This section provides a specific, hypothetical example of how the partial schema described in the previous section would contribute to the
development of a greyfield precinct. The PIM, based on an open data model, is a formal definition of the information content for a precinct-level model. As such a PIM aggregates, as well as is inclusive of, the detailed constituent entities that make up a precinct.
Figure 5.6 is a diagrammatic representation of a greyfield redevelopment. The base layer shows an out-dated shopping mall surrounded by a sea of grey asphalt (the car park) on the southern edge of a town centre. In this example, a mixed use redevelopment of this precinct is proposed. An information model of the precinct should include everything relevant to its planning, operation and maintenance – if not as one integrated model, at least in parts that potentially can be read together since each is constructed against a common information schema (data definition).
Performance Assessment of Urban Precinct Design: A Scoping Study 99 For the proposed infill development, there is an existing context made up of
objects about which much is known. There are physical entities – buildings, car parking, streets, and landscape elements. These can be deconstructed in information terms into their component assemblies, made up of manufactured products, and ultimately composed from quantities of various materials. In the case where some of these entities are to be removed to make way for the new infill development, the quantity and composition of waste created can be accurately calculated. With reference to the partial PIM shown in Figure 5.5, the buildings are BuiltFacility entities, the streets are TransportNetwork entities, the carparking and landscape elements are ManMadeLandscape entities, and the existing services (energy and water reticulation) are
UtilityNetwork entities. The identified precinct to be developed is a ProjectZone – note that in this sense, a precinct is an arbitrary designated
area on which to carry out the proposed project. The ProjectZone may be contained wholly within another type of zone (for example a CensusZone or an AdministrativeZone such as a local government area), or it may overlap several of these. Where reference data is only available relative to local government areas, and the ProjectZone overlaps more than one of those areas, an approximation will be required to calculate an appropriate proportion of the reference value from each reference source to be the value for the
ProjectZone for that characteristic.
Properties of these entities, including geometric representation, may be attached at this gross level (the definition of a core set of relevant properties should be an integral part of the ongoing detailed definition of the PIM). For some levels of analysis (and simulation) this level of information granularity may be sufficient. For example, the “look” of a building can be achieved by attaching a picture (texture map) to a simple geometric mass – a technique used by some existing urban simulation software, particularly where movement through the urban precinct is part of the user interface (and therefore, restricting the number of geometric primitives is important for efficient scene rendering performance). However, in a situation where one or more of the existing buildings has previously been modelled using BIM, or there is an identified need to more closely integrate the new buildings with the existing, and therefore it is decided to create a BIM model for part or all of that existing building, these more detailed entities can be aggregated against the broad PIM entities. Entities at the detail building level include walls, slabs, roofs, doors, windows, spaces. Again, these entities may have geometric representations and other properties. Especially for the low carbon precinct- level assessment agenda, it will be important to define a common set of properties against these entities from which the sustainability metrics can be consistently derived and aggregated. As discussed in Chapter 4, LCI data could be organised to be referenced in a bottom-up fashion – in this example, that would be applicable where detailed material/product/assembly
information is available such as for one or more of the existing buildings against which to aggregate quantities of materials used times relevant index value for each material. Or, for the proposed development, that data could be applied as an approximated (aggregated) index value times the quantity (square metres) of a given usage type (residential, retail etc.) or, alternatively, times the quantity of the proposed construction type(s).
Since a greyfield development of this type could have ongoing socio-political ramifications, when communicating with the affected stakeholders in the project – owners, existing tenants, neighbours and municipal authorities – the proponents of the infill development need to be careful to present their analyses and findings in a transparent and verifiable manner. This transparency has a number of implications for a proposed PIM. Is the reference data used applicable in this situation? And, are the calculations made using that data based on formulae which are certified or independently provable? One of the tasks for the development of the PIM schema is to assess the need to provide an entity to contain such a formula within the formal schema (as MUtopia have done in their data model).
There are also virtual entities interwoven in this precinct information model. The shopping mall contains tenancies (both in a legal and a geometrically bounded sense) and these are contained within one or more cadastral lots. A
Performance Assessment of Urban Precinct Design: A Scoping Study 100 history of energy and water use for these tenancies exists. A history of rental
returns exists. A history of changes in occupancy and usage exists. Before any planning redevelopment starts, there are existing planning controls in place – land use zones, and planning envelopes (floor space ratios, building heights and setbacks).
Furthermore, for the proposal, there are stages in its planning containing entities at different levels of resolution. The planning starts with usage layouts (zones), then indicative 3D urban form (block masses). From there it
progresses through detailed design (product assemblies), construction (schedules), etc. At each stage, carbon and other assessments are possible only if appropriately granular reference data and benchmarks are available relative to the quantification of entities at the same level of detail (that is, “trustworthiness”). In information modelling terms, there is a progression from existing entities with attributes indicating their current and required states, through entity types, to individual entity instances. For example, a planning zone entity with attributes for land usage (residential) and proposed population (2000 persons), in a next design iteration develops to the instantiation of residential dwelling typologies (attached, detached, multi- dwelling) with quantities for each, and then to the placement of all the individual instances of those dwellings onto cadastral lots. These instances at this stage are still “fuzzily-defined placeholders” for the subsequent individual dwelling designs which follow. In addition, planning and design is not a linear process. Early in the proposal, there may be a number of competing options (or scenarios). Unlike IFC, which currently only has the capability to
“snapshot” a single design at a point in time, it is important for the PIM to include the concept of a scenario, since very early in the planning of the proposed infill development the design is fluid and we may simultaneously be carrying multiple design versions to be assessed and communicated in parallel for a period of time.
The planning and development and construction process can be lengthy, particularly for greyfield sites where financial investment and returns are often tied to incremental staging, and over this whole period there can be many handovers of responsibility for the ongoing information “bank” associated with that development. This means that it is important to include another type of virtual entity in the consideration of an overall PIM. These entities are those concerned with “intent” and include such concepts as “targets” and
“constraints” which act as indicators of design and performance intent for subsequent participants in the development chain. For example, the mixed- use proposal is flagged to achieve a 6-star sustainability rating. At the broad masterplanning level the scheme has been assessed as meeting this target, but this will need to be revisited as more is progressively decided regarding the characteristics of the scheme, and ultimately tested five or ten years after occupation. The target remains as an integral part of the information model, not as an ephemeral by-product. These “intent” entities are instantiated around, and linked into, the contextual physical and virtual entities which exist in the model at a given point in time. They inform the “process” of the
development.
What this example tries to show is that the conceptual model (the PIM) is an open data definition, independent of the software tools used to create, manipulate, and utilise/view the entities modelled. The intention of a PIM is that there is a seamless integration of relevant information (conceptually integrated even if physically disaggregated) across all the various scales and viewpoints – there is a place and a semantic context for each piece of information against which a whole range of general purpose, as well as specialised, software can interoperate.