Technical Papers
Feb 9, 2023

Data Reliability in BIM and Performance Analytics: A Survey of Contemporary AECO Practice

Publication: Journal of Architectural Engineering
Volume 29, Issue 2

Abstract

As awareness around building energy consumption increases, practitioners are encouraged to consider performance aspects regarding the built environment more closely and find ways to improve its efficiency. Improvements in building information modeling (BIM) and building performance simulation (BPS) tools present opportunities to facilitate information communication with a wider range of stakeholders. The building sector can benefit from the integration of performance informatics; however, there has been limited success in utilizing available technologies that promote data integration and management in favor of enriching our knowledge and understanding of buildings as artifacts of information. This phenomenon was investigated by conducting a survey, together with a review of relevant literature, to depict the relevant challenges and opportunities for the architecture, engineering, construction, and owner-operated (AECO) industry, as it undergoes digital transformation, as well as the working practices that have formed around them. It is argued that the current tools available to practitioners do not support effective data serialization between design and analytics processes, affecting the collaboration between team members. Finally, a series of functional goals are proposed to support a higher level of reliability in the ways information is mobilized, by rethinking the technologies and methods for organizing information systems.

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Acknowledgments

This material is based on work supported by the US DOE’s Office of Energy Efficiency and Renewable Energy (EERE) under the Buildings Technology Office Award Number DE-EE0008680. The authors thank Professor Sonit Bafna and Ph.D. student Zachary Lancaster, for their advice and support with the statistical analysis of the survey, as well as Goel Supriya, Sarah Mokhtar, Zachary Lancaster, Yasser El Masri, and Alexandra Lipezker, for piloting the survey before deployment.

References

Afsari, K., and C. Eastman. 2014. “Categorization of building product models in BIM Content Library portals.” In Vol. 1 of XVIII Conf. of the Iberoamerican Society of Digital Graphics, 370–374. Sao Paolo: Blucher.
AIA Document E202TM-2008. Building Information Modeling Protocol Exhibit. AIA Document E202 (10): 1–9.
Ansah, M. K., X. Chen, H. Yang, L. Lu, and P. T. I. Lam. 2019. “A review and outlook for integrated BIM application in green building assessment.” Sustainable Cities Soc. 48: 101576. https://doi.org/10.1016/j.scs.2019.101576.
Bastem, S. S., and A. Cekmis. 2022. “Development of historic building information modelling: A systematic literature review.” Build. Res. Inf. 50 (5): 527–558. https://doi.org/10.1080/09613218.2021.1983754.
Batini, C., C. Cappiello, C. Francalanci, and A. Maurino. 2009. “Methodologies for data quality assessment and improvement.” ACM Comput. Surv. 41 (3): 1–52. https://doi.org/10.1145/1541880.1541883.
Bergmann, H., et al. 2020. “Semantic interoperability to enable smart, grid-interactive efficient buildings.” In ACEEE Summer Study in Energy Efficiency in Buildings, 44–59. Berkeley, CA: Lawrence Berkeley National Laboratory.
Berners-Lee, T., J. Hendler, and O. Lassila. 2001. “The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities.” Sci. Am. 284 (5): 34–43. https://doi.org/10.1038/scientificamerican0501-34.
Bhalerao, S., and P. Kadam. 2010. “Sample size calculation.” Int. J. Ayurveda Res. 1 (1): 55. https://doi.org/10.4103/0974-7788.59946.
Bhattacharya, S., and K. S. Momaya. 2021. “Actionable strategy framework for digital transformation in AECO industry.” Eng. Constr. Archit. Manage. 28 (5): 1397–1422.https://doi.org/10.1108/ecam-07-2020-0587.
Bonduel, M., M. Vergauwen, R. Klein, M. H. Rasmussen, and P. Pauwels. 2018. “A novel workflow to combine BIM and linked data for existing buildings.” In Proc., 12th European Conf. on Product and Process Modelling: EWork and EBusiness in Architecture, Engineering and Construction, edited by R. S. Jan Karlshøj, 347–354. London: CRC Press.
Borrmann, A., M. König, C. Koch, and J. Beetz. 2018. “Building information modeling – Why? What? How?.” In Building information modeling: Technology foundations and industry practice, edited by A. Borrmann, M. König, C. Koch, and J. Beetz, 1–24. Cham, Switzerland: Springer.
Bracht, M. K., A. P. Melo, and R. Lamberts. 2021. “A metamodel for building information modeling-building energy modeling integration in early design stage.” Autom. Constr. 121: 103422. https://doi.org/10.1016/j.autcon.2020.103422.
Carvalho, J. P., L. Bragança, and R. Mateus. 2020. “Guidelines for analysing the building energy efficiency using BIM.” IOP Conference Series: Earth and Environmental Science, 588 (2). https://doi.org/10.1088/1755-1315/588/2/022058.
Crawley, D. B., et al. 2001. “EnergyPlus: Creating a new-generation building energy simulation program.” Energy Build. 33 (4): 319–331. https://doi.org/10.1016/S0378-7788(00)00114-6.
De Michelis, G., E. Dubois, M. Jarke, F. Matthes, J. Mylopoulos, J. W. Schmidt, C. Woo, and E. Yu. 1998. “A three-faceted view of information systems.” Commun. ACM 41 (12): 64–70. https://doi.org/10.1145/290133.290150.
Eastman, C. 2011. BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. Hoboken, NJ: Wiley.
Eastman, C., D. Fisher, G. Lafue, J. Lividini, D. Stoker, and C. Yessios. 1974. An outline of the building description system. Research Rep. No. 50. Pittsburgh: Institute of Physical Planning, Carnegie-Mellon Univ.
Ehrlinger, L., and W. Wöß. 2022. “A survey of data quality measurement and monitoring tools.” Front. Big Data 5: 850611. https://doi.org/10.3389/fdata.2022.850611.
Farzaneh, A., D. Monfet, and D. Forgues. 2019. “Review of using Building Information Modeling for building energy modeling during the design process.” J. Build. Eng. 23 (January): 127–135. https://doi.org/10.1016/j.jobe.2019.01.029.
Gao, H., C. Koch, and Y. Wu. 2019. “Building information modelling based building energy modelling: A review.” Appl. Energy 238: 320–343. https://doi.org/10.1016/j.apenergy.2019.01.032.
Gerrish, T., K. Ruikar, M. Cook, M. Johnson, M. Phillip, and C. Lowry. 2017. “BIM application to building energy performance visualisation and management: Challenges and potential.” Energy Build. 144: 218–228. https://doi.org/10.1016/j.enbuild.2017.03.032.
GhaffarianHoseini, A., T. Zhang, N. Naismith, A. GhaffarianHoseini, D. T. Doan, A. U. Rehman, O. Nwadigo, and J. Tookey. 2019. “Nd BIM-integrated knowledge-based building management: Inspecting post-construction energy efficiency.” Autom. Constr. 97 (September 2018): 13–28. https://doi.org/10.1016/j.autcon.2018.10.003.
Gross, L. J., J. Yellen, and M. Anderson. 2019. Graph theory and its applications. 3rd ed., edited by A. Boggess and K. Rosen. London: Taylor & Francis Group.
Grytting, I., F. Svalestuen, J. Lohne, H. Sommerseth, S. Augdal, and O. Lædre. 2017. “Use of LoD decision plan in BIM-projects.” Procedia Eng. 196: 407–414. https://doi.org/10.1016/j.proeng.2017.07.217.
Hensen, J. L. M., and R. Lamberts. 2019. Building performance simulation for design and operation. London: Routledge.
Hijazi, A. A., S. Perera, R. N. Calheiros, and A. Alashwal. 2022. “A data model for integrating BIM and blockchain to enable a single source of truth for the construction supply chain data delivery.” Eng. Constr. Archit. Manage. https://doi.org/10.1108/ECAM-03-2022-0209.
Howard, C. H., R. E. Levitt, B. C. Paulson, J. G. Pohl, and B. C. Tatum. 1989. “Computer integration: Reducing fragmentation in AEC industry.” J. Comput. Civil Eng. 3 (1): 18–32. https://doi.org/10.1061/(ASCE)0887-3801(1989)3:1(18).
Hu, S., J. Wang, C. Hoare, Y. Li, P. Pauwels, and J. O’Donnell. 2021. “Building energy performance assessment using linked data and cross-domain semantic reasoning.” Autom. Constr. 124: 103580. https://doi.org/10.1016/j.autcon.2021.103580.
Kamel, E., and A. M. Memari. 2019. “Review of BIM’s application in energy simulation: Tools, issues, and solutions.” Autom. Constr. 97: 164–180. https://doi.org/10.1016/j.autcon.2018.11.008.
Klitgaard, J., P. H. Kirkegaard, and M. Mullins. 2006. “On the integration of digital design and analysis tools.” WIT Trans. Built Environ. 90: 187–196. https://doi.org/10.2495/DARC060191.
Ladenhauf, D., K. Battisti, R. Berndt, E. Eggeling, D. W. Fellner, M. Gratzl-Michlmair, and T. Ullrich. 2016. “Computational geometry in the context of building information modeling.” Energy Build. 115: 78–84. https://doi.org/10.1016/j.enbuild.2015.02.056.
Lee, Y. C., W. Solihin, and C. M. Eastman. 2019. “The mechanism and challenges of validating a building information model regarding data exchange standards.” Autom. Constr. 100: 118–128. https://doi.org/10.1016/j.autcon.2018.12.025.
Maile, T., M. Fischer, and V. Bazjanac. 2007. Building energy performance simulation tools - a life-cycle and interoperable perspective, 1–49. CIFE Working Paper #WP107. Center for Integrated Facility Engineering. Stanford, CA: Stanford Univ.
Malkawi, A. M. 2004. “Developments in environmental performance simulation.” Autom. Constr. 13 (4): 437–445. https://doi.org/10.1016/j.autcon.2004.03.002.
Medhi, S., and H. Baruah. 2017. “Relational database and graph database: A comparative analysis.” J. Process Manage. New Technol. 5 (2): 1–9. https://doi.org/10.5937/jouproman5-13553.
Menezes, A. C., A. Cripps, D. Bouchlaghem, and R. Buswell. 2012. “Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap.” Appl. Energy 97: 355–364. https://doi.org/10.1016/j.apenergy.2011.11.075.
Muller, M. F., F. Esmanioto, N. Huber, E. R. Loures, and O. Canciglieri. 2019. “A systematic literature review of interoperability in the green building information modeling lifecycle.” J. Cleaner Prod. 223: 397–412. https://doi.org/10.1016/j.jclepro.2019.03.114.
Negendahl, K. 2015. “Building performance simulation in the early design stage: An introduction to integrated dynamic models.” Autom. Constr. 54: 39–53. https://doi.org/10.1016/j.autcon.2015.03.002.
Pauwels, P., R. Bod, D. Di Mascio, and R. De Meyer. 2013. “Integrating building information modelling and semantic web technologies for the management of built heritage information.” In Vol. 1 of Proc., Digital Heritage 2013 - Federating the 19th Int. VSMM, 10th Eurographics GCH, and 2nd UNESCO Memory of the World Conf., Plus Special Sessions From CAA, Arqueologica 2.0, Space2Place, ICOMOS, ICIP & CIPA, EU Projects, et al., 481–488. Piscataway, NJ: Institute of Electrical and Electronics Engineers.
Pauwels, P., R. De Meyer, and J. Van Campenhout. 2011. “Interoperability for the design and construction industry through semantic web technology.” In Vol. 6725 of Semantic multimedia. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), edited by T. Declerck, M. Granitzer, M. Grzegorzek, M. Romanelli, S. Rüger, and M. Sintek, 143–158. Berlin: Springer.
Pauwels, P., M. Poveda-Villalón, Á Sicilia, and J. Euzenat. 2018. “Semantic technologies and interoperability in the built environment.” Semantic Web 9 (6): 731–734. https://doi.org/10.3233/SW-180321.
Pauwels, P., S. Zhang, and Y. C. Lee. 2017. “Semantic web technologies in AEC industry: A literature overview.” Autom. Constr. 73: 145–165. https://doi.org/10.1016/j.autcon.2016.10.003.
Pezeshki, Z., A. Soleimani, and A. Darabi. 2019. “Application of BEM and using BIM database for BEM: A review.” J. Build. Eng. 23: 1–17. https://doi.org/10.1016/j.jobe.2019.01.021.
Ramaji, I. J., J. I. Messner, and E. Mostavi. 2020. “IFC-based BIM-to-BEM model transformation.” J. Comput. Civ. Eng. 34 (3): 1–13. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000880.
Rasmussen, M. H., M. Lefrançois, P. Pauwels, C. A. Hviid, and J. Karlshøj. 2019. “Managing interrelated project information in AEC knowledge graphs.” Autom. Constr. 108: 102956. https://doi.org/10.1016/j.autcon.2019.102956.
Rezaee, R., J. Brown, J. Haymaker, and G. Augenbroe. 2019. “A new approach to performance-based building design exploration using linear inverse modeling.” J. Build. Perform. Simul. 12 (3): 246–271. https://doi.org/10.1080/19401493.2018.1507046.
Sacks, B. R., C. Eastman, G. Lee, P. Teicholz. 2018. BIM handbook: A guide to building information modeling for owners, designers, engineers, contractors and facility managers. Hoboken, NJ: Wiley.
Sattler, L., S. Lamouri, R. Pellerin, and T. Maigne. 2019. “Interoperability aims in building information modeling exchanges: A literature review.” IFAC-PapersOnLine 52 (13): 271–276. https://doi.org/10.1016/j.ifacol.2019.11.180.
Sibenik, G. 2016. “Building information modelling based interdisciplinary data exchange: A case study.” In Proc., 1st Int. UK BIM Academic Forum Conf., 13–15. Glasgow: National & International Publications Ltd, Dublin.
Tayri, G. K., and D. P. Ballou. 1998. “Examining data quality.” Commun. ACM 41 (2): 54–57.
Tchouanguem Djuedja, J. F., F. H. Abanda, B. Kamsu-Foguem, P. Pauwels, C. Magniont, and M. H. Karray. 2021. “An integrated linked building data system: AEC industry case.” Adv. Eng. Softw. 152: 102930. https://doi.org/10.1016/j.advengsoft.2020.102930.
Timón-Reina, S., M. Rincón, and R. Martínez-Tomás. 2021. “An overview of graph databases and their applications in the biomedical domain.” Database 2021 (5): 1–22. https://doi.org/10.1093/database/baab026.
USBLS (US Bureau of Labor Statistics). 2021. https://www.bls.gov/opub/mlr/2021/home.htm.
Volk, R., J. Stengel, and F. Schultmann. 2014. “Building information modeling (BIM) for existing buildings—Literature review and future needs.” Autom. Constr. 38: 109–127. https://doi.org/10.1016/j.autcon.2013.10.023.
Werbrouck, J., P. Pauwels, J. Beetz, and L. van Berlo. 2019. “Towards a decentralised common data environment using linked building data and the solid ecosystem.” In Proc., 36th CIB W78 2019 Conf.: Advances in ICT in Design, Construction and Management in Architecture, Engineering, Construction and Operations, 113–123. Newcastle: Univ. of Northumbria, Newcastle-upon-Tyne.
Whyte, J. K., and T. Hartmann. 2017. “How digitizing building information transforms the built environment.” Build. Res. Inf. 45 (6): 591–595. https://doi.org/10.1080/09613218.2017.1324726.
Zanni, M. A., R. Soetanto, and K. Ruikar. 2017. “Towards a BIM-enabled sustainable building design process: Roles, responsibilities, and requirements.” Archit. Eng. Des. Manage. 13 (2): 101–129. https://doi.org/10.1080/17452007.2016.1213153.

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Go to Journal of Architectural Engineering
Journal of Architectural Engineering
Volume 29Issue 2June 2023

History

Received: Apr 25, 2022
Accepted: Dec 14, 2022
Published online: Feb 9, 2023
Published in print: Jun 1, 2023
Discussion open until: Jul 9, 2023

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Ph.D. Candidate, School of Architecture, Georgia Institute of Technology, North Avenue NE, Atlanta, GA, 30303 (corresponding author). ORCID: https://orcid.org/0000-0002-1356-2913. Email: [email protected]
Tarek Rakha [email protected]
Assistant Professor, School of Architecture, Georgia Institute of Technology, North Avenue NE, Atlanta, GA, 30303. Email: [email protected]

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