One reason oil and gas companies adopt a standard cost coding system is to facilitate benchmarking. NORSOK Z-014 Standard Cost Coding System (SCCS) is an example of this kind of system. This paper describes a set of issues found in a project that attempted to adopt this standard. These were issues whose analysis revealed problems with the standard’s fundamental structure. Further analysis showed that these types of problems are well understood outside the project controls community and resolvable using a classification technique technically known as ‘facets’. The paper provides examples of these issues and indicates how they can be resolved. It also describes the systematic modernization approach adopted by the project to resolve the issues throughout the standard. The aim of this paper is to introduce to the project controls community an understanding of the importance of these issues for raising the quality of their data and the new techniques to provide improved foundations for standard cost coding systems for the oil and gas industry in the 21st Century.

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.

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.

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.

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

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.

One of the central concerns of the multi-level modelling (MLM) community is the hierarchy of classifications that appear in conceptual models; what these are, how they are linked and how they should be organised into levels and modelled. Though there has been significant work done in this area, we believe that it could be enhanced by introducing a systematic way to investigate the ontological nature and requirements that underlie the frameworks and tools proposed by the community to support MLM (such as Orthogonal Classification Architecture and Melanee). In this paper, we introduce a key component for the investigation and understanding of the ontological requirements, an ontological sandbox. This is a conceptual framework for investigating and comparing multiple variations of possible ontologies – without having to commit to any of them – isolated from a full commitment to any foundational ontology. We discuss the sandbox framework as well as walking through an example of how it can be used to investigate a simple ontology. The example, despite its simplicity, illustrates how the constructional approach can help to expose and explain the metaphysical structures used in ontologies, and so reveal the underlying nature of MLM levelling.

The presentation introduces BORO Solution’s commercial work.

Data integration of enterprise systems typically involves combining heterogeneous data residing in different sources into a unified, homogeneous whole. This heterogeneity takes many forms and there are all sorts of significant practical and theoretical challenges to managing this, particularly at the semantic level. In this paper, we consider a type of semantic heterogeneity that is common in Model Driven Architecture (MDA) Computation Independent Models (CIM); one that arises due to the data’s dependence upon the system it resides in. There seems to be no relevant work on this topic in Conceptual Modelling, so we draw upon research done in philosophy and linguistics on formalizing pure indexicals – ‘I’, ‘here’ and ‘now’ – also known as de se (Latin ‘of oneself’) or the deitic centre. This reveals firstly that the core dependency is essential when the system is agentive and the rest of the dependency can be designed away. In the context of MDA, this suggests a natural architectural layering; where a new concern ‘system dependence’ is introduced and used to divide the CIM model into two parts; a system independent ontology model and a system dependent agentology model. We also show how this dependence complicates the integration process – but, interestingly, not reuse in the same context. We explain how this complication usually provides good pragmatic reasons for maximizing the ontology content in an ‘Ontology First’, or ‘Ontology then Agentology’ approach.

Double entry bookkeeping lies at the core of modern accounting. It is shaped by a fundamental conceptual pattern; a design decision that was popularised by Pacioli some 500 years ago and subsequently institutionalised into accounting practice and systems. Debits and credits are core components of this conceptual pattern. This paper suggests that a different conceptual pattern, one that does not have debits and credits as its components, may be more suited to some modern accounting information systems. It makes the case by looking at two conceptual design choices that permeate the Pacioli pattern; de se and directional terms - leading to a de se directional conceptual pattern. It suggests alternative design choices - de re and non-directional terms, leading to a de re non-directional conceptual pattern - have some advantages in modern complex, computer-based, business environments.

A major challenge faced in the deployment of collaborating unmanned vehicles is enabling the semantic interoperability of sensor data. One aspect of this, where there is significant opportunity for improvement, is characterizing the coordinate systems for sensed position data. We are involved in a proof of concept project that addresses this challenge through a foundational conceptual model using a constructional approach based upon the BORO Foundational Ontology. The model reveals the characteristics as sets of options for configuring the coordinate systems. This paper examines how these options involve, ontologically, ascending levels. It identifies two types of levels, the well-known type levels and the less wellknown tuple/relation levels.

We aim to lay the basis for a unified architecture for enterprise computer nomenclatures by providing the grounding ontology based upon the BORO Foundational Ontology. We start to lower two significant barriers within the computing community to making progress in this area; a lack of a broad appreciation of the nature and practice of nomenclature and a lack of recognition of some specific technical, philosophical issues that nomenclatures raise. We provide an overview of the grounding ontology and how it can be implemented in a system. We focus on the issue that arises when tokens lead to the overlap of the represented domain and its system representation – system-domain-overlap – and how this can be resolved.

We aim to lay the basis for a unified architecture for nomenclatures in enterprise computer systems by providing the grounding for an ontology of en-terprise computing nomenclatures within a foundational ontology. We look at the way in which nomenclatures are tools both shaped by and shaping the prevailing technology. In the era of printing technology, nomenclatures in lists and tables were ‘paper tools’ deployed alongside scientific taxonomic and bureaucratic clas-sifications. These tools were subsequently embedded in computer enterprise sys-tems. In this paper we develop an ontology that can be used as a basis for nomen-clature ‘computer tools’ engineered for computing technology.

The multi-level modelling community’s raison d'être is its vision of the ubiquity and importance of multi-level-types: the ascending levelled hierarchy of types in conceptual models; starting with types of things, then types of these types, then types of these types of types, and so on. The community both promotes this vision and investigates this hierarchy, looking at how it can be accommodated into existing frameworks. In this paper, we consider a specific domain, coordinate systems’ characterising options. While we recognise that, unsurprisingly, this domain contains a ubiquity of multi-level-types, our interest is in investigating a new and different approach to understanding them. For this we needed to develop a new framework. We devise one focussing on this case, based upon scaling down to simple compositional algorithms (called constructors) to form a new, radically simpler foundation. From the simple operations of these constructors emerges the scaled up multi-level structures of the domain. We show how the simple operations of simple constructors give rise to compositional connections that shape – and so explain – different complex hierarchies and levels, including the familiar multi-level-types and relatively unknown multi-level-tuples. The framework crystallises these connections as metaphysical grounding relations. We look at how simple differences in the shape and operation of constructors give rise to different varieties of these hierarchies and levels – and the impact this has. We also look at how the constructional approach reveals the differences between foundational constructors and derived constructors built from the foundational constructors – and show that conceptual modeling’s generalisation relations are secondary and dependent upon the more foundational instantiation relations. Based upon this, we assemble a constructional foundational ontology using the BORO Foundational Ontology as our starting point. We then use this to reveal and explain the formal levels and hierarchies that underlie the options for characterising coordinate systems.

This presentation introduces the survey of top-level ontologies. It provides an overview of the context in which it was produced and reviews its contents.

Presentation Structure:

1. Context
2. Candidate Top-level Ontologies
3. Assessment Framework
4. Summary