An Ontological Approach for Recovering Legacy Business Content

Legacy Information Systems (LIS) pose a challenge for many organizations. On one hand, LIS are viewed as aging systems needing replacement; on the other hand, years of accumulated business knowledge have made these systems mission-critical. Current approaches however are often criticized for being overtly dependent on technology and ignoring the business knowledge which resides within LIS. In this light, this paper proposes a means of capturing the business knowledge in a technology agnostic manner and transforming it in a way that reaps the benefits of clear semantic expression – this transformation is achieved via the careful use of ontology. The approach called Content Sophistication (CS) aims to provide a model of the business that more closely adheres to the semantics and relationships of objects existing in the real world. The approach is illustrated via an example taken from a case study concerning the renovation of a large financial system and the outcome of the approach results in technology agnostic models that show improvements along several dimensions.

BORO as a Foundation to Enterprise Ontology

Modern business organizations experience increasing challenges in the development and evolution of their enterprise systems. Typical problems include legacy re-engineering, systems integration/interoperability, and the architecting of the enterprise. At the heart of all these problems is enterprise modeling. Many enterprise modeling approaches have been proposed in the literature with some based on ontology. Few however adopt a foundational ontology to underpin a range of enterprise models in a consistent and coherent manner. Fewer still take data-driven re-engineering as their natural starting point for modeling. This is the approach taken by Business Object Reference Ontology (BORO). It has two closely intertwined components: a foundational ontology and a re-engineering methodology. These were originally developed for the re-engineering of enterprise systems and subsequently evolved into approaches to enterprise architecture and systems integration. Together these components are used to systematically unearth reusable and generalized business patterns from existing data. Most of these patterns have been developed for the enterprise context and have been successfully applied in several commercial projects within the financial, defense, and oil and gas industries. BORO's foundational ontology is grounded in philosophy and its metaontological choices (including perdurantism, extensionalism, and possible worlds) follow well-established theories. BORO's re-engineering methodology is rooted in the philosophical notion of grounding; it emerged from the practice of deploying its foundational ontology and has been refined over the last 25 years. This paper presents BORO and its application to enterprise modeling.

Guidelines for Developing Ontological Architectures in Modelling and Simulation

This book is motivated by the belief that “a better understanding of ontology, epistemology, and teleology” is essential for enabling Modelling and Simulation (M&S) systems to reach the next level of ‘intelligence’. This chapter focuses on one broad category of M&S systems where the connection is more concrete; ones where building an ontology – and, we shall suggest, an epistemology – as an integrated part of their design will enable them to reach the next level of ‘intelligence’. Within the M&S community, this use of ontology is at an early stage; so there is not yet a clear picture of what this will look like. In particular, there is little or no guidance on the kind of ontological architecture that is needed to bring the expected benefits. This chapter aims to provide guidance by outlining some major concerns that shape the ontology and the options for resolving them. The hope is that paying attention to these concerns during design will lead to a better quality architecture, and so enable more ‘intelligent’ systems. It is also hoped that understanding these concerns will lead to a better understanding of the role of ontology in M&S.