transformation and conversion from the legacy information systems to the new updated information system. The researchers applied the REA model approach and process into a real case study of sales order and cash receipt systems. The result shows that REA model captures only essential aspects of economic phenomena and thus, (1) models are kept concise and easy to understand, (2) models can be used for many applications, and (3) derived artefacts are always consistent by means of the models. This new developed system has resulted in the improvement in business processes efficiency, the timely collection of cash and the provision of timely account information for decision making. Database design in business information system structured by accountants and those who are involved in the business itself will create a meaningful system as their business needs are fulfilled.

Resources -Events -Agents (REA) is the best known theoretical accounting enterprise database model, while SAP is the dominant enterprise resource-planning system. The purpose of this paper is to investigate some of the relationships between the underlying data models in REA and SAP. The criteria of Dunn and McCarthy [J. Inf. Syst. (1997) 31] for differentiating accounting systems (database orientation, semantic orientation, and structuring orientation) are used to structure a summary of those relationships.

Current Enterprise Resource Planning (ERP) systems are based on double entry bookkeeping. This technique has several disadvantages concerning application neutral financial data storage. Therefore, the Resource Event Agent (REA) ontology was introduced to negotiate the current drawbacks. It describes concepts and its relationships semantically. Nevertheless, there exist a set of different REA models that reveal several lacks in context of

This paper contains a description of an approach to formalizing REA patterns, their composition, and an analysis of the resulting product. When patterns are used in the design of business models and processes, pattern composition is an essential operation because one pattern is not usually enough to define the complete set of business models and operations. In composition, we want to ensure that the results produced implement the (business) rules that are intended. Thus, there must be a clear and unambiguous specification of patterns and their composition so questions about the combination can be accurately formulated and answered. In this brief paper, we use an example to outline our formal approach to specification, composition, and analysis of REA patterns using Alloy. We present a demonstration of how the formalism can be used to show whether the resulting policies conform to our business rules.

Current Enterprise Resource Planning (ERP) systems are based on double entry bookkeeping. This technique has several disadvantages concerning application neutral financial data storage. Therefore, the Resource Event Agent (REA) ontology was introduced to negotiate the current drawbacks. It describes concepts and its relationships semantically. Nevertheless, there exist a set of different REA models that reveal several lacks in context of formalization and specification. Although several REA approaches use formalized languages like the Unified Modeling Language (UML), they are too general to fulfill the Guidelines of Modeling. Due to these reasons, the paper adapts the SEManticbased Planning Approach (SEMPA) for a formalized REA modeling. By annotating process activities semantically, the approach emphasizes on business control. Furthermore, process activities are linked together representing all valid solutions of a process flow representing behavioral aspects of REA. The goal is to...

Business domain ontologies offer great opportunities for f acilitating communication between people in business, for improving the enterprise system engineering processes and for creating interoperabili ty between enterprise systems. However despite these opportunities, their use in practice is still limited. This can be partly attributed to the lack of formal representation of these ontologies. This paper proposes a structured approach

Companies model their business processes either for documentation, analysis, re-engineering or automation purposes; usually using normalized business process modeling languages such as EPC or BPMN. Although these models explain how the processes should be performed and by whom, they abstract away their business rationale (i.e. what is offered and why). Business modeling aims to answer the latter and different frameworks have been proposed to express the process in terms of value-chains. Ensuring alignment between both of these views manually is error prone and labor intensive. In this paper, we present a novel approach to derive a value-chain-expressed in REA-from a business process model expressed in BPMN. At the heart of our approach and our main contribution lies a set of nine general business patterns we have defined and classified as structural and behavioral patterns.

Revenue Information System (RiS) is the product of a research project based on a case study on direct-selling sales point. This study is to determine the resources, events, and agents for Resource-Event-Agent (REA) data model as a technique of specifying and designing accounting information system and also to develop a system prototype based on the REA model. RiS is built based on the REA data model since it captures only essential aspects of economic phenomena. The idea is to build an information system application that supports business process in real-time and the REA data model is chosen to ease the understanding of the database. In this paper, the researchers described the approach and process in planning and performing the project transformation and conversion from the legacy information systems to the new updated information system. The researchers applied the REA model approach and process into a real case study of sales order and cash receipt systems. The result shows that ...

This paper describes an approach, which uses formal specifications, for the classification of REA patterns and their building blocks. In general, classification is essential-especially when the number of patterns of a collection increases. Budgen [Bud03] stresses the need and importance of exploring and evaluating "the most effective ways to index and classify patterns." The number of patterns increases over time, and there is always the possibility of having either duplicate patterns or patterns whose relationships can be interpreted differently if these relationships are not clearly defined. In this short paper, we describe our approach in which REA patterns are specified formally using Alloy prior to being classified in the Zachman framework. For convenient references, these REA specifications are assigned numbers.

Abstract. Business modelling can be used as a starting point for business analysis. The core of a business model is information about resources, events, agents, and their relations. The motivation of a business model can be found in the goals of an enterprise and those are made explicit in a goal model. This paper discusses the alignment of business models with goal models and proposes a method for constructing business models based on goal models. The method assists in the design of business models that conform to the explicit ...

This paper describes an approach, which uses formal specifications, for the classification of REA patterns and their building blocks. In general, classification is essential -especially when the number of patterns of a collection increases. Budgen [Bud03] stresses the need and importance of exploring and evaluating "the most effective ways to index and classify patterns." The number of patterns increases over time, and there is always the possibility of having either duplicate patterns or patterns whose relationships can be interpreted differently if these relationships are not clearly defined. In this short paper, we describe our approach in which REA patterns are specified formally using Alloy prior to being classified in the Zachman framework. For convenient references, these REA specifications are assigned numbers.

The Resources-Events-Agents (REA) model is a semantic data model for the development and integration of conceptual schemas of accounting information systems. Although in the Accounting Information Systems literature, the REA model is proposed as a benchmark against which to evaluate newly proposed accounting data models, only few studies have been undertaken to empirically validate the claimed benefits of REA modeling.

This work furthers the work in Transaction Agent Modelling (TrAM) by merging its conceptual catalogue based on the REA (Resources-Events-Agents) accounting model with Sowa's 1984 conceptual catalogue. The merged catalogue features in a preliminary implementation of TrAM using the Amine software tool, which also offers the model-checking support that is core to TrAM. This automated process demonstrates how Conceptual Graphs (CG) might lucidly interrelate the divergent conceptual catalogues of the myriad domains in which contemporary enterprise systems operate.

This paper contains a description of an approach to formalizing REA patterns, their composition, and an analysis of the resulting product. When patterns are used in the design of business models and processes, pattern composition is an essential operation because one pattern is not usually enough to define the complete set of business models and operations. In composition, we want to ensure that the results produced implement the (business) rules that are intended. Thus, there must be a clear and unambiguous specification of patterns and their composition so questions about the combination can be accurately formulated and answered. In this brief paper, we use an example to outline our formal approach to specification, composition, and analysis of REA patterns using Alloy. We present a demonstration of how the formalism can be used to show whether the resulting policies conform to our business rules.

This paper presents a laboratory experiment that evaluates the REA approach for modelling enterprise-wide accounting information systems. REA is a pattern-driven conceptual modelling approach that is based on the Resource-Event-Agent semantic model of a company’s accountability infrastructure. Using a between-subjects experiment with business students we investigated whether Entity-Relationship (ER) diagrams that show a REA pattern occurrence are better understood than

The Resources-Events-Agents (REA) model is a semantic data model for the development and integration of conceptual schemas of accounting information systems. Although in the Accounting Information Systems literature, the REA model is proposed as a benchmark against which to evaluate newly proposed accounting data models, only few studies have been undertaken to empirically validate the claimed benefits of REA modeling. Moreover, these studies focused on REA-based accounting system implementations and not on problem space representations. The work presented in this paper addresses this gap. Starting from theoretical frameworks for conceptual model quality and method evaluation in the IS field, and from previous research on comparative analysis of data modeling formalisms, a laboratory experiment was organized to evaluate the understanding of diagrammatic conceptual schemas that are developed using the REA model. The experimental results indicate that the REA modeling of accounting systems is effective in terms of the accuracy of understanding. On the other hand, little support was found for its efficiency in terms of faster comprehension of schemas that are developed according to the REA model. outside participation outside participation inside participation 1 A description of the REA modeling process and activities can be found in .

Business frameworks offer great opportunities of communication between people for working on the enterprise system engineering processes, as well as for eliciting services that the enterprise can offer in collaboration contexts. However, these kinds of frameworks, such as Resource-Event-Agent and Open-edi, recently unified in Open-edi Business Ontology (OeBTO), lack formal representations. This fact considerably limits their use in system development, particularly in model-driven development methods where the efficiency of transformations is of great importance. In this paper we suggest a formalization of OeBTO using OMG's standard Semantics of Business Vocabulary and Business Rules (SBVR), as a method for creating a service-centric business model. This makes it possible to provide the necessary formal logic foundation to allow automatic processing of the business model and its transformation to a system-level service model. An example from the bank loan business sector is used to argument the application of the method.

Current Enterprise Resource Planning (ERP) systems are based on double entry bookkeeping. This technique has several disadvantages concerning application neutral financial data storage. Therefore, the Resource Event Agent (REA) ontology was introduced to negotiate the current drawbacks. It describes concepts and its relationships semantically. Nevertheless, there exist a set of different REA models that reveal several lacks in context of formalization and specification. Although several REA approaches use formalized languages like the Unified Modeling Language (UML), they are too general to fulfill the Guidelines of Modeling. Due to these reasons, the paper adapts the SEMantic-based Planning Approach (SEMPA) for a formalized REA modeling. By annotating process activities semantically, the approach emphasizes on business control. Furthermore, process activities are linked together representing all valid solutions of a process flow representing behavioral aspects of REA. The goal is to present a formalized approach that enables the integration of diverse REA models.

The Resources-Events-Agents (REA) model is a semantic data model for the development of enterprise information systems. Although this model has been proposed as a benchmark for enterprise information modelling, only few studies have attempted to empirically validate the claimed benefits of REA modelling. Moreover, these studies focused on the evaluation of REA-based system implementations rather than directly assessing the REA-modelled conceptual schemas that these systems are based on. This paper presents a laboratory experiment that measured the user understanding of diagrammatic conceptual schemas developed using the REA model. The theoretical foundation for the hypotheses are cognitive theories that explain pattern recognition phenomena and the resulting reduction in cognitive effort for understanding conceptual schemas. The results of the experiment indicate a more accurate understanding of the business processes and policies modelled when users recognize the REA model’s core pattern of enterprise information in the diagram. The implication for modelling practice is that the use of the REA model improves the requirements engineering process by facilitating the user validation of conceptual schemas produced by analysts, and thus helps ensuring the quality of the enterprise information system that is developed or implemented.

This paper presents a reference model for the registration of economic data that enables the tracking and tracing of product and money flows in the registered data. The model is grounded in the REA ontology, which has its origin in accounting and provides the conceptual foundation for the ISO open-edi transaction standard. The use of the reference model is illustrated with an example database that demonstrates the different usage scenarios covered by the model.