A review of BIM data exchange method in BIM collaboration Jinfeng Lou 1*, Weisheng Lu 2, Fan Xue 3 This is the authors’ pre-print version (before peer review) of the paper: Lou, J., Lu, W. & Xue, F. (2020). A review of BIM data exchange method in BIM collaboration. Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate (CRIOCM2020), Springer, in press. This file is shared for personal and academic use only, under the license CC BY-NC-ND 4.0 (Non-Commercial, No Derivatives, and with an Attributed citation when you use). The final published version of this paper can be found at: [LINK_TO_SPRINGERLINK]. Any uses other than personal and academic purposes must obtain appropriate permissions from Springer first. Abstract: Nowadays, building information modeling (BIM) plays a crucial role in project collaboration. BIM information should be freely exchanged among different stakeholders for the purpose of collaboration. With the development of Information and Communication Technology (ICT), there are many novel data exchange methods for BIM information exchange. However, little literature has attempted to review the current status of BIM data exchange methods. This study aims to provide a comprehensive summary of the status quo of BIM data exchange methods, including file-based method, cloud-based method, and three local data exchange methods. The advantages and disadvantages of each method are identified. This paper reveals that more efforts should be paid for enhancing the capability to deal with large Industry Foundation Class (IFC) files; a more stable, consistent identifier that can uniquely and easily identify an object should be developed; more opportunity in integrating BIM with some emerging technologies, like blockchain, should be seized to solve the problems in BIM data exchange. This study presents an in-depth analysis of the current BIM data exchange method and helps the industry and academia to identify the existing gaps 1* Jinfeng Lou Corresponding author, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong, China E-mail: waseljf@connect.hku.hk 2 Weisheng Lu Department of Real Estate and Construction, The University of Hong Kong, Hong Kong, China 3 Fan Xue Department of Real Estate and Construction, The University of Hong Kong, Hong Kong, China and future directions. Keywords: Building information modeling (BIM); Data exchange; Collaboration. 1 1 Introduction 2 Since building information modeling (BIM) first appeared in journal articles[1], BIM has 3 aroused widespread interest in academia and industry in many countries. BIM serves as a 4 digital representation of physical and functional characteristics of a facility, which can be 5 shared among various stakeholders[2]. The richness of data in BIM provides a brand new way 6 that people design, construct, and operate a building. From this point of view, BIM has led to 7 great transformation in Architecture, Engineering, Construction, and Operation (AECO). BIM 8 is not only a tool for representing facilities but also a project and process management 9 technique, covering almost all the information related to the project[3]. 10 Recent years have witnessed a surge of leveraging BIM technology in a variety of 11 applications. It is reported that BIM increased labor productivity from 75% to 240% within a 12 small contractor[4]. With the help of BIM, Lee et al. proposed an ontological method to 13 automate the inference process and gain a more precise cost estimation, reducing the amount 14 of manual work[5]. Liu et al. also developed a framework for integrating change management 15 with BIM and created an automated model updating workflow[6]. Besides, BIM has been 16 regarded as a powerful and disruptive tool for education and training to boost education 17 design and students' learning outcomes[7]. Grilo and Jardim-Goncalves proved that BIM has 18 effectively promoted electronic procurement in the AECO sector[8]. In these cases, BIM can 19 benefit project management a lot. 20 Another significant advantage of BIM lies in project collaboration. BIM has the ability to 21 improve the collaboration between stakeholders, including owners, architects, engineers, 22 contractors, and suppliers, by conveying accurate information efficiently[9]. The concept of 23 “collaboration” refers to a process during which participants collectively evaluate their 24 differences and seek cooperative solutions that are beyond the vision and capacity of any 25 single individual participant[10]. From a project management perspective, collaboration means 26 an agreement that some experts share and exchange their expertise, information, and 27 experience to fulfill a specific task and reach the project aim[11][12]. The lack of collaboration 28 in construction projects has been heavily criticized in the literature[12]. The advent of BIM 29 technology provides a digital information platform for the collaboration of construction 30 projects. Information exchange, corresponding to data exchange in BIM, is a crucial basis for 31 participant collaboration. BIM, as a pool of digital data, can convey the proper information to 32 proper participants with the assistance of modern Information and Communication 33 Technology (ICT). 34 However, BIM-enabled data exchange is also faced with several problems from both 35 social and technical aspects. For the social issues, Gielingh identified the lack of motivation, 36 legal concerns, and industrial unreadiness when integrating BIM into collaboration[13]. In 37 2004, Kam and Fischer summarized some of the technical problems, such as geometric 38 misrepresentation, loss of object information, application-specific input/output, time- 39 consuming one-way conversion processes, and so on[14]. With the rapid development of BIM 40 and ICT technology, many aforementioned problems have already been solved, and many 41 new ones have emerged. Nevertheless, there is very little literature regarding the current BIM 42 data exchange methods. 43 This study aims to provide a comprehensive elaboration of the status quo of the 44 prevailing BIM data exchange approach from a technical perspective. Section 2 reviews the 45 file-based data exchange method. The cloud-based approach is reviewed in Section 3. 46 Moreover, three local data exchange method is summarized in Section 4. Conclusions and 47 future directions are given in Section 5. 48 2 File-based data exchange 49 File-based BIM data exchange is to directly transfer a specific file to the receiver manually. In 50 the early stages of BIM development, different software vendors had their own file formats, 51 which can not be recognized by other software. It caused much trouble in project 52 collaboration when the stakeholders used different software. Therefore, as expected, Industry 53 Foundation Class (IFC) format, as a neutral data format, has been widely accepted by existing 54 BIM collaboration standards and various software vendors[15]. Many recently developed 55 applications and studies are based on IFC format[16][17]. 56 Exchanging IFC-based files is the most simple and straightforward way of 57 communicating BIM information. In IFC schema, one can easily extract a subset of data from 58 the overall model via Model View Definition (MVD), a pre-defined subset of the IFC schema 59 in light of the receiver’s need[18]. 60 However, file-based exchange transfers information in a one-way manner, leading to the 61 results that designers should transfer files repeatedly in each design iteration to ensure all the 62 design changes are considered[19]. The request for BIM information and file transfer is 63 manually made often through emails or other correspondence. And current file-based 64 exchange technologies are incapable of managing data inconsistencies and redundancy, with 65 network resources occupied by excessive files[20]. Moreover, the file-based exchange is 66 unlikely to provide object-level data management without auxiliary tools. For example, 67 different participants may have different access privileges. For a file-based system, the 68 accessibility of data can only be regulated on a file-level instead of an object-level[21]. 69 3 Cloud-based data exchange 70 Cloud computing has long been regarded as transforming information technology. The most 71 widely accepted definition of cloud computing stated that “Cloud computing is a model for 72 enabling convenient, on-demand network access to a shared pool of configurable computing 73 resources (e.g., networks, servers, storage, applications, and services) that can be rapidly 74 provisioned and released with minimal management effort or service provider interaction”[22]. 75 The benefits of cloud computing come in many aspects, such as low cost, scalability, 76 independence of hardware, and venue[23]. Three common cloud service architectures are 77 identified: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a 78 Service (IaaS). By deployment model, cloud service can also be categorized into four types: 79 Private cloud, Community cloud, Public cloud, and Hybrid cloud. The advent of cloud BIM is 80 considered to realize the function of real-time data exchange[24]. There are already a number 81 of vendors developing their own cloud services, such as Graphisoft’s BIM Explorer (BIMx) 82 and BIMcloud, Autodesk’s A360, and BIM360, BIMServer, ONUMA System, and Trimble 83 QuadriDCM and Trimble Connect[19]. 84 By combining cloud computing and BIM technology, cloud BIM promises to solve some 85 of the problems, such as lack of computing power and high cost[20]. Cloud BIM also allows 86 real-time access to data, on-demand access to computing resources and applications, which 87 potentially provides a high level of collaboration in a consolidated model[19]. 88 However, the collaboration between various cloud BIM software provided by different 89 vendors is difficult[25]. The open standards for cloud BIM collaboration, like IFC schema, are 90 expected to be developed to tackle this issue[19]. More importantly, organizational and legal 91 problems are regarded as the major obstacles to implementing cloud BIM[24]. For example, 92 shared common platforms, like cloud BIM, create significant vulnerability and uncertainties 93 towards privacy and information security due to its nature of openness and 94 decentralization[26]. Redmond et al. maintained that the current contract does not cover 95 information about the ownership clarity of the BIM model[27]. The lack of a clear statement 96 about responsibility and liability can hinder the adoption of cloud BIM. Moreover, the 97 promotion of cloud BIM is in urgent need of a large number of technicians and professionals 98 to adapt to this new technology[24][27]. 99 4 Local data exchange method 100 The above two methods are general methods for BIM data exchange. Recently researchers 101 have developed some other approaches to deal with local data exchange for partial models, 102 including the serialization method, transaction-based method, and blockchain-based method. 103 4.1 Serialization method 104 Some researchers attempted to serialize the contents of IFC files in order to store, transfer, 105 identify, trace objects. Data serialization refers to encoding IFC objects into a format or data 106 structure that can be stored or sent to other applications[28]. The data structure is critical for 107 exchanging data and other applications at an object level. 108 One of the serialization methods is the “flattening” method. Data exchange relies on an 109 identifier (e.g., the reference number of each line in IFC files and Globally Unique Identifier 110 (GUID)) to trace objects. The line reference number serves as a local reference of an object, 111 but only valid within one file[29]. With the help of these reference numbers, IFC files are 112 organized into an object-based inheritance hierarchy[30]. GUID is a unique and reproductive 113 128-bit number for identifying objects[31][32]. Different software has different internal data 114 structures and editing operations, which results in the inconsistency and inadequacy of both 115 the reference number and GUID to be an identifier during the IFC roundtripping 116 process[33][34]. Some techniques have been developed to avoid using the reference number or 117 GUID as an identifier. The “flattening” method, proposed by Lee et al.[35], is to replace the 118 reference numbers with the actual values by a recursive strategy and decode nested 119 relationships between various instances to form a full and unique description string for an IFC 120 instance itself[36]. In this case, each line of IFC files does not include any reference, and the 121 hierarchical structure is “flattened”. Each object can be identified by this unique string 122 directly, not affected by the unstable reference number or GUID. However, such a flattening 123 process may be sensitive to redundant instances[34] and produce an overly long string, which 124 costs a lot of computing resources and time[33]. 125 Some other studies seek to convert an IFC file into a graph. Arthaud and Lombardo 126 developed a method to transform IFC files into oriented graphs[37]. Oraskari and Törmä 127 derived an RDF graph from IFC files and used a Short Paths Crossings Algorithm (SPCA) to 128 assign an identifier to those instances that do not have a GUID[29]. However, these graph- 129 based methods depend more or less on the GUID and can be very time-consuming when IFC 130 files are too large. Additionally, these methods can not cope with duplicate instances[34]. 131 4.2 Transaction-based method 132 Froese pointed out that collecting common data in a centralized server allows various flexible 133 data management services and enables a series of transaction-based IFC exchange with proper 134 data exchange protocols between distributed parties[38]. Jørgensen et al. developed an IFC 135 model server, supporting functions such as working on partial models, granting different 136 access rights to different users, and versioning on an object level[39]. Du et al. realized the 137 real-time information interaction between BIM and VR via transactional data exchanges[32]. 138 These transaction-based data exchange applications benefit from GUID, which could be 139 used to index an object for each transaction. Nevertheless, its disadvantages also lie here. 140 GUID has been criticized for its inconsistency and instability[33]. 141 4.3 Blockchain-based method 142 Since Nakamoto proposed the prototype of Bitcoin in 2008, blockchain, as its core 143 technology, has been a buzzword around the world[40]. Nowadays, blockchain has evolved 144 from version 1.0 to 4.0[41]. Blockchain technology has permeated into all walks of life, 145 including the AECO industry. It can be used to facilitate the BIM collaboration process. 146 Xue and Lu developed a semantic differential transaction (SDT) approach to capture 147 model changes as SDT records and chronologically collect them into a BIM change contract 148 (BCC)[36]. All the stakeholders can submit their BIM changes to the blockchain, and all 149 history changes of the project are stored in one blockchain, unchangeable. This method 150 addresses the challenge of information redundancy in integrating BIM and blockchain, and 151 turns out to be light and lean, suitable for performing heavy computation[36]. 152 However, the conflict-resolving mechanisms need to be improved by some other 153 sophisticated models[36]. And only two pilot case studies were conducted to prove the 154 feasibility of the SDT approach. More tests considering extensibility and compatibility 155 problems should be carried out within real blockchain shells in the context of practical 156 construction projects[36]. 157 5 Conclusions 158 BIM data exchange plays a crucial role in BIM project collaboration. With the development of 159 Information and Communication Technology, some previous problems are already solved 160 while some new issues emerge. In this study, the current BIM data exchange methods are 161 comprehensively reviewed. For the file-based data exchange method, it is regarded as the 162 most straightforward way. Still, its disadvantages lie in its one-way file-transfer manner and 163 incapability to manipulate at an object level. For cloud-based data exchange method, it is 164 praised by efficiency, low cost, real-time access to data, and on-demand access. However, the 165 cloud BIM also faces the problem of lack of open cloud BIM standards, and too much 166 organizational and legal issues, such as privacy, information security, lack of sufficient 167 technicians, and ownership and responsibility clarity. There are some local data exchange 168 approaches developed for partial model exchange. The “flattening” method dissolves all 169 nested relationships between objects and identifies an object by a unique string. Others tried 170 to convert IFC files into a graphic structure. However, these methods are not applicable to 171 large IFC files and depend on the unstable GUID more or less. For the transaction-based 172 method, most of them are based on the GUID, which might be inconsistent. With the help of 173 blockchain, a novel semantic differential transaction (SDT) approach collects the model 174 changes into a blockchain, better solving the problem of redundancy. However, this is a 175 brand-new method, requiring more consideration, such as conflict-resolving mechanisms, 176 extensibility, and compatibility. 177 Future research directions should focus on: (1) developing an algorithm to deal with 178 large IFC files with less computing time and resources; (2) finding a unique, stable, 179 consistent, and easy-to-use identifier to track IFC objects throughout the building life-cycle; 180 (3) exploring more about the potential of blockchain and other emerging technologies in 181 facilitating BIM data exchange. 182 References 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 [1] Zhao, X. (2017). A scientometric review of global BIM research: Analysis and visualization. Automation in Construction, 80, 37-47. [2] ISO. (2016). Building Information Models - Information Delivery Manual - Part 1: Methodology and Format (ISO 29481-1: 2016). International Organization for Standardization, Geneva, Switzerland. [3] Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in construction, 18(3), 357-375. [4] Poirier, E. A., Staub-French, S., & Forgues, D. (2015). Measuring the impact of BIM on labor productivity in a small specialty contracting enterprise through actionresearch. Automation in Construction, 58, 74-84. [5] Lee, S. K., Kim, K. R., & Yu, J. H. (2014). BIM and ontology-based approach for building cost estimation. Automation in construction, 41, 96-105. [6] Liu, F., Jallow, A. K., Anumba, C. J., & Wu, D. (2014). A framework for integrating change management with building information modeling. In Computing in Civil and Building Engineering (2014) (pp. 439-446). [7] Wu, W., & Issa, R. R. (2014). BIM education and recruiting: Survey-based comparative analysis of issues, perceptions, and collaboration opportunities. Journal of professional issues in engineering education and practice, 140(2), 04013014. [8] Grilo, A., & Jardim-Goncalves, R. (2011). Challenging electronic procurement in the AEC sector: A BIM-based integrated perspective. Automation in Construction, 20(2), 107-114. [9] Azhar, S., Khalfan, M., & Maqsood, T. (2012). Building information modelling (BIM): now and beyond. Construction Economics and Building, 12(4), 15-28. [10] Gray, B. (1985). Conditions facilitating interorganizational collaboration. Human relations, 38(10), 911-936. [11] Hu, Z. Z., Zhang, X. Y., Wang, H. W., & Kassem, M. (2016). Improving interoperability between architectural and structural design models: An industry foundation classesbased approach with web-based tools. Automation in Construction, 66, 29-42. [12] Oraee, M., Hosseini, M. R., Edwards, D. J., Li, H., Papadonikolaki, E., & Cao, D. (2019). Collaboration barriers in BIM-based construction networks: A conceptual model. International Journal of Project Management, 37(6), 839-854. [13] Gielingh, W. (2008). An assessment of the current state of product data technologies. Computer-Aided Design, 40(7), 750-759. [14] Kam, C., & Fischer, M. (2004). Capitalizing on early project decision-making opportunities to improve facility design, construction, and life-cycle performance—POP, PM4D, and decision dashboard approaches. Automation in construction, 13(1), 53-65. [15] buildingSMART International. (2020). Industry Foundation Classes (IFC). Retrieved September 15, 2020, from https://www.buildingsmart.org/standards/bsistandards/industry-foundation-classes/. [16] Jeong, S. K., & Ban, Y. U. (2011). Computational algorithms to evaluate design solutions using Space Syntax. Computer-Aided Design, 43(6), 664-676. [17] Sun, J., Liu, Y. S., Gao, G., & Han, X. G. (2015). IFCCompressor: A content-based compression algorithm for optimizing Industry Foundation Classes files. Automation in Construction, 50, 1-15. 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 [18] buildingSMART International. (2020). Model View Definitions (MVD). Retrieved September 15, 2020, from https://www.buildingsmart.org/standards/bsi-standards/modelview-definitions-mvd/. [19] Afsari, K., Eastman, C. M., & Shelden, D. R. (2016). Cloud-based BIM data transmission: current status and challenges. In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 33, p. 1). IAARC Publications. [20] Zhang, J. P., Liu, Q., Yu, F. Q., Hu, Z. Z., & Zhao, W. Z. (2014). A framework of cloudcomputing-based BIM service for building lifecycle. In Computing in Civil and Building Engineering (pp. 1514-1521). [21] Lee, G., Jeong, J., Won, J., Cho, C., You, S. J., Ham, S., & Kang, H. (2014). Query performance of the IFC model server using an object-relational database approach and a traditional relational database approach. Journal of Computing in Civil Engineering, 28(2), 210-222. [22] Mell, P., & Grance, T. (2009). Draft NIST working definition of cloud computing-v15. 21. Aug 2009, 2, 123-135. [23] Shen, Z., Li, L., Yan, F., & Wu, X. (2010). Cloud computing system based on trusted computing platform. In 2010 International Conference on Intelligent Computation Technology and Automation (Vol. 1, pp. 942-945). IEEE. [24] Wong, J., Wang, X., Li, H., & Chan, G. (2014). A review of cloud-based BIM technology in the construction sector. Journal of information technology in construction, 19, 281291. [25] Wu, W., & Issa, R. R. (2012). Leveraging cloud-BIM for LEED automation. Journal of Information Technology in Construction (ITcon), 17(24), 367-384. [26] Mahamadu, A. M., Mahdjoubi, L., & Booth, C. (2013). Challenges to BIM-cloud integration: Implication of security issues on secure collaboration. In 2013 IEEE 5th International Conference on Cloud Computing Technology and Science (Vol. 2, pp. 209214). IEEE. [27] Redmond, A., Hore, A., Alshawi, M., & West, R. (2012). Exploring how information exchanges can be enhanced through Cloud BIM. Automation in construction, 24, 175183. [28] Afsari, K., Eastman, C. M., & Castro-Lacouture, D. (2017). JavaScript Object Notation (JSON) data serialization for IFC schema in web-based BIM data exchange. Automation in Construction, 77, 24-51. [29] Oraskari, J., & Törmä, S. (2015). RDF-based signature algorithms for computing differences of IFC models. Automation in Construction, 57, 213-221. [30] Lin, J. R., & Zhou, Y. C. (2020). Semantic classification and hash code accelerated detection of design changes in BIM models. Automation in Construction, 115, 103212. [31] Jeong, Y. S., Eastman, C. M., Sacks, R., & Kaner, I. (2009). Benchmark tests for BIM data exchanges of precast concrete. Automation in construction, 18(4), 469-484. [32] Du, J., Zou, Z., Shi, Y., & Zhao, D. (2018). Zero latency: Real-time synchronization of BIM data in virtual reality for collaborative decision-making. Automation in Construction, 85, 51-64. [33] Shafiq, M., & Lockley, S. (2018). Signature-based matching of IFC models. In 35th International Symposium on Automation and Robotics in Construction (ISARC). [34] Shi, X., Liu, Y. S., Gao, G., Gu, M., & Li, H. (2018). IFCdiff: A content-based automatic comparison approach for IFC files. Automation in Construction, 86, 53-68. [35] Lee, G., Won, J., Ham, S., & Shin, Y. (2011). Metrics for quantifying the similarities and differences between IFC files. Journal of Computing in Civil Engineering, 25(2), 172181. 277 278 279 280 281 282 283 284 285 286 287 288 289 290 [36] Xue, F., & Lu, W. (2020). A semantic differential transaction approach to minimizing information redundancy for BIM and blockchain integration. Automation in Construction, 118, 103270. [37] Arthaud, G., & Lombardo, J. C. (2006). Automatic semantic comparison of STEP product models. In Innovations in Design & Decision Support Systems in Architecture and Urban Planning (pp. 447-463). Springer, Dordrecht. [38] Froese, T. (2003). Future directions for IFC-based interoperability. Journal of Information Technology in Construction (ITcon), 8(17), 231-246. [39] Jørgensen, K., Skauge, J., Christiansson, P., Svidt, K., Sørensen, K. B., & Mitchel, J. (2008). Use of IFC Model Servers: Modelling Collaboaration Possibilities in Practice. Aalborg Universitet. [40] Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. [41] Angelis, J., & da Silva, E. R. (2019). Blockchain adoption: A value driver perspective. Business Horizons, 62(3), 307-314.