IV. Knowledge Sets

Knowledge Sets are higher order Knowledge Objects composed of the other three lower order concepts, relations and attributes.

Table 5. Knowledge Sets (4 sets in v3.1, last updated July 28, 2016)

Publication Log - Summary 

References

Cottam, H. (1999). Ontologies to Assist Process Oriented Knowledge Acquisition (Draft). Retrieved from http://www.inovexadvancedsolutions.ltd.uk/spede/default.htm

Gruber, T. R. (1995). Toward principles for the design of ontologies used for knowledge sharing? International journal of human-computer studies, 43(5-6), 907-928.  Retrieved from http://www.sciencedirect.com/science/article/B6WGR-45NJJDF-K/2/b47f5cb67315c76b60ac39f44e0a2cec

Milton, N. R. (2007a). Knowledge Acquisition in Practice: A Step-by-step Guide: Springer, London.

Milton, N. R. (2007b). Specification for the General Technological Ontology (GTO). http://www.pcpack.co.uk/gto/notes/files/GTO%20Spec%20v4.doc Retrieved from http://www.pcpack.co.uk/gto/notes/files/GTO%20Spec%20v4.doc

Noy, N. F., & McGuinness, D. L. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. http://www.lsi.upc.edu/~bejar/aia/aia-web/ontology101.pdf Retrieved from http://www.lsi.upc.edu/~bejar/aia/aia-web/ontology101.pdf

Shanks, G., Tansley, E., & Weber, R. (2003). Using ontology to validate conceptual models. Communications of the ACM, 46(10), 85-89. doi:10.1145/944217.944244

Studer, R., Benjamins, V. R., & Fensel, D. (1998). Knowledge engineering: Principles and methods. Data & Knowledge Engineering, 25(1-2), 161-197.  Retrieved from http://www.sciencedirect.com/science/article/B6TYX-3SYXJ6S-G/2/67ea511f5600d90a74999a9fef47ac98

Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in Construction, 18(3), 357-375.  Retrieved from http://dx.doi.org/10.1016/j.autcon.2008.10.003

Succar, B., Sher, W., & Aranda-Mena, G. (2007). A Proposed Framework to Investigate Building Information Modelling Through Knowledge Elicitation and Visual Models. Paper presented at the Australasian Universities Building Education (AUBEA2007), Melbourne, Australia. http://aubea.org.au/ocs/viewpaper.php?id=15&cf=1

Lenses and Filters are investigative tools of enquiry and domain analysis allowing the discovery of concepts and relations. The difference between (BIM) Lenses and Filters can be summarised as such: Lenses are additive and are deployed from the ‘investigator’s side’ of BIM Field observation while Filters are subtractive and are deployed from the ‘data side’. Lenses highlight observables that meet research criteria and identify their relations; example, an infrared lens highlights heat sources in a scene. Filters remove observables that do not meet the research criteria; example, data filters hides non-conforming data within a spreadsheet.

Updated April 18, 2014... BIM Capability Sets is a taxonomy representing BIM Player’s abilities to satisfy a BIM Requirement or generate a BIM Deliverable. A BIM Capability Set is a hierarchical collection of BIM abilities identified using the BIM Framework ( (refer to Structure of BIM Capability Sets) for the purposes of BIM implementation and assessment. 

Please note that the term BIM Capability Sets is used for staged capability improvement at Organizational Scales 1-10 (thus excludes OScales 12 Individual and 11 Group). It should not be confused with the BIM Competency Hierarchy (with Competency Tiers, Competency Sets and Competency Topics), the taxonomy used for contiuous performance improvement at OScales 9-12.

Building information models (note Models not Modelling) are a collection of objects represent ing physical elements like doors, columns and their host spaces. BIModels encapsulate a level of machine ‘intelligence’ in how these objects and spaces relate to each other.

Fig.1 Project Lifecycle Phases, and sub-phases 

Fig.2 Effect of BIM on Project Lifecycle Phases

Construction projects pass through three major Project Lifecycle Phases (PLP)s: Design [D], Construction [C] and Operations [O]. These phases are also subdivided into sub-phases which are in turn further subdivided into activities, sub-activities and tasks. This conceptual model (Fig. 2) depicts the effects of BIM on project lifecycle phases over the three BIM Stages.

The three BIM Fields overlap as they share players and deliverables. This overlap between fields occurs when:

(1) A deliverable requires players from two or more fields. For example, the development and  implementation of Industry Foundation Classes (IFC) across the construction industry require the joint efforts of Policy players (researchers and policy makers) and Technology players (software developers).

(2) Players pertaining to one field generate deliverables classified in another. For example, the Australian Institute of Architects is an ‘industry body’ whose members are Process players (architects) generating Policy deliverables (guidelines and best practices) rather than Process deliverables (building designs and construction details).

Legend: the letters within the model correspond to the following overlaps:

(a) Sample Policy-Process overlap: Industry body (BIM player) and Continuous Professional Development (CPD) training (BIM deliverable);

(b) Sample Policy-Technology overlap: Interoperability standards (BIM deliverable);

(c) Sample Process-Technology overlap: Communities of Practice  (BIM player); and

(d) Sample Policy-Process-Technology overlap: BIM Implementation (BIM deliverable), BIM specialists – individuals and groups (BIM players). 

BIM Interactions are push-pull knowledge transactions occurring within or between BIM Fields and sub-Fields. Push mechanisms transfer knowledge to another field or sub-field while pull mechanisms transfer knowledge to satisfy a request by another field or sub-field. Sample transactions include data transfers, team dynamics and contractual relationships between fields and sub-fields.

One of the easiest ways to explain the meaning of BIM to non-specialists is by flipping the term around from Building Information Modelling (BIM) to modelling information to perform a function related to buildings. The functional use of information is later formalised through the term Model Uses and represented by the Model Use Wheel.

BIM Lenses represent the third dimension of the Tri-Axial Model and generate its depth of enquiry. BIM Lenses are distinctive layers of analysis applied to Fields and Stages to generate Knowledge Views. They abstract the BIM domain and control its complexity by removing unnecessary detail. Lenses allow domain researchers to selectively focus on any aspect of the DCO industry and generate knowledge views that either (a) highlight observables which meet the research criteria or (b) filter out those that do not.

Below is a short video briefly explaining the above on the dedicated BIM Framework YouTube channel:

The BIM Framework introduces the stages separating Pre-BIM (the status before BIM) from viDCO (virtually integrated Design, Construction and Operation) - the ultimate vision from implementing BIM. These revolutionary stages, and the evolutionary steps separating them, are intended to both clarify and measure BIM adoption.

Note 1: this model depicts BIM Capability Stages at Maturity Level C...Also, starting in Paper A4, the term viDCO replaces the term IPD as used earlier in Papers A2 and A3

Note 2: The ‘BIM Stages’ model was first introduced by the author through BIM ThinkSpace (Episode 8 – Feb 18, 2008) and then published in Paper A2 as ‘BIM Maturity Stages’. As of Paper A3, the BIM capability/maturity concept embedded in the original model was split into two metrics/models: BIM Capability Stages and BIM Maturity Levels.

Update (July, 2015) - below is a short video explaining the above on the Framework's YouTube channel: