Updated August 9, 2019 (Original post October 23, 2014): To enable the definition of physical deliverables (Physical Assets) in a flexible manner, the concept of Asset Unit is needed (to be covered in a separate post). An Asset Unit combines: (i) a variable Asset Scale (e.g. a component, an assembly, a building, or a whole city) derived from the Asset Hierarchy (see below), with (ii) an Asset List defined by the Demand Entity (Employer, Client, Appointing Party) within an Information Cycle (a list of assets to be designed delivered, and/or utilised), and (iii) Asset Attributes derived from the Conceptual (BIM) Ontology (e.g. Asset Function, Asset Location, and Asset Cost).

Asset Hierarchy – v2.0, 2018 (full size image) - Link to older version (v1, 2011) 

The Asset Hierarchy organises Physical Deliverables/Assets by relative scale by combining taxonomies developed by OSCRE[1] and Transport for North South Wales[2]. The diagram does not differentiate between assets – Buildings as a sample scale - by their size, monetary value, location, or designated function[3] - e.g. Cultural, Transportation, or Recreation[4] but by their granularity relative to each other. The diagram includes a numbering system (scale 10-70) to establish an Asset’s relative position on the scale. The diagram also highlights how:

• The Assets Scale bridges the semantic and informational divide between three complementary industries and their respective information domains. At the upper-end of the scale, the Geospatial Industry and its Geographic Information System (GIS) domain overlaps with the Construction Industry and its BIM domain; while at the lower-end of the scale, it overlaps with the Manufacturing Industry and its Product Lifecycle Management (PLM) domain[5].
• An Asset can be a member of three Asset Clusters:
  • An Asset Portfolio (scale 300) is a clustering of assets for the purposes of strategic investment, operation, and management. Asset Portfolios may also be referred to as ‘asset groupings’ or ‘asset systems’[6];
  • A Modular Assembly (scale 500) is a functional clustering of assets for the purposes of Design for Manufacturing and Assembly (DfMA) and similar offsite methods. Examples of Modular Assemblies and Sub-Assemblies include prefabricated houses, pre-assembled mechanical risers, and pre-constructed wall sections[7]. Treated as a single Asset Unit, a Modular Assembly can be (a) first developed and tested in digital space; (b) prototyped, manufactured, constructed, and/or pre-assembled offsite; (c) packaged and readied for transportation; (d) transported for storage on site or delivered Just-In-Time (JIT); and (e) unpacked, erected, and/or assembled; and
  • A Temporary Package (scale 700) is a clustering of assets for the purposes of transportation and storage logistics. Examples of Temporary Packages include standardised shipping containers and logistical package[8]. Temporary Packages also include bundled materials (e.g. a sandbag, load, or palette).
• Systems are treated as dynamic sub-scales that – depending on the Physical Asset being measured – may be more/less granular than other assets. Systems span the entire hierarchy (from scale 15 to 65) and can flexibly connect information deliverables and requirements across the BIM, GIS, and PLM domains.

Using a variable Asset Scale allows the dynamic assignment of less granular assets at the start of an information cycle. More information about how Asset Scales and Asset Units are used will be explained in future posts.

[1] Fuhrman, A. (2007). The Hybrid Taxonomy Real Estate Focus, The Open Standards Consortium for Real Estate (OSCRE).

[2] TfNSW. (2015). Systems Engineering, Transport for NSW, New South Wales Government (T MU AM 06006 GU). Retrieved from https://www.transport.nsw.gov.au/system/files/media/asa_standards/2017/t-mu-am-06006-st-v2.0.pdf Last accessed Aug 9, 2019

[3] Assets can be classified under many concepts which should not be combined in a single taxonomy. Information Actors will need to identify the number of classifications needed to manage their asset information. For example, an Information Actor may use three primary classifications to identify a Physical Asset: Asset Scale (e,g. Lighting System), Asset Function (Lighting), and Asset Location (e.g. In Room 391 or along Highway A5, Exit Ramp 17).

[4] OmniClass. (2013). OmniClass | Construction Classification System, Retrieved from http://www.omniclass.org/; and NBS. (2015). UniClass 2015 (1.7 ed.). Retrieved from https://buildig.com/uniclass-2015/ Last accessed Aug 9, 2019.

[5] Overlaps between the BIM and GIS/PLM domains are well-covered in: Song, Y., Wang, X., Tan, Y., Wu, P., Sutrisna, M., Cheng, J. C., & Hampson, K. (2017). Trends and Opportunities of BIM-GIS Integration in the Architecture, Engineering and Construction Industry: A Review from a Spatio-Temporal Statistical Perspective. ISPRS International Journal of Geo-Information, 6(12), 397; and in Jupp, J. R., & Singh, V. (2014). Similar concepts, distinct solutions, common problems: learning from PLM and BIM deployment. Paper presented at the IFIP International Conference on Product Lifecycle Management.

[6] ISO. (2014). ISO 55000:2014 Asset management - Overview, principles and terminology. Retrieved from https://www.iso.org/standard/55088.html Last accessed Aug 9, 2019

[7] BWTL. (2018). Platforms Bridging the gap between construction + manufacturing, Brydon Wood Technology Limited (BWTL) for the Centre for Digital Built Britain (CDBB), University of Cambridge. Retrieved from https://www.cdbb.cam.ac.uk/system/files/documents/2018Platforms_Bridgingthegapbetweenconstructionandmanufacturing.pdf Last accessed Aug 9, 2019

[8] Saghir, M. (2004). The concept of packaging logistics. Paper presented at the Proceedings of the Fifteenth Annual POMS Conference, Cancun, April.

This conceptual model (Figure 1) identifies nine BIM player groups (industry stakeholders) distributed across three BIM Fields (technology, process and policy) as defined within the BIM Framework. The nine player groups are: policy makers, educational institutions, construction organisations, individual practitioners, technology developers, technology service providers, industry associations, communities of practice, and technology advocates.

Figure 1. Macro Diffusion Responsibilities v1.0 (full size, current version)

The nine player groups belong to either BIM Field or their overlaps. Pending further research, the tenth player group at the intersection of the three fields is intentionally excluded from this model. Table 1 below provides a succinct description of each player group followed by how this subdivision can be used in evaluating BIM diffusion within and across different markets.

Table 1. Macro Diffusion Responsibilities matrix (player groups with sample players – market scale)

Each of the nine player groups identified in Figure 1 includes a number of player types. For example, player group 3 (construction organisations) is composed of varied player types including: asset owners, architects, engineers and project managers. Also, player group 4 (individual practitioners) is composed of professionals, associated professionals and tradespeople. These distinctions between player groups, player types and unique players (e.g. a specific person, group, association, company or university) allow the targeted assessment and comparison of stakeholders’ involvement.

Below is a short video explaining the above, as available on the Framework's YouTube channel:

Please note that the above model and table are part of five macro adoption models collated within "Succar, B., & Kassem, M. (2015). Macro-BIM adoption: Conceptual structures. Automation in Construction, 57, 64-79". Download full paper from here: http://bit.ly/BIMPaperA8

The BIM Framework Conceptual Reactor v1.0 (full size, current version)

The BIM Framework Conceptual Reactor explains how existing conceptual constructs – terms, classifications, taxonomies, models and frameworks – are used to identify, explain and test new constructs.

The conceptual reactor thus allows the BIM framework to be continuously extended according to evolved research aims and objectives - represented as input 1 (or 'in1'). By integrating existing conceptual structures (in2) with new knowledge gained through literature reviews, and data collection (in3), the reactor can then generate new conceptual structures (output or ‘out’) after passing through an iterative, three-stage theory-building process. This process has been identified by J. Meredith (1993) (J. R. Meredith, Raturi, Amoako-Gyampah, & Kaplan, 1989) and includes three repetitive stages - description, explanation and testing:

• First, the Description Stage develops a description of reality; identifies phenomena; explores events; and documents findings and behaviours;
• Second, the Explanation Stage builds upon descriptions to infer a concept, a conceptual relationship or a construct; and then, develops a framework or a theory to explain and/or predict behaviours or events. In essence, the explaining stage develops a testable theoretical proposition which clarifies what has previously been described; and
• Third, the Testing Stage inspects explanations and propositions for validity; tests concepts or their relationships for accuracy; and tests predictions against new observables.

The Point of Adoption (PoA) model is a distillation of three implementation phases: readiness, capability, and maturity. As a term, PoA identifies the juncture(s) where organizational readiness transforms into organizational capability/maturity. It also identifies the juncture(s) where technological invention and a procedural innovation transforms into organizational - as well as market wide - diffusion:

Point of Adoption model v1.1 (full size, current version)

As explored in Figure 1 above, transformative BIM adoption starts at the Point of Adoption (PoA) when an organization, after a period of planning and preparation (readiness), successfully adopts object-based modelling tools and workflows. The PoA[1] thus marks the initial capability jump from no BIM abilities (pre-BIM status) to minimum BIM capability (Stage 1). As the adopter interacts with other adopters, a second capability jump (Stage 2) marks the organization’s ability to successfully engage in model-based collaboration. Also, as the organisation starts to engage with multiple stakeholders across the supply chain, a third capability jump (Stage 3) is necessary to benefit from integrated, network-based tools, processes and protocols (refer back to BIM Stages).

Each of these capability jumps is preceded with considerable investment in human and physical resources, and each stage signals new organizational abilities and deliverables not available before the jump. However, the deliverables of different organizations at the same stage may vary in quality, repeatability and predictability (refer to BIM Maturity Index). This variance in performance excellence occurs as organizations climb their respective BIM maturity curve, experience their internal BIM diffusion, and gradually improve their performance over time[2].

The multiple maturity curves depicted in Figure 1 reflect the heterogeneous nature of BIM adoption even within the same organization (e.g. sample Organization X) has a compiled rating of 1c, 2b and 3a). This is due to the phased nature of BIM with each revolutionary stage requiring its own readiness ramp, capability jump, maturity climb, and point of adoption. This is also due to varied abilities across organizational sub-units and project teams: while organizational unit A1 (within Organization A) may have elevated model-based collaboration capabilities, unit A2 may have basic modelling capabilities, and unit A3 may still be preparing to implement BIM software tools. This variance in ability necessitates a compiled rating for organization A as it simultaneously prepares for an innovative solution, implements a system/process, and continually improves its performance.

Update (May, 2016): below is a short video explaining the above on the Framework's YouTube channel:

This conceptual model (Figure 1) clarifies how BIM Field types (technology, process and policy) interact with BIM Capability Stages (modelling, collaboration and integration) to generate nine areas for targeted BIM diffusion analysis and BIM diffusion planning:

Figure 1. Diffusion Areas model v1.0 (full size, current version)

The nine diffusion areas, explored in the below table, can be assessed independently or collectively. For example, the diffusion of BIM software tools within a population (modelling technologies [1TE]) can be assessed separately, and using different assessment methods, than establishing the proliferation of integrated project delivery contracts (integration policies [3PO]). Also, the diffusion of multidisciplinary BIM educational curricula (collaboration policies [2PO]) can be assessed separately, or in combination with, the proliferation of collaborative BIM roles and responsibilities (collaboration processes [2PR]).

Table 1. Diffusion Areas matrix (with sample granular metrics within each diffusion area)

The nine diffusion areas, their structured subdivisions and combinations, provide an opportunity for granular assessments of BIM diffusion within a population of adopters. Rather than being treated uniformly as a single set of data, or separated into disparate topics without an underlying conceptual structure, the Diffusion Areas’ model (Figure 1) allows the generation of targeted ratings for comparative market analysis - as exemplified in Figure 2:

Figure 2. Diffusion Areas Comparison sample chart v1.1 - updated April 24, 2016  (full size, current version)

Below is a short video explaining the above, as available on the Framework's YouTube channel:

Please note that the above model, table and chart are part of five macro adoption models collated within "Succar, B., & Kassem, M. (2015). Macro-BIM adoption: Conceptual structures. Automation in Construction, 57, 64-79". Download full paper from here: http://bit.ly/BIMPaperA8

Research Continuum v1.1 (partial, showing sample relations | Full Size - 1.1Mb)

The Research Continuum v1.1 represents a network of conceptual and practical deliverables across a number of papers till December 2013 (model to be updated in 2016). The continuum highlights how each paper delivers a number of conceptual constructs which either extend earlier constructs/tools or support the development of new ones. Constructs are hierarchical  - frameworks, models, taxonomies, classifications and dictionary terms - yet interconnect through explicit ontological relations. At the bottom of the image are sample Knowledge Tools TL1-TL5 (e.g. TL4 is the online BIM Dictionary) which are dependent on these conceptual constructs. 

Updated 19 July 2016: The continuum clarifies how the BIM Maturity Matrix (TL2 - a practical tool introduced in Paper A3 and later released in a number of  languages) is dependent on several models (e.g. MD7-MD9), which are in-turn ontologically-connected to a number of taxonomies, classifications and dictionary terms.

Full Size Image (Research Path v1.3 - 378 kb) 

The Research Path identifies the major milestones along four research sub-paths: literature review, research methodology, conceptual development and data collection. This visual knowledge model (VKM) also identifies a number of ongoing research activities pursuant to each research sub-path. 

Note: the importance of a clearly defined research path cannot be understated. However, allowing oneself to diverge into inter-connected sub-paths (a network of tunnels dug underneath the main topic) is an excellent mechanism for knowledge exploration and discovery.

Conceptual Hierarchy Current Version, full-size image (older version v1.0)

The BIM framework is composed of several interrelated conceptual constructs: models, taxonomies, classifications and dictionaries. A common conceptual ontology connects all conceptual constructs and makes explicit the relationship between them. Below is a generic description of the depicted conceptual parts:

Frameworks show “the gestalt, the structure, the anatomy or the morphology of a field of knowledge or the links between seemingly disparate fields or sub-disciplines” (Reisman, 1994, p. 92).

Models (conceptual models) are simplified representations and abstractions of the “enormous richness of this world” (Ritter, 2010, p. 360) (Lave & March, 1993).

Taxonomies are an efficient and effective way to organize and consolidate knowledge (Reisman, 2005) (Hedden, 2010). A well-structured taxonomy allows “the meaningful clustering of experience” (Kwasnik, 1999, p. 24).

Classifications are the “meaningful clustering of experience” (Kwasnik, 1999, p. 24) and “lies at the heart of every scientific field” (Lohse, Biolsi, Walker, & Rueter, 1994, p. 36). Classification is also a heuristic tool useful during the formative stages of discovery, analysis and theorizing (Davies, 1989).

Dictionaries constitute a web of meaning (Cristea, 2004) connecting terms to each other and to other knowledge bases.

Macro Maturity Components  - v1.2 full size (500Kb),  older version 1.1 (277Kb)

Also Available in Italian

The Macro Maturity Components model (upadated Nov 17, 2014) identifies eight complementary components for measuring and establishing the relative and absolute BIM maturity of Macro Organizational Scales (Market, Defined Market and Sub-Market). The eight components are:

1. Objectives, stages and milestones
2. Champions and drivers
3. Regulatory framework
4. Noteworthy publications
5. Learning and education
6. Measurements and benchmarks
7. Standardised parts and deliverables
8. Technology infrastructure

The components are measured individually and collectively using the BIM Maturity Index (BIMMI) which includes 5 levels: (a) initial/ad-hoc, (b) defined, (c) managed, (d) integrated, and (e) optimised.

Note: the Macro Maturity Components model is discussed in BIM ThinkSpace Episode 22 (published Jan 27, 2015).

This conceptual model represents BIM learning as a triangular interaction between BIM learners, BIM learning providers and the BIM learning spectrum.

BIM learners

BIM learners are all individuals pursuing knowledge, skill or expertise in BIM technologies or workflows. BIM learners include practitioners and future practitioners; within any Design, Construction and Operation discipline; and at any position or role.

BIM learning providers

BIM learning providers are commercial and not-for-profit entities providing formal or informal BIM education, training or professional development. BIM learning providers include individual trainers, registered training organizations, universities, vocational institutions, industry association and communities of practice.

BIM learning spectrum

The BIM learning spectrum includes all BIM topics that can be learned by BIM learners or taught by BIM learning providers. The learning spectrum represents both structured and unstructured information, including well-defined, classified and aggregated BIM competency items.