The conceptual modelling community has no clear, agreed semantics for its models; or more plainly, there is no general agreement on what the models model. One mainstream proposal is that they model concepts, but there is no clear semantics for this; no clear description of what concepts are and how they relate to their domain. This creates theoretical problems; for example, it is difficult to build accurate meta-models, as these have to encompass the semantic structure. It also creates practical problems; practitioners will approach building a model of the concept of a business differently from modelling the business itself. We aim to exploit research undertaken in philosophy to construct a framework that classifies the broad semantic options. Using this we identify two major options: concept-mediated and direct-domain semantics. We focus on the concept-mediated option and examine how philosophy has analysed what a concept is; identifying three main options and exploring the issues they raise. While not wishing to advocate choices at this stage, we note that the concept-mediated view - in particular, the version prevalent in conceptual modelling, that concepts are representations – faces serious challenges as a practical semantics for modelling and languages.

This tutorial presents an introduction to the BORO methodology, an ontology-based systems engineering approach. The authors present both the ontological foundations of the approach as well as business examples of the application of this approach.

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.

The purpose of this paper is to establish the nature of the need for a new accounting conceptual scheme and provide the framework for taking a managed approach to this change. This paper firstly reviews the nature of the need for a radical shift in the foundations and framework of accounting’s conceptual scheme. It touches upon how the existing uses of ontological analysis within accounting information systems research do not address this need. It then outlines how a more philosophical approach to ontological analysis provides a process for starting the shift in the foundation. And illustrates how the process will work with some examples.

The 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 workshop 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 work explains, via a small worked example, how stability is achieved via a process of ‘sophistication’. The outcome of the process demonstrates how the balance that stability seeks can be achieved.

The organizational environment increasingly demands that computer-based information systems are responsive to change and can work with each other seamlessly (ideally from a dynamic perspective). Given the large investment that organizations have in mission-critical legacy systems, evolutionary maintenance and systems integration now form a very significant part of the cost and effort profile of systems development. In terms of the integration issue, much of the difficulty lies in the fact that different systems often contain different ‘representations’ of the world. In the development process, it is generally accepted that the ‘information’ an information system contains about its business domain(s) is an essential intellectual part of the system, and the domain of fundamental concern. This concern is generally regarded as unitary, however, requiring no further breakdown into parts and it is commonly perceived that its relation to the business information system is simple and direct.

This paper examines the development of a conceptual model that defines Shell’s information requirements - the Downstream Data Model (DDM). The model has its roots in a framework based on the notion of ontological commitment and the focus of the analysis seeks to provide useful insights into the metaphysical aspects relevant to the creation and deployment of the DDM – primarily that related to the extensional nature of the model. The impact of this choice and the methodology employed in the production of the model is examined through example patterns covering spatial and temporal dissectiveness and the use of powerclasses. Having been through the experience of conceptual model development, the work concludes that the separation of the implementational and epistemological ‘gloss’ from a studied understanding of ontological commitment is a necessary evolution of practice in conceptual modelling.

When we embed the building of an ontology into an information system development or maintenance process, then the question arises as to how one should construct the content of the ontology. One of the choices is whether the construction process should focus on the mining of the ontology from existing resources or should be the result of speculation (‘starting with a blank sheet of paper’). I present some arguments for choosing mining over speculation and then look at the implications this has for legacy modernisation.

An overview of 42 Objects' approach to Business Ontology Based Software Development that aims to secure a measure of agreement on:

• What philosophical ontology is,
• Whether, and how, ontology can assist in object oriented software development,
• What philosophical ontology can add to the debate on the mapping between objects in the real world and system objects,
• What the key obstacles to the deployment of ontology are

More and more enterprises are currently undertaking projects to integrate their applications. They are finding that one of the more difficult tasks facing them is determining how the data from one application matches semantically with the other applications. Currently there are few methodologies for undertaking this task – most commercial projects just rely on experience and intuition. Taking semantically heterogeneous databases as the prototypical situation, this paper describes how ontology (in the traditional metaphysical sense) can contribute to delivering a more efficient and effective process of matching by providing a framework for the analysis, and so the basis for a methodology. It delivers not only a better process for matching, but the process also gives a better result. This paper describes a couple of examples of this: how the analysis encourages a kind of generalisation that reduces complexity. Finally, it suggests that the benefits are not just restricted to individual integration projects: that the process produces models which can be used as to construct a universal reference ontology – for general use in a variety of types of projects.

From the perspective of enterprise computing, ontology is seen as a kind detached pure science. When enterprise computing ventures into ontological topics it does not look to ontology to provide it with theories - it devises its own theory-lite solutions. This keynote aims to make a case for joining up these two by identifying an area where enterprise computing can usefully apply ontological theory. It does this using an example; immutability, a current concern in big data. It argues that ontology’s theories about change, in particular McTaggart’s analysis of ways of viewing time in terms of series, provide a strong explanatory framework for enterprise computing’s immutability and have the potential to lead to better solutions. This approach also reveals that there is an aspect of change in computing systems – the epistemic aspect – where a mutable approach (McTaggart’s Series A) provides a better explanatory framework.

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.