Are Conceptual Models Concept Models?

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.

Ontology-Driven Re-engineering of Business Systems

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.

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.

Shifting the ontological foundations of accounting’s conceptual scheme

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.

Software Stability:

Recovering General Patterns of Business

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 Challenge of Epistemic Divergence in IS Development

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.

Enterprise Data Modelling:

Developing an Ontology-Based Framework for the Shell Downstream Business

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.

Ontology Mining versus Ontology Speculation

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.

Setting the Scene:

42 Objects Business Ontology Based Software Development

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

The Role of Ontology in Semantic Integration

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.

Ontology meets Big Data:

Immutability

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.

Re-engineering Data with 4D Ontologies and Graph Databases

The amount of data that is being made available on the Web is increasing. This provides business organisations with the opportunity to acquire large datasets in order to offer novel information services or to better market existing products and services. Much of this data is now publicly available (e.g., thanks to initiatives such as Open Government Data). The challenge from a corporate perspective is to make sense of the third party data and transform it so that it can more easily integrate with their existing corporate data or with datasets with a different provenance. This paper presents research-in-progress aimed at semantically transforming raw data on U.K. registered companies. The approach adopted is based on BORO (a 4D foundational ontology and re-engineering method) and the target technological platform is Neo4J (a graph database). The primary challenges encountered are (1) re-engineering the raw data into a 4D ontology and (2) representing the 4D ontology into a graph database. The paper will discuss such challenges and explain the transformation process that is currently being adopted.

Grounding for Ontological Architecture Quality:

Metaphysical Choices

Information systems (IS) are getting larger and more complex, becoming ‘gargantuan’. IS practices have not evolved in step to handle the development and maintenance of these gargantuan systems, leading to a variety of quality issues. The community recognises that they need to develop an appropriate organising architecture and are making significant efforts. Examples include the System Engineering Modeling Language (SysML), the Reference Model for Open Distributed Processing (RM-ODP) and 4+1 Architectural Blueprints. Most of these follow IEEE 1471-2000’s recommendation to use view models. We believe that these efforts are missing a key component – an information grounding view. In this paper, we firstly describe this view. Then we suggest a way to provide an architecture for it – foundational ontologies – and a way of assessing them – metaphysical choices. We illustrate how the metaphysical choices are made and how this can affect information modelling.

Report from the ECOOP 2004 Workshop on Philosophy, Ontology, and Information Systems

The workshop aimed at providing a forum to discuss the use of philosophical ontology in object-oriented information systems. Whilst ontology is now more widely used in computing circles – knowledge representation, system integration, legacy transformation, and the semantic web for example – initial attempts have been modest in their outcomes. This is because computing ontology to-date has been used primarily for (often competing) concept definitions: Pragmatically, ontologies have either been developed in an abstract sense (based on some authorative perspective), or people have taken materials at hand (data models and the like) and tried to glue them together. A sound basis on which to properly align different views on aspects of the world in order to work towards a consistent whole is missing. With this in mind, the workshop aimed to secure a measure of agreement on:

  • What philosophical ontology is,
  • How ontology can assist in software development,
  • Key obstacles to the deployment of ontology, and
  • Possible collaborative efforts among the participants.

Selection of participants was based on short position papers and/or previously demonstrated interest in related areas of activity.
The title of this report should be referenced as “Report from the ECOOP 2004 Workshop on Philosophy, Ontology, and Information Systems”.

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.

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