Wim Laurier

Positioning and Formalizing the REA Enterprise Ontology.

ABSTRACT: Recent Resource, Event, Agent (REA) research has focused on defining and theoretically justifying the ontologys contents. Here, we elaborate on more practical issues related to REA. First, we classify REA and its applications using ontology classification schemes and application frameworks. This analysis clarifies REAs application potential but also reveals weaknesses that may impede its operationalization. Next, we propose a new REA ontology specification that uses a Unified Modeling Language (UML) profile for graphically representing ontologies. This new specification is more complete and precise than previously available specifications, without compromising understandability. It can easily be transformed into a machine‐readable representation for automatic processing, which is a prerequisite for the successful application of REA in business modeling, software engineering, knowledge representation, and interoperability creation. The paper ends with a proof of concept application in which a f...

Invariant conditions in value system simulation models

This paper presents a framework for the integration of supply chain (or logistics/distribution), value chain (or financial), and business process (or operational/manufacturing) simulation models, which should facilitate assessing the impact of supply chain and operational changes on an enterprises financial performance. A Design Science approach is taken to demonstrate that the REA ontology, which provides a shared conceptual ground for these three model types, and its axioms, which describe invariant conditions for value systems, can help to build conceptually sound simulation models and identify the integration points between these models. It is further shown how these three types of simulation models can be integrated into one value system model for discrete event simulation, making use of the ExSpecT simulation tool. With this ontology-based framework, simulation model builders should be able to scope their models better and define integration points with other models, which is expected to promote the (re)use of simulation models for different purposes (e.g., simulating logistical, operational and financial performance). Defining the scope of business process, supply and value chain simulation modelsRephrasing the REA modeling axioms for each of these types of simulation modelsIdentifying integration points between these models through the REA ontologyIntegrating these three types of models into a hierarchic value system modelFirst application of the REA ontology for building discrete-event simulation models

Simulating Liquidity in Value and Supply Chains

This paper provides an ontology-based set of Petri-nets for simulating the effect of business process changes on an organisation’s liquidity, and demonstrates that certain types of business process redesign can increase or reduce the amount of external funding that is required to prevent an organisation from defaulting on its debt. This debt defaulting may lead to proliferating liquidity constraints for subsequent supply chain partners. Consequently, this paper provides a proper toolkit for assessing and mitigating the propagation of liquidity constraints in supply chains. The paper uses the accounting-based Resource-Event-Agent ontology to create workflow patterns for modelling exchanges between supply chain partners and for the value chains that represent an organisation’s internal processes. Both the exchange and internal processes continuously convert money into resources and vice versa. These models for money to resource and resource to money conversions are then used for constructing supply chain models for liquidity modelling and analysis.

The Value of Ontology

It is generally accepted that the creation of added value requires collaboration inside and between organizations. Collaboration requires sharing knowledge (e.g., a shared understanding of business processes) between trading partners and between colleagues. It is on the (unique) knowledge that is shared between and created by colleagues that organizations build their competitive advantage. To take full advantage of this knowledge, it should be disseminated as widely as possible within an organization. Nonaka distinguished tacit knowledge, which is personal, context specific, and not so easy to communicate (e.g., intuitions, unarticulated mental models, embodied technological skills), from explicit knowledge, which is meaningful information articulated in clear language, including numbers and diagrams. Tacit knowledge can be disseminated through socialization (e.g., face-to-face communication, sharing experiences), which implies a reduced dissemination speed, or can be externalized , which is the conversion of tacit into explicit knowledge. Although explicit knowledge can take many forms (e.g., business (process) models, manuals), this chapter focuses on ontologies, which are versatile knowledge artifacts created through externalization, with the power to fuel Nonaka’s knowledge spiral. Nonaka’s knowledge spiral visualizes how a body of unique corporate knowledge, and hence a competitive advantage, is developed through a collaborative and iterative knowledge creation process that involves iterative cycles of externalization, combination, and internalization. When corporate knowledge is documented with ontology, a knowledge spiral leads to ontology evolution.

An Enterprise Ontology Based Conceptual Modeling Grammar for Representing Value Chain and Supply Chain Scripts

In business modeling the focus is shifting from individual enterprises to the supply chains in which they col- laborate. Contemporary business modeling grammars should allow each enterprise taking part in a supply chain to develop its own information system and at the same time support the creation of system interoperability and information sharing amongst business partners in the supply chain. This paper presents a conceptual modeling grammar for representing business scripts in a way that is both observer-dependent and independent. That is, value chain information should be represented in a format that is suitable for the perspective of any partner in the supply chain (e.g., enterprise, supplier, customer, customer’s customer, supplier’s supplier) and for the perspective of a completely neutral third party (e.g., government). The proposed observer-independent conceptual-modeling grammar, which is given strength by grounding it in the mature Resource-Event-Agent model, is shown to represent information about business phenomena of diverse supply chain partners such that it can be integrated across enterprise boundaries

A Simulation Model Articulation of the REA Ontology

This paper demonstrates how the REA enterprise ontology can be used to construct simulation models for business processes, value chains and collaboration spaces in supply chains. These models support various high-level and operational management simulation applications, e.g. the analysis of enterprise sustainability and day-to-day planning. First, the basic constructs of the REA ontology and the ExSpect modelling language for simulation are introduced. Second, collaboration space, value chain and business process models and their conceptual dependencies are shown, using the ExSpect language. Third, an exhibit demonstrates the use of value chain models in predicting the financial performance of an enterprise.

The BPM Ontology

This chapter introduces the BPM ontology that can be applied within the area of process modelling, process engineering and process architecture. At the highest level by providing the fundamental process concepts that are used to document corporate knowledge. At the lowest level by structuring the process knowledge itself in defining its relations.

Conceptual Structures in LEADing and Best Enterprise Practices

Conceptual Structures, namely Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are beginning to make an impact in Industry. This is evidenced in LEAD as it seeks to provide its 3100+ industry practitioners in many Fortune 500 and public organisations with capabilities that can handle ontology and semantics. The existing ontology and semantics work in LEAD, supported by the Global University Alliance, is described and how CGs, FCA and their tools (e.g. CoGui, CG-FCA) enhance this endeavour.

Rewiring Strategies for Changing Environments

A typical pervasive application executes in a changing environment: people, computing resources, software services and network connections come and go continuously. A robust pervasive application needs adapt to this changing context as long as there is an appropriate rewiring strategy that guarantees correct behavior. We combine the MERODE modeling methodology with the ReWiRe framework for creating interactive pervasive applications that can cope with changing environments. The core of our approach is a consistent environment model, which is essential to create (re)configurable context-aware pervasive applications. We aggregate different ontologies that provide the required semantics to describe almost any target environment. We present a case study that shows a interactive pervasive application for media access that incorporates parental control on media content and can migrate between devices. The application builds upon models of the run-time environment represented as system states for dedicated rewiring strategies.