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1. 1 Big Ideas in Building Information Modeling (BIM) Core ideas, not software-product hype Curated by Ian Smith, EPFL, Lausanne Switzerland and Robert Amor, University of Auckland, New Zealand

2. 2 Contributors Fernanda Leite , UT Austin Burcu Akinci, CMU Timo Hartmann, TU Berlin Robert Amor, University of Auckland

3. 3 What is BIM? A working definition. Building Information Modeling (BIM) involves … the creation and maintenance of a digital representation of physical and functional characteristics of a facility. BIM results in a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life-cycle; defined as existing from earliest conception to demolition.  For the purpose of these slides BIM is an act, not a noun. Also, a facility is a building, industrial plant, road, bridge, tower, tunnel and any other element of civil infrastructure, either vertical or horizontal.

4. 4 What are the core ideas in BIM? Answering this question involves separating technological details and software dependent aspects from fundamental challenges. This can be facilitated by responding to the following questions: What are the fundamental challenges of BIM in the context of the field of information science? What challenges are present in BIM regardless of the software that is used? The goal of these slides is to present ideas that form the basic challenges in BIM. In this module, they are called “Big Ideas”. Each idea is then expanded through responding to the following questions What are the opportunities and risks? Are there needs for future research? While such ideas may support formulation of future research agendas, a more immediate goal is to help ensure the quality of practical implementations.

5. 5 How does knowledge of fundamentals improve practical implementations? Software products provide support for fundamental ideas in varying ways. This needs to be evaluated for specific cases when selecting software. Using generic support code for fundamentals, rather than devising case-specific solutions, is more stable and resilient to change over time. Solutions in other areas of information science can be evaluated rationally according to their ability to enhance support of fundamental aspects. Aspects where much research is still necessary can be identified and evaluated for specific cases.

6. 6 Big Ideas in BIM (not necessarily present in all implementations) - at the root of the body of knowledge associated with BIM Collaboration between partners (architects, engineers, trades, suppliers, contractors)  through shared concurrent information Support for objectifying the world - links from domain knowledge to geometry (and back) in a complex environment Fusion of data from heterogeneous sources to support tasks such as simulation and prediction Platform for managing change Improved HCI - Closer representations of human mental models than 2-3D drawings Interoperability between software that is developed by several competing vendors

7. Big Ideas in BIM – Topic 1 Collaboration between multiple project stakeholders (architects, engineers, trades, suppliers, contractors) through shared concurrent information Fernanda Leite, Ph.D., P.E., M.ASCE Associate Professor Department of Civil, Architectural and Environmental Engineering The University of Texas at Austin http://www.caee.utexas.edu/prof/leite/ Twitter: @ LeiteBuild [email protected]

8. Construction projects are usually accomplished through several sequential phases. Each phase involves multiple parties such as owners, architects and engineers (A/E), contractors, subcontractors, materials and equipment suppliers. These parties, with various organizational backgrounds and cultures, are increasingly dispersed both geographically and over time. Some parties may have conflicting goals The fragmented nature of the Architecture, Engineering, Construction, and Operations (AECO) industry results in a sequential and cultural separation between disciplines and project phases. The information silos and inadequate collaboration often leads to information loss, duplication, physical or soft clashes and inaccuracy. This leads to productivity loss, schedule delays, cost overruns, increased litigation and unsatisfied production quality ( Tommelein 2015; Shokri et al. 2016; Leite 2019). Why this is a big idea

9. Opportunities BIM speakers often include this graph, adapted from a figure in Paulson (1976). Patrick MacLeamy of the design firm HOK made it widely known. The idea is simple: as design develops, changes become more difficult and costly to implement. Therefore, increasing early design effort minimizes cost impact of design changes. BIM enables teams to collaborate more seamlessly. For example, with the assistance of BIM, construction teams can perform automated clash detection more efficiently and intuitively, as compared with paper-based design reviews. Level of Influence of Design on Project Cost (adapted from Paulson 1976) Example Hard Clash – clash between HVAC duct and light fixtures (Leite 2019)

10. Future research needs Commercially available software applications provide little support for knowledge capture and management during the coordination process. This knowledge is usually lost afterward but could be utilized if systematically documented (Wang and Leite 2016). For example, current mechanical, electrical, plumbing and fire protection design coordination is still very iterative and experience-driven. An efficient and effective lessons-learned and knowledge management system is not available. In current practice, coordination information is partially documented in the form of clash reports, tags or comments that are either attached to coordination models or in informal documents. Since the information is not documented in a way that can be easily managed or referenced, subsequent decision making for current and future projects cannot benefit.

11. References Leite, F. (2019). BIM for Design Coordination: a Virtual Design and Construction Guide for Designers, General Contractors, and Subcontractors. New York: Wiley. Milberg, C., and Tommelein , I. (2003). "Role of tolerances and process capability data in product and process design integration." Proceeding of the Construction Research Congress, ASCE, Honolulu, Hawaii, 8. Paulson, Boyd (1976). “Designing to Reduce Construction Costs.” In: Journal of the Construction Division 102 (4): 587–592. Shokri , S., Ahn , S., Lee, S., Haas, C., Haas, R. (2016) “Current Status of Interface Management in Construction: Drivers and Effects of Systematic Interface Management.” In: ASCE Journal of Construction Engineering and Management. DOI: 10.1061/(ASCE)CO.1943-7862.0001035 Tommelein , I.D. (2015). “Journey toward Lean Construction: Pursuing a Paradigm Shift in the AEC Industry.” ASCE, Journal of Construction Engineering and Management, June, 141 (6) 1-12, https://doi.org/10.1061/(ASCE)CO.1943-7862.0000926 Wang, L., Leite, F. (2016) “Formalized Knowledge Representation for Spatial Conflict Coordination of Mechanical, Electrical and Plumbing (MEP) Systems in New Building Projects”. In: Automation in Construction. Volume 64, pp. 20-26. DOI: 10.1016/j.autcon.2015.12.020

12. Big Ideas in BIM – Topic 2 Support for objectifying the world - links from domain knowledge to geometry (and back) in a complex environment Fernanda Leite, Ph.D., P.E., M.ASCE Associate Professor Department of Civil, Architectural and Environmental Engineering The University of Texas at Austin http://www.caee.utexas.edu/prof/leite/ Twitter: @ LeiteBuild [email protected]

13. Why this is a big idea Large architecture, engineering, construction, and operations (AECO) firms contain massive banks of knowledge yet often struggle to transfer knowledge effectively across siloed teams and departments (Gallaher et al. 2004). Many organizations don’t know what they know ( Chinowsky and Songer 2011) and the knowledge they possess is not readily available to the employees who need it. How will the rising generation of construction professionals apply the insight of veteran practitioners, in an industry where recent economic turmoil has driven them to retire in droves? When workers fail to access existing knowledge within their firm, they waste resources regenerating knowledge and potentially apply suboptimal solutions ( Poleacovschi et al. 2019). The ability to marshal and deploy knowledge that is dispersed across organizations will always be a central organizational challenge.

14. Opportunities Capturing and integrating/fusing information from all phases of the project lifecycle into building databases such as BIM helps firm transfer and reuse knowledge. BIM helps transform the tools used to both store and explore information and knowledge, and in so doing, the way engineers seek answers to technical questions. BIM facilitates new types of knowledge management (KM) systems which unites several previously disparate streams of communication to solve the issues of input and interoperability of today’s KM systems. Examples are: Recent advances in semantic web (Antoniou et al., 2012) and linked data ( Bizer et al., 2011) technologies for encoding, searching, and reasoning and structural knowledge Recent advances in information retrieval (Zhang et al., 2017), machine learning ( Domingos , 2012), knowledge graphs ( Bordes and Gabrilovich , 2014) and knowledge graph embedding ( Bordes et al. 2013)

15. Risks and needs for further research Multiple sources of data in BIM systems are often not sufficiently leveraged to ensure comprehensiveness. Engineering work has been increasingly digitized in computer-interpretable, parametric representations with the increasing popularity of BIM. However, many engineering decisions are still not represented digitally. BIM could circumvent the challenge of manual knowledge input into knowledge bases, leveraging pre-existing digital work products of engineers to represent knowledge. Fundamental shift in how engineers manage and acquire knowledge, relying on digital information to fully enable seamless use of the population of databases. Currently, this shift may not be sufficiently implemented. Research needs to improve the interface between the traditional computer science-based linked data field and civil engineering. Such synergetic collaboration would also provide a significant scientific and multidisciplinary body of work.

16. References Antoniou, G., Groth , P., van Harmelen , F., Hoekstra, R. (2012). A Semantic Web Primer. 3 rd Edition. Cambridge: MIT Press. 269 pp. Bizer , C., Heath, T., & Berners-Lee, T. (2011). Linked data-the story so far. Semantic services, interoperability and web applications: emerging concepts. IGI Global (pp. 205-227). Bordes , A., Usunier , N., Garcia-Duran, A., Weston, J., & Yakhnenko , O. (2013). Translating embeddings for modeling multi-relational data. In Advances in neural information processing systems (pp. 2787-2795). Bordes , A., & Gabrilovich , E. (2014). Constructing and mining web-scale knowledge graphs. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1967-1967). Chinowsky , P., Songer , A. (2011) Organization Management in Construction. London: Spon Press. 203 pp. Domingos , P. (2012). A few useful things to know about machine learning. Communications of the ACM, 55(10), 78-87. Gallaher, M.P., O’Connor, A.C. and Gilday , L.T. (2004) Cost analysis of inadequate interoperability in the U.S. capital facilities industry, National Institute of Standards and Technology Poleacovschi , C., Javernick -Will, A., Tong, T., Wanberg , J. (2019) “Engineers Seeking Knowledge: Effect of Control Systems on Accessibility of Tacit and Codified Knowledge.” In: ASCE Journal of Construction Engineering and Management. DOI: 10.1061/(ASCE)CO.1943-7862.0001594 Wang, L.; Leite, F. (2016) “Formalized Knowledge Representation for Spatial Conflict Coordination of Mechanical, Electrical and Plumbing (MEP) Systems in New Building Projects”. In: Automation in Construction. Volume 64, pp. 20-26. DOI: 10.1016/j.autcon.2015.12.020 Wang, L.; Leite, F. (2015) “Process Knowledge Capture in BIM-Based Mechanical, Electrical, Plumbing Design Coordination Meetings”. In: ASCE Journal of Computing in Civil Engineering. DOI: 10.1061/(ASCE)CP.1943-5487.0000484 Zhang, Y., Mustafizur Rahman, M., Braylan , A., Dang, B., Chang, H.-L., Kim, H., McNamara, Q., Angert , A., Banner, E., Khetan , V., McDonnell, T., Thanh Nguyen, A., Xu, D., Wallace, B. C., and Lease, M. (2017) Neural Information Retrieval: A Literature Review. Technical report, University of Texas at Austin, ArXiv 1611.06792.

17. Big Ideas in BIM - Topic 3 Fusion of data from heterogeneous sources to support tasks such as simulation and prediction Burcu Akinci Paul Christiano Professor of Civil and Environmental Engineering Carnegie Mellon University https://faculty.ce.cmu.edu/akinci/ [email protected]

18. Why this is a big idea Complexities of construction projects/facilities/infrastructure systems challenge the decision-making capability of engineers and this results in significant waste. For example: 6-12% of construction costs are wasted due to late detection of defects ( Burati et al. 1991) Based on 2004 data, $1.5 billion is wasted for staying idle due to lack of information during facility operations and $4.8 billion is spent annually in the US for verifying existing facilities information. (NIST 2004) $ 36 – 60 billion is wasted annually on HVAC faults that are not detected in a timely manner ( DoE 2008) Reactive maintenance (which is the most common way of doing maintenance) costs 30-40% more over predictive maintenance (DoE 2010)

19. Why this is a big idea (cont’d) Data integration issues are significant for two reasons The architecture, engineering, construction and facility management industry is a highly fragmented industry with many task-specific legacy systems. Data/information is stored in many heterogeneous sources and platforms. Data quality issues are pervasive. Data is often not available at the right time in the right format. Behavior/performance of facilities/infrastructure systems are influenced by the contexts in which they operate. Hence, having information about physical systems alone does not necessarily result in useful analyses.

20. Opportunity: BIM-based Data Meshing to support predictive decision-making. Known as built environment information fabric (BEIF) Courtesy of LeanFM Technologies

21. Example Research – Self-Managing Framework for HVAC Systems Information base Condition measures HVAC configuration Building information Self-configuration Self-healing Self-recognition Self-monitoring Self-assessment Self-improvement Information repository Information mediator layer Liu 2012

22. References Burati , J. and Ferrington , J., “Costs of Quality Deviations in Design and Construction,” Construction Industry Institute, 1987. Gallaher, M., O’Connor, A., Dettbarn , J., and Gilday , T., “Cost Analysis of Inadequate Interoperability in the U.S. Capital Facilities Industry,” NIST GCR 04-867, 2004. Liu, X., “An Integrated Information Support Framework for Performance Analysis and Improvement of Secondary HVAC Systems,” PhD Thesis submitted to the Department of Civil and Environmental Engineering, Carnegie Mellon University, 2012. U. S. DoE, “Building Energy Data Book,” Energy Efficiency and Renewable Energy, Buildings Technologies Program, U.S. DoE, Washington, D.C., 2008. US DoE “Operations & Maintenance Best Practices A Guide to Achieving Operational Efficiency,” https://www1.eere.energy.gov/femp/pdfs/OM_5.pdf, August 2010 .

23. Timo Hartmann Professor of Civil Systems Engineering [email protected] Lucian Ungureanu Post. Doc. Civil Systems Engineering [email protected] Big ideas in BIM – Topic 4 Platform for managing change

24. Why this is a big idea Unforeseen changes on construction projects usually account for 8-12% of overall construction costs. Many projects fail because of changes that are introduced late. The conservative/non-innovative culture in the industry is often attributed to the fear of having to dealing with unforeseen changes. 24

25. Opportunities BIM enables virtually designing and constructing a building so that many changes can be found in the virtual model before they will cause large extra costs in the real world. This model is sometimes called a digital twin. Virtual BIM models facilitate implementation of change management systems during the design process to coordinate all changes implemented by the design team. Product centric BIM applications allow for advanced configuration management. For example, focusing on interfaces between building parts may enable flexible changes (agile products). 25

26. Risks BIM models usually represent buildings in much more detail than traditional drawings → required conflicts and changes might be hidden in the details (information overload). Design tasks are reciprocal -> there could be circular dependencies -> a change in the design of one part will lead to changes in other parts that might require a further change in the original part. 26

27. Managing changes 27 Currently, standards such as BS1192 and PAS 1192-2, now superceded by ISO 19650, propose a structured way of making changes across teams Four abstract areas are defined work-in-progress - where the changes are continuously committed by the design authoring team shared area - where changes are committed and shared with the other teams with specific purposes defined by suitability codes such as S1-for coordination, S2 - for information. published area - where all the validated changes are shared externally (outside design teams) for various purposes such as tender, manufacture, construction, as-built archive - where all the changes recorded during design are maintained for project history purposes

28. Big Ideas in BIM – Topic 5 Improved Human-Computer Interface (HCI) – Closer representations of human mental models than 2-3D drawings Robert Amor, Ph.D. Professor School of Computer Science University of Auckland New Zealand http://www.cs.auckland.ac.nz/~trebor/

29. 16/12/2018 Why this is a big idea Architecture, engineering, construction and owner-operated (AECO) professionals are most efficient in their use of software tools when their mental model aligns closely with the model that is embodied in the software. With thousands of software tools developed for AECO professionals by several hundred companies and thousands of developers there is great variation in the embodied software models. Other industries (e.g., medicine) have developed standardized HCI approaches to bring uniformity to the software in their industry, thus reducing the potential for conflicting mental models. The 2D heritage of AECO still dominates interactions in a world that offers a multitude of HCI approaches.

30. 16/12/2018 Opportunities Standardized HCI approaches that are developed to be specific to the needs of AECO professionals could be widely propagated and utilized. More efficient HCI would lead to productivity improvements and reduce errors in use of software Approaches utilizing new HCI software and hardware technologies could move the AECO profession away from the limitations of traditional 2D. A greater percentage of the population would understand a designer’s intent and thus they would more readily partake in discussions related to design proposals.

31. 16/12/2018 Risks Poorly crafted HCI solutions would provide no benefit to AECO professionals and degrade performance in the industry. Cost of defining standardized HCI approaches may be beyond what is affordable by AECO community. BIM models offer much more information than traditional means of communication. There is a risk of information overload. Engineers might no longer be able to quickly find the information that is relevant to them.

32. 16/12/2018 References Alavi, H.S., Churchill, E.F., Wiberg, M., Lalanne, D., Dalsgaard, P., Fatah gen Schieck, A., and Rogers, Y. (2019) Introduction to human-building interaction (HBI): Interfacing HCI with architecture and urban design. ACM Trans. Comput.-Hum. Interact. 26, 2 (Mar. 2019), Article 6. Anshuman, S. and Kumar, B. (2004) ‘Architecture and HCI: a review of trends towards an integrative approach to designing responsive space’. International Journal of IT in Architecture, Engineering and Construction, 2(4), December, 273-283. Dalton, N.S., Schnädelbach, H., Wiberg, M., and Varoudis, T., Eds. (2016) Architecture and Interaction: Human Computer Interaction in Space and Place. Springer. Gül, L.F. (2014) ‘The Impact of Digital Design Representations on Synchronous Collaboration Behaviour’, Journal of Information Technology in Construction, 47-71.

33. Big Ideas in BIM – Topic 6 Interoperability between software that is developed by several competing vendors Robert Amor, Ph.D. Professor School of Computer Science University of Auckland New Zealand http://www.cs.auckland.ac.nz/~trebor/

34. Why this is a big idea Interoperability is a perennial and surprisingly unsolved issue for the domain. AECO professionals and their software tools require consistent information about the building across all processes and stages of a project. The information required about the building for each process and software tool is specific to the tool and process. This information is represented in very different ways to suit process viewpoints and the efficiency of the software tools (e.g., for rendering or simulation). Having a complete (in its mathematical sense) mapping between different tool representations, or to an industry standard representation, is impossible in the vast majority of instances. AECO professionals hold a deep understanding of the domain and are able to interoperate through paper representations, which gives hope to computerized interoperability. The volume and complexity of information exchanged about a building is too great for non-computerized interoperability approaches.

35. Opportunities Semantic web, IoT and AI offer new approaches to tackling interoperability, which has not been successfully addressed by past technologies and techniques. Metrics and measures of a software tool’s level of interoperability could provide AECO professionals with the information needed to make rational choices for project needs. Model View Definition(MVD) provision for specific processes and software tools to be further explored and standardized. Interoperability approaches from other domains have some bearing on AECO, for example military systems and database federation. A sufficient open standard BIM representation reduces the size of the interoperability problem from O(n 2 ) to O(n).

36. Risks Poorly crafted interoperability solutions degrade trust in BIM and computerized project systems. Inadequate testing of open standard BIM compliance leads to degraded trust in open standard BIM approach. Cost of defining interoperability metrics and measures is beyond what is affordable by AECO community. Poor interoperability solutions lead to invalid decisions in design and construction, with significant losses to project participants.

37. References Amor, R., Jiang, Y., and Chen, X. (2007) ‘BIM in 2007 – are we there yet?’. Proceedings of CIB W78 conference on Bringing ITC knowledge to work, Maribor, Slovenia, 26-29 June, 159-162. Hartmann, T., Amor, R., and East, B. (2017) ‘Information Model Purposes in Building and Facility Design’, ASCE Journal of Computing in Civil Engineering, 31(6). Jeong , Y.-S., Eastman, C., Sacks, R., and Kaner , I. (2009). “Benchmark tests for BIM data exchanges of precast concrete.” Autom . Constr., 18(4), 469–484. Kent, W., and Hoberman , S. (2012). Data and reality: A timeless perspective on perceiving and managing information in our imprecise world, Technics Publications, London. Sowa, J. F. (1999). Knowledge representation: Logical, philosophical, and computational foundations, Brooks Cole, Pacific Grove, CA. Turk, Ž. (2001). “Phenomenological foundations of conceptual product modelling in architecture, engineering and construction.” Artif . Intell . Eng., 15(2), 83–92.

38. 38 Conclusions Knowledge of “big ideas”, including their opportunities, risks and needs for future work, supports current practical applications through providing high-level criteria for evaluating software products exposing possible weaknesses and challenges in applications identifying areas where generic solutions are feasible identifying areas where application-specific solutions are needed pointing to what to look for in new software products Research efforts are expected to be supported in analogous ways.