An overview of BORO Foundational Ontology’s Meta-ontological Choices. This covers:

• Background - BORO as an extensional ontology for business systems
• The context for metaphysical choices
• How does philosophy characterise the different metaphysics? Metaphysics through the eyes of philosophy textbooks
• BORO’s metaphysical choices
• Top level patterns - that emerge as a result of the choices
• Re-engineering the companies house data - an example of the re-engineering process assocaited with the choices
• Company - an example of the result of the choices
• Higher order types - one of BORO's metaphysical choices

Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the “one and the many.” Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor’s work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus to the ISE literature. The literature survey follows the evolution of ISE’s understanding of how to formalize the classification pattern. The various proposals are assessed using the classical example of classification; the Linnaean taxonomy formalized using powersets as a benchmark for formal expressiveness. The broad conclusion of the survey is that (1) the ISE community is currently in the early stages of the process of understanding how to formalize the classification pattern, particularly in the requirements for expressiveness exemplified by powersets, and (2) that there is an opportunity to intervene and speed up the process of adoption by clarifying this expressiveness. Given the central place that the classification pattern has in domain modeling, this intervention has the potential to lead to significant improvements.

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.

With re-engineering of software systems becoming quite pronounced amongst organisations, a software stability approach is required to balance the seemingly contradictory goals of stability over the software lifecycle with the need for adaptability, extensibility and interoperability. This paper addresses the issue of how software stability can be achieved over time by outlining an approach to evolving General Business Patterns (GBPs) from the empirical data contained within legacy systems. GBPs are patterns of business objects that are (directionally) stable across contexts of use. The approach is rooted in developing patterns by extracting the business knowledge embedded in existing software systems. The process of developing this business knowledge is done via the careful use of ontology, which provides a way to reap the benefits of clear semantic expression. A worked example is presented to show how stability is achieved via a process of ‘interpretation’ and ‘sophistication’. The outcome of the process demonstrates how the balance that stability seeks can be achieved.

Several foundational ontologies have been developed recently. We examine two of these from the point of view of their quality in representing temporal changes, focusing on the example of roles. We discuss how these are modelled in two foundational ontologies: the Unified Foundational Ontology and the BORO foundational ontology. These exhibit two different approaches, endurantist and perdurantist respectively. We illustrate the differences using a running example in the university student domain, wherein one individual is not only a registered student but also, for part of this period, was elected the President of the Student Union. The metaphysical choices made by UFO and BORO lead to different representations of roles. Two key differences which affect the way roles are modelled are exemplified in this paper: (1) different criteria of identity and (2) differences in the way individual objects extend over time and possible worlds. These differences impact upon the quality of the models produced in terms of their respective explanatory power. The UFO model concentrates on the notion of validity in “all possible worlds” and is unable to accurately represent the way particulars are extended in time. The perdurantist approach is best able to describe temporal changes wherein roles are spatio-temporal extents of individuals.

Contracts are fundamental toward characterising the very nature of a firm (or enterprise). The firm is considered by some economic theories as a bundle of contracts and contracts in turn are considered also as bundles of rights and obligations (commitments). As such it can be argued that the ontological relationships between the firm and its contracts an be explained through a set of mereological (or whole-part) relationships. Specifically, the relationships between a contract and its parties and between the parties and their rights/commitments are all mereological. This view of what contracts are may appear at first surprising but a perdurantist interpretation of contracts results in such an ontology. The main contribution of this paper is a perdurantist ontology of contracts which introduces the following distinctive features: (1) a differentiation between contract specification and contract execution, (2) contract executions as objects whose spatio-temporal extents intersect those of its parties and (3) a generic model of contractual commitments and fulfilment events impacting the economics of the enterprise. The ontology proposed in this paper is applied to an example scenario to demonstrate its benefits in enterprise modelling.