In the multi-level type modeling community, claims that most enterprise application systems use ontologically multi-level types are ubiquitous. To be able to empirically verify this claim one needs to be able to expose the (often underlying) ontological structure and show that it does, indeed, make a commitment to multi-level types. We have not been able to find any published data showing this being done. From a top-level ontology requirements perspective, checking this multi-level type claim is worthwhile. If the datasets for which the top-level ontology is required are ontologically committed to multi-level types, then this is a requirement for the top-level ontology. In this paper, we both present some empirical evidence that this ubiquitous claim is correct as well as describing the process we used to expose the underlying ontological commitments and examine them. We describe how we use the bCLEARer process to analyse the UNICLASS classifications making their implicit ontological commitments explicit. We show how this reveals the requirements for two general ontological commitments; higher-order types and first-class relations. This establishes a requirement for a top-level ontology that includes the UNICLASS classification to be able to accommodate these requirements. From a multi-level type perspective, we have established that the bCLEARer entification process can identify underlying ontological commitments to multi-level type that do not exist in the surface linguistic structure. So, we have a process that we can reuse on other datasets and application systems to help empirically verify the claim that ontological multi-level types are ubiquitous.

The Centre for Digital Built Britain has been tasked through the Digital Framework Task Group to develop an Information Management Framework (IMF) to support the development of a National Digital Twin (NDT) as set out in “The Pathway to an Information Management Framework” (Hetherington, 2020). A key component of the IMF is a Foundation Data Model (FDM), built upon a top-level ontology (TLO), as a basis for ensuring consistent data across the NDT.

This document captures the results collected from a broad survey of top-level ontologies, conducted by the IMF technical team. It focuses on the core ontological choices made in their foundations and the pragmatic engineering consequences these have on how the ontologies can be applied and further scaled. This document will provide the basis for discussions on a suitable TLO for the FDM. It is also expected that these top-level ontologies will provide a resource whose components can be harvested and adapted for inclusion in the FDM.

Following the publication of this document, the programme will perform a structured assessment of the TLOs identified herein, with a view to selecting one or more TLOs that will form the kernel around which the FDM will evolve. A further report – The FDM TLO Selection Paper – will be issued to describe this process in late 2020.

The review of existing industry data models and reference data libraries will support the development of the National Digital Twin Information Management Framework. The review will have different roles during the development. The envisaged roles are as follows:

- existing industry data models and reference data libraries are identified

- the structure of the models and libraries is summarised

- the extensibility of the models is described

- the documentation of the models is described

- the maintenance and usage of the models is described

Component breakdowns are a vital multi-purpose tool and hence ubiquitous across a range of disciplines. Information systems need to be capable of storing reasonably accurate representations of these breakdowns. Most current information systems have been designed around specific breakdowns, without considering their general underlying formal structure. This is understandable, given the focus on devising the breakdown and that there is not a readily available formal structure to build upon. We make a step towards providing this structure here.

At the core of the notion of a component breakdown is the component as an integral (dependent) part of the composite whole. This leads to a rich formal structure, one that requires careful consideration to capture well enough to support the range of specific breakdowns. If one is not sufficiently aware of this structure, it is difficult to determine what is required to produce a reasonably accurate representation – in particular, one that is sufficiently accurate to support interoperability.

In this report, enabled by the Construction Innovation Hub, we describe this rich formal structure and develop a framework for assessing how well a data model (or ontology) has captured the main elements of the structure. This will enable people to both assess existing models as well as design new models. As a separate exercise, as an illustration, we develop a data model that captures these elements.

Associated with the notion of component (as an integral, dependent part) is the notion of replaceable part (see Appendix A for more details). We do not characterise this here but will do so in a later report.