1 Introduction
Blockchain, emerging from the technology sphere, could instigate a paradigm shift in construction engineering and management (CEM) (
Li et al., 2019). A blockchain is a cryptographically secure shared database with a decentralized consensus mechanism, which can effectively record and endorse transaction data among users in a shared, secure, and traceable manner (
Risius and Spohrer, 2017). Numerous benefits of blockchain have been reported in the literature, such as reinforced data transparency, traceability, immutability, and privacy (
Elghaish et al., 2020), promotion of democratic decision-making through decentralization (
Hamledari and Fischer, 2021a), and reduced costs through the removal of intermediaries (
Wu et al., 2022a). It has been explored in CEM for internal administration (
Pradeep et al., 2021), immutable records of transactions (
Lu et al., 2022a), secure payment (
Wu et al., 2022b), accurate information sharing (
Wu et al., 2022a), and combined applications with the Internet of Things (IoT), building information modeling (BIM) (
Li et al., 2022), and cloud computing (
Li and Kassem, 2021). To successfully implement these blockchain applications, construction stakeholders need to visualize blockchain to gain trust in the system.
Developing from a general computer science background, blockchain technology uses a set of unique terminologies and system architectures, which CEM practitioners find less accessible (
Xue and Lu, 2020). In the big data era, the amount of data submitted to blockchain is growing exponentially (
Tao et al., 2021). A key issue when uploading construction data, in particular, to blockchain systems is how to visualize data management processes (DMP) to give users a sense of user-friendliness and trustworthiness. This paper takes typical DMP, such as data submission, endorsement, storage, and invocation, as the research scope. Data visualization, which is the graphical representation of data using common graphics, such as charts, plots, infographics, and animation (
Börner et al., 2019), offers several benefits, such as improved comprehension, increased engagement, effective communication (
Sackett et al., 2006), reinforced transparency, enhanced decision-making (
Park et al., 2022), and storytelling (
Wang et al., 2019). In blockchain, data visualization can quickly help users understand the DMP (
Spiller et al., 2021).
It is essential for practitioners in construction projects to trust in the systems and subscribe to the technology and, without clear visualization, construction practitioners may struggle to do so. This lack of trust can result in hesitancy or reluctance to adopt blockchain technology, hindering the potential benefits it offers in terms of transparency, security, and efficiency in DMP. A lack of data visualization can also lead to confusion, misinterpretation, and potential errors in decision-making, undermining the overall effectiveness of DMP and potentially impacting project outcomes. However, the visualization of blockchain-based DMP has received little scholarly attention in the CEM context.
The primary aim of this research, therefore, is to provide a set of guidelines for users to visualize DMP on blockchain systems with a focus on the CEM context. Our research objectives are to:
(1) identify the current patterns and challenges of DMP visualization on blockchain systems in construction projects;
(2) develop guidelines for visualizing blockchain-based DMP according to construction project needs; and
(3) evaluate the effectiveness of the developed guidelines through demonstration and assessment in a case project.
The rest of this paper is organized as follows. Section 2 introduces the research methods. Section 3 shows the analytical results by illustrating the status quo and challenges of visualization methods of blockchain-based DMP in construction projects. Based on the analyzed patterns and challenges, guidelines are developed, demonstrated, and assessed in Section 4. The conclusion is presented in Section 5.
2 Research methods
The primary research method used in this study is an archival study following a four-step methodology involving: (1) development of a guiding conceptual model, (2) data collection through literature search, (3) data extraction and analyses, and (4) results validation.
2.1 A guiding conceptual model
To articulate the research aims and guide the research design, a conceptual model comprising three interlinked CEM components, namely, data inputs, blockchain systems, and DMP visualization, is proposed (Fig.1). Data inputs are records related to CEM activities that are submitted to blockchain systems, including design, quality, progress, and safety records. Blockchain systems, built on various platforms, can record and share data (i.e., offering data transparency and traceability) to support different applications in construction. These blockchain systems can be permissionless or used in a permissioned manner (
Lu et al., 2022a). The DMP visualization component refers to the visualization tools and mediums in blockchain systems, such as charts, dashboards, and blocks.
The types of data input, blockchain system, and DMP visualization components are listed in Tab.1.
2.2 Literature search
The literature search conducted in this study was guided by a conceptual model and followed the PRISMA standard (
Rethlefsen et al., 2021), which is a widely recognized approach for systematic literature reviews. The search process began on 20 October 2023, using the full-text search engine of Google Scholar with a specific query combination that included technical blockchain terms and construction-related terms. This approach ensured that the target publications explicitly mentioned both terms, thus increasing the relevance of the search results. The search terms used were “(“blockchain*” OR “block chain*” OR “smart contract*”) and (construction* OR infrastructure* OR building*).” To ensure that all relevant publications were included in the review, the “snowballing” technique was used in Scopus and the university library search engine. This technique involves examining the reference lists of identified publications to identify additional relevant articles. This approach ensured the completeness of the data collected, and all relevant publications were included in the study. The review surveyed literature published between 2008 and 2023 since blockchain technology was not invented until 2008 (
Suyambu et al., 2020). The search was further restricted to the literature published in journals, excluding law cases and patents. This approach ensured that the included articles underwent rigorous review processes, providing accurate and trustworthy content. The initial search produced 4930 hits, including journal and conference papers, books, dissertations, and reports. The large number of search results highlighted the need for a rigorous screening process to identify relevant publications for the study.
After the initial literature search, a rapid screening process was conducted to identify relevant articles based on their titles and abstracts. This screening process took place during the literature collection, identification, and scoping stage. Articles that were deemed irrelevant to CEM, such as those focusing on healthcare, were excluded from further consideration. Additionally, articles that did not specifically concentrate on blockchain technology were also excluded, as the study specifically aimed to explore the application of blockchain in CEM. Non-journal articles were also excluded from the study. This decision was made based on the understanding that journal articles undergo rigorous review processes, ensuring the accuracy and reliability of the content they contain, as supported by Li et al. (
2019). Following the preliminary screening, the full texts of 323 papers that passed the screening were downloaded and further examined. Two criteria were applied to determine which papers would be included in the analysis. First, papers had to demonstrate the actual application of blockchain in CEM, as empirical research provides verifiable proof, as noted by Oraee et al. (
2017). Non-empirical studies, such as review articles and position papers, were excluded from the analysis. Secondly, papers had to offer an original contribution with sufficient technical details of blockchain elaborated in actual applications. Based on these criteria, a total of 49 journal articles were gathered for further analysis and exploration in the study.
2.3 Data extraction and analyses
Data were manually mined from the selected publications, with basic information extracted using the code defined in Tab.1. Tab.2 summarizes the information, including the reference, details of the data input, blockchain system adopted, visualization tools and mediums, project phase, and actual application. For example, the first item, Ahmadisheykhsarmast and Sonmez (
2020), first entered progress and payment data into the Ethereum blockchain, which is a permissionless blockchain. Input data was visualized through a dashboard with details of blockchain components. The visualization was adopted in the construction phase and applied to the secure payment application. Overall, the information in Tab.2 provides an understanding of the current status and related challenges of blockchain-based DMP visualization methods. Based on this, guidelines for visualizing blockchain-based DMP in construction projects can be proposed (Section 4).
2.4 Case study
The focal project of this study is a high-rise residential building project in Hong Kong, which fully adopts modular integrated construction (MiC), shown in Fig.2(a). The project comprises four towers on a single-story common podium, with rooms formed from about 2000 integrated modules manufactured in an offsite factory in mainland China and transported to Hong Kong for onsite assembly, as illustrated in Fig.2(b). The case project customizes a blockchain-based e-Inspection system developed by Lu et al. (
2022a) for the same project client and for a project with the same requirements, mainly to monitor the quality of modules produced by an offsite MiC manufacturer. Thus, frontline workers from the MiC factory are required to upload photos related to module production at each hold point. The project client, main contractor, registered structural engineer (RSE), authorized person (AP), and building service inspector (BSI) should then endorse the uploaded photos through the decentralized consensus mechanism of the distributed network of the blockchain system. Therefore, they asked the research team to help them visualize DMP on the blockchain system to enhance user-friendliness so that they could further increase their trust in the system.
Using the proposed guidelines for visualizing blockchain-based DMP in construction projects, we worked closely with the project team to visualize the DMP on the blockchain system to enhance user-friendliness and trust in the system. To uncover the views of participants concerning the visualization processes, we conducted structured interviews comprising a set of pre-prepared questions and multiple answer options. Structured or standardized interviews are commonly used in social sciences (
Lewis-Beck et al., 2004). These interviews involve pre-developed questions and answer categories, which are organized in an interview schedule before the actual interview. This approach aims to ensure consistency and standardization in the interview process. The study implemented the structured interview protocol described by Lewis-Beck et al. (
2004). This protocol involved several vital elements. First, the questions were asked as they were worded and in the predetermined order specified in the interview schedule. This ensured that all participants were asked the same questions in the same way, minimizing variations in the data collected. Secondly, if an interviewee did not provide a complete answer to a question, follow-up questions were asked to prompt for further details or clarification. This allowed for a more comprehensive understanding of the interviewee’s responses. Thirdly, the interviewer recorded the answers provided by the interviewee without exercising personal discretion or bias. This approach aimed to capture the interviewee’s responses as they were given accurately. Lastly, the interviewer minimized personal judgment and feedback during the interview process. This was done to create an environment that facilitated honest and unbiased responses from the interviewees. By adhering to the structured interview protocol, the study aimed to collect reliable and consistent data from the participants, enhancing the validity of the findings.
Four participants from the client organization, two from the main contractor, and one from the manufacturer (Tab.3), were asked four pre-worded questions in the same order, as shown in Tab.4. All interviewees fulfilled three participant selection criteria. The first criterion was that participants needed to be actively engaged in utilizing the blockchain system within the project, demonstrating their fundamental understanding of blockchain technology. This ensured that the participants had practical experience in using blockchain technology, which would provide valuable insights into its application in the construction industry. The second criterion was that participants needed to be closely collaborating with the research team, employing the suggested guidelines to visualize the blockchain-based DMP. This ensured that the participants had a good understanding of the study’s objectives and were committed to use the proposed guidelines in practice. The third criterion was that participants needed to demonstrate a willingness to provide feedback on the suggested guidelines. This ensured that the participants were willing to engage in a constructive dialog with the research team and provide valuable feedback on the suggested guidelines. The responses provided by the interviewees were documented and transcribed to enable further examination.
3 Analytical results
3.1 Status quo of data visualization methods on blockchain systems
The Sankey chart presented in Fig.3 offers a graphical overview of the Tab.2 data extracted from studies visualizing blockchain-based DMP for different CEM activities. In the chart, the size of a rectangle indicates the number of actual descriptors mentioning data inputs, blockchain systems, and data visualization tools and mediums for various CEM phases and applications. Among on studied 49 cases, multiple descriptors can be found in one case.
3.1.1 Blockchain platforms and types
In most reviewed cases, the uploaded data was recorded in Hyperledger Fabric (34 cases), an open-source platform for all industries, including construction (
Sheng et al., 2020). Data was recorded in 15 cases on the blockchain platform Ethereum, which has a native cryptocurrency (Ether). This indicates that the construction industry can take advantage of what cryptocurrency can offer, such as automatic progress payments (
Ahmadisheykhsarmast and Sonmez, 2020). Only one case built a custom blockchain to record data, likely because to do so requires in-depth understanding of blockchain technology and CEM processes (
Lu et al., 2021a). A notable trend is that the number of cases using a Hyperledger Fabric platform has increased over time while the number of cases adopting the Ethereum platform have shown a decreasing trend (Fig.4(a)).
We observed that permissioned blockchain was mainly selected for recording data. In a permissioned blockchain, users are preauthorized to participate, thereby ensuring the data privacy of construction projects (e.g.,
Tao et al., 2022). Permissionless blockchains were adopted in only five cases, mainly because data transparency was a priority. Fig.4(b) shows an increase in adoption of permissioned blockchains over the last two years due to increasing data privacy concerns.
3.1.2 Data inputs
The pattern of data inputs is summarized as follows, based on Tab.2 and Fig.5.
(1) Quality and payment records were the most popular data inputs, appearing in over 41% (26 over 64) of descriptors. Construction quality data are still recorded mainly on paper, risking document loss and data manipulation, jeopardizing quality accountability (
Wu et al., 2021;
Lu et al., 2022a). The immutability of blockchain allows it to securely record quality-related data, effectively addressing the issue of information fraud (
Zhong et al., 2020;
Lu et al., 2021a). Payment records were primarily for reducing late interim payments in construction projects. Blockchain-enabled smart contracts have attracted increasing attention from the construction industry because they decentralize the execution of contract terms to ensure payment certainty (
Hamledari and Fischer, 2021a).
(2) Construction progress records were the second most popular data inputs, appearing in over 14% (9 over 64) descriptors. Recording construction progress on a blockchain can bring increased transparency and accountability. Thus, all parties involved in the construction project can access consistent progress data and can make informed decisions (
Ahmadisheykhsarmast and Sonmez, 2020). Additionally, blockchain can help reduce disputes and delays by providing immutable and tamper-proof records of all construction activities (
Wu et al., 2022b).
(3) Design files, logistics status, environmental data, operation and maintenance and safety records were not frequently uploaded to blockchain systems in the reviewed cases. This may be attributed to the specialized nature of blockchain technology, such that individuals without expertise in this area, including construction practitioners, may find it challenging to engage with and utilize blockchain effectively (
Xue and Lu, 2020). Therefore, the visualization of DMP on blockchain is necessary.
(4) In the remaining cases, multiple types of records were uploaded to the blockchain. In these studies, blockchain was mainly used for data immutability and transparent sharing (e.g.,
Kim et al., 2023;
Zhao et al., 2023).
The trend of data inputs for the reviewed cases is summarized in Fig.5. Before 2021, the types of data input for recording on the blockchain system were less diverse than after 2021. Among the pre-2021 cases, quality (e.g.,
Sheng et al., 2020;
Wang et al., 2020) and payment (e.g.,
Elghaish et al., 2020) records were of most concern. In 2021, increased attention was paid to inputting logistic status (
Li et al., 2021b;
Lu et al., 2021b) and design files (
Tao et al., 2021) to the blockchain system. In 2022, the number of cases inputting records of operation and maintenance (
Yang et al., 2022), environment (
Zhong et al., 2022), and safety (
Xu et al., 2022) increased, while in 2023, environmental records began to be actively submitted to blockchain (
Wu et al., 2023).
3.1.3 Visualization tools and mediums for data submitted on blockchain
Concerning the selection pattern of the data visualization tools, most studies (26 out of 77 descriptors) used dashboards to present blockchain-based DMP. Dashboards allow construction project teams to visually present complex data collected from CEM activities in one place (e.g.,
Wu et al., 2022b). It organizes, groups, and presents essential project information with a few clicks (
Pradeep et al., 2021). The second most used visualization tool was explorers (25 descriptors), such as Hyperledger Explorer. These platform-provided explorers are Web application tools to view, invoke, deploy, or query transaction data (
Elghaish et al., 2020). Comparatively, charts, process maps, and tables were used less frequently. One reason may be that describing the data submitted to blockchain platforms in many solutions does not make it intuitive and easy for users to understand. For example, users may not know whether the recorded data was successfully packed into blocks and stored in ledgers immutably.
The trend of visualization tools for blockchain-based DMP can be observed in Fig.6(a). The number of descriptors using charts, explorers, and dashboards were used less frequently. For example, Hamledari and Fischer (
2021a) employed charts to help demonstrate an automated construction payment process based on blockchain-enabled smart contracts. In addition, many descriptors (e.g.,
Jiang et al., 2021) employed the explorers provided by the platforms to view the number of transactions and blocks generated by the case studies. Self-designed dashboards were commonly used to upload and query transaction data due to their customizability and visibility (e.g.,
Sigalov et al., 2021).
Most studies (37 descriptors) visualized the DMP by allowing users to invoke stored transactions from blocks. Eighteen descriptors visualized smart contracts, allowing users to understand the automated process of contract execution, and four descriptors visualized network information to make the blockchain network (e.g., project participants) transparent. However, there were six descriptors where blockchain details were not visualized, which could limit user satisfaction. Fig.6(b) reveals that more descriptors showing blockchain components and smart contracts have appeared in the last two years. For example, Tao et al. (
2022) illustrated how design files are converted into transactions and packaged into blocks and execution processes of smart contracts.
3.1.4 Visualized data in CEM phases and applications
More than half of the descriptors (32) covered the construction stage, and about 18% (11 out of 62) of descriptors covered offsite or offshore prefabrication housing production. In contrast, only a few descriptors (7 out of 62) concerned transportation. Only 6 descriptors focused on pre-construction and design phases, respectively. Regarding applications, most descriptors (19 out of 73) applied blockchain to record data because of its immutability. Also, many descriptors (15 out of 73) focused on combined applications. For example, Wu et al. (
2022c) adopted blockchain to avoid the single point of failure (SPOF) of IoT and BIM. Almost the same number of descriptors focused on secure payment (12 descriptors) and internal administration (11 descriptors), respectively. Blockchain was less explored in information sharing (10 descriptors), and encryption was even less used in privacy protection (4 descriptors).
In 2020, blockchain-based DMP was concentrated in the construction phase (Fig.7). Among post-2020 descriptors, increased attention was paid to recording data in offsite housing production, transportation, and design phases. Among those post-2020 descriptors is Lu et al. (
2022a)’s blockchain e-Inspection 2.0 system developed to supervise modular housing production. This system is adopted in our case study, as mentioned above. Li et al. (
2021b) adopted blockchain to monitor the supply chain in prefabrication construction. Pradeep et al. (
2021) adopted blockchain for liability control in the design phase. Another notable trend is that the number of descriptors applying blockchain for information sharing, privacy protection, and combined application has increased over time. Among those descriptors, Lee et al. (
2021) proposed a blockchain framework to support accountable information sharing in construction projects. Recently, Tao et al. (
2022) proposed a blockchain-enabled framework to protect sensitive design data. Wu et al. (
2022c) aimed to link the permissioned blockchain to the IoT-BIM platform for offsite production management in modular construction. These trends expand the visibility of blockchain-based DMP in various CEM applications.
3.2 Challenges
The challenges of visualizing blockchain-based DMP submitted to blockchain systems are summarized below.
• Data diversity: construction projects involve a wide range of data, such as design files, quality records, progress approvals, and logistic status. Each data type may have its unique format, structure, and requirements. Visualizing these diverse data types can be complex and time-consuming. Additionally, ensuring the accurate visualization of different data sources can pose challenges.
• Visualization tools: there is a lack of guidelines for users and system developers to guide their selection of appropriate blockchain visualization tools. Thus, visualized data on blockchain systems may not be understood by construction practitioners, thereby reducing users’ trust in such systems.
• Visualization mediums: without criteria for selecting visualization mediums, there are no clear user requirements as to what details should be visualized to reflect that the DMP can be visualized by certain blockchain components to increase user trust in blockchain systems.
• Visualization domain: there are no clear reminders for system developers and users about what types of CEM applications and phases data visualization will involve, leading to miscommunication on blockchain visualization.
Section 4 will present proposed guidelines for visualizing blockchain-based DMP in construction projects, based on a review of 49 real-world cases.
4 Guidelines for visualizing blockchain-based DMP in construction projects
4.1 Five-step guidelines
The proposed guidelines for visualizing blockchain-based DMP in construction projects are demonstrated in Fig.8 and are introduced below.
Step 1: Targeting the visualization domain. Through project meetings, the project team must first discuss which phase of CEM needs to involve blockchain-based DMP. After that, they need to determine the application domain, i.e., the purpose of using the blockchain. A series of questions, such as “should the blockchain ensure data immutability”?, “Should the blockchain be used to improve information sharing”?, must be raised during project meetings.
Step 2: Planning blockchain visualization. Since CEM activities can generate various types of data, including quality and safety data, the project management team must determine the type of data input to be recorded on blockchain systems. Depending on the degree of network centralization, blockchain systems can be permissioned or permissionless (
Wu et al., 2022c). A permissionless blockchain is accessible to everyone (
Yang et al., 2020), while control of the permissioned blockchain is allocated to pre-authorized organizations participating in the operation of the system. The teams must also choose a blockchain platform such as Bitcoin, Ethereum, or Hyperledger Fabric, all of which have different focus domains, or they may build a customized blockchain. Lu et al. (
2022b) developed a multicriteria decision matrix (MCDM) for project management practitioners, which will support blockchain type selection and evaluate blockchain platforms. Users of our guidelines are suggested to use this MCDM, after which system developers should work with project teams to develop or customize blockchain systems.
Step 3: Choosing a visualizing tool. According to the specific project situation, project teams should work with system developers to select their preferred visualization tool based on their advantages and disadvantages (Tab.5) through a point-based scoring method. For each advantage of each tool in Tab.5, one point can be awarded if they meet the project requirements; otherwise, no point is given. Similarly, for each disadvantage of each tool, one point is deducted if it does not meet the project requirements; otherwise, no point is deducted.
Step 4: Selecting a visualization medium. When deciding on visualization mediums for a blockchain system, it is important to consider the level of trust that users have in the system. Blockchain components, smart contracts, and network activities can all be useful in increasing trust by providing transparency and security. Blockchain components can create an immutable ledger that records every transaction, ensuring that no data are lost or altered. Smart contracts can automate processes and ensure that all parties involved in a transaction are held accountable. Network activities can provide real-time monitoring and alert users to any suspicious activity. By implementing these visualization mediums, users can have greater confidence in blockchain. The finalization of data visualization processes entails presenting a solution that successfully conveys the processing of data on blockchain systems. By presenting a solution that effectively communicates the data, stakeholders can obtain valuable insights from the visualization and develop trust in blockchain systems.
Step 5: Fine-tuning the visualization solution. This is a critical step in ensuring its effectiveness and usability. By soliciting feedback from users, it becomes possible to understand any potential issues they may have encountered. This feedback can then be used to make necessary adjustments and refinements to the visualization solution. This iterative process helps to improve the clarity, comprehensibility, and overall user experience of the visualization.
4.2 Demonstration in a case project
The applicability of the guidelines developed here is demonstrated in a real-life case, where a blockchain system was customized to record MiC offsite production quality data. The project team wanted to visualize blockchain-based DMP to enhance trust in the blockchain system. Thus, the project and research teams were invited to use the proposed guidelines to visualize the MiC quality blockchain-based DMP.
The guidelines shown in Fig.8 were followed to determine the target CEM phase and application domain of the blockchain system. In Step 1, since the project client has high requirements for the quality of modules produced by the offsite MiC manufacturer, offsite production is selected as the target CEM phase for the blockchain application (Fig.9(a) and Fig.9(b)). In addition, the project team selected immutable records as the application domain (Fig.9(c) and Fig.9(d)).
In Step 2, photos showing the production quality of the MiC module at each checkpoint were selected as data input to be uploaded to the blockchain system (Fig.9(e)), allowing project stakeholders from Hong Kong (e.g., authorized persons, registered structural engineers) to inspect and endorse the quality remotely through the decentralized consensus mechanism of the blockchain system (Fig.9(f)).
In addition, the project team used the organization criteria of the MCDM developed by Lu et al. (
2022b) to choose the blockchain type (in the previous case project) (Fig.10(a)). The project team believed permissioned blockchain could meet their requirements based on criteria such as range of use, transparency, centralization, auditability, cost, privacy, security, and scalability (Fig.10(b)). Also, the project team selected Hyperledger Fabric as the platform by using the performance criteria of the MCDM (in the previous case project) (Fig.10(c)). The project team believed that transaction throughput, block time, consensus network, smart contract language, cryptocurrency availability, and transaction fees of Hyperledger Fabric could meet their requirements in projects (Fig.10(d)).
Subsequently, the blockchain system developed in the previous project (
Lu et al., 2022a) was customized for the case project of this study. The customization was mainly achieved by adjusting the project participants and their permission level (Fig.10(e)).
In Step 3, the project team was requested to select a preferred data visualization tool. Based on the pros and cons of the available visualization tools in Tab.4, the project team held two workshops to conduct a scoring-based strength and weakness analysis to select the appropriate tool. As a result, the dashboard was selected as the visualization tool.
In Step 4, the project team selected the visualization mediums for the blockchain system. In a joint project meeting with the research team, the project team first selected the blockchain component to ensure that the production and inspection data of the modules during the offsite production phase could be successfully stored in the block and recalled when needed. Next, the project team selected the network as they wanted to ensure that peer nodes were active and not offline to store data in their distributed ledgers.
A dashboard was thereby developed to visualize blockchain-based DMP based on the selections and knowledge gained from Steps 1–3. Manufacturers submitted the data related to module offsite production via the front-end interface, and inspectors then endorsed the data through the decentralized network of the blockchain. Therefore, as shown in Fig.11(a), the dashboard displays the blockchain network by showing all users and their categories and locations. In this way, users can improve their trust in the blockchain system by understanding the active users in the network who submit and endorse production data and their corresponding locations. After endorsing the production data, the data are packed as transactions and stored in a block. The developed dashboard allows users to recall the corresponding production data in the block by searching the Module ID and Workstage, thus enhancing trust in the system by ensuring that the data are successfully endorsed and stored on the blockchain (Fig.11(b)).
In Step 5, a survey was conducted to collect user feedback in order to improve the developed blockchain dashboard. For example, a technical manager from the client pointed out that the dashboard should allow users to use the timeline search bar to find the corresponding production data submitted on a particular date on the blockchain system. Thus, the research team further developed an interface based on this feedback, as shown in Fig.11(c).
4.3 Assessment
After utilizing the guidelines in the visualization processes, individuals responded to four interview queries. The responses are summarized in the supplementary information in Appendix A. In response to Question 1, the interviewee from MiC manufacturer confirmed that the guidelines helped them understand the data submission process of MiC modules on the blockchain system because it helped frontline staff perceive and confirm that relevant photos were successfully submitted through the user dashboard developed by the research team. Therefore, the visualization processes enhanced their trust in the blockchain system. Main contractor interviewees also noted that they can now feel the presence of the blockchain system as they can now call up production data in blockchain ledgers. However, in addition to visualizing data submission, endorsement, storage, and invocation, they stressed that guidelines should also include guidance on how to visualize opportunistic events, such as alerting users where data has been manipulated. Likewise, project clients stated that the guidelines can guide users like them in perceiving DMP on blockchain systems, rather than incomprehensible coding.
When answering Question 2, interviewees from the project client organization and the MiC manufacturer pointed out that the guidelines have clear and straightforward steps to visualize blockchain-based DMP without wasting time. Interviewees from the project client organization further stated that another two benefits of the guidelines are the presentation of the pros and cons of various visualization tools and the usefulness of enabling practitioners to visualize and perceive data submission, endorsement, secure storage, and invocation processes on blockchain systems systematically. Interviewees from the project client organization, main contractor, and MiC manufacturer reflected that the guidelines could help bridge the knowledge gap between practitioners and blockchain system developers for visualizing blockchain-based DMP by allowing them to understand what system developers can do for them to visualize blockchain and propose corresponding user requirements.
Nevertheless, when answering Question 3, interviewees reflected on two disadvantages of the guidelines: (1) selecting the blockchain type and platform using the developed MCDM and choosing the visualization tool using the scoring method consume additional time, and (2) more explanation is needed in the guidelines to help users choose different visualization mediums. These crucial concerns should be addressed in the future. For Question 4, interviewees recommended providing an example of how to use the scoring method to select visualization tools, requiring blockchain system developers in the selection of visualization tools, attaching the developed MCDM as a sub-guide with some explanations, offering descriptions for visualization mediums that clarify how the data can be shown through them, and formatting the guide as a booklet for better readability and attraction purposes —all excellent suggestions for further study.
5 Conclusions
The study aimed to provide a set of guidelines for users to visualize data management processes (DMPs) on blockchain systems in the construction and engineering management (CEM) context. First, it identified the status quo of blockchain-based DMP visualization by reviewing 49 actual cases published in scholarly papers. It is discovered that current blockchain-based DMP are predominantly focused on safeguarding quality inspection and payment records in the construction phase of a project. Most of the systems adopted the Hyperledger Fabric platform and favored a permissioned type of blockchain. Dashboards were widely used to visualize blockchain-based DMP by only allowing users to invoke transactions from blocks for query purposes. Therefore, how to visualize blockchain-based DMP, including submission, endorsement, storage and invocation so that users have a sense of user-friendliness and trustworthiness has become the point of departure of this study.
Then, the research identified the challenges as seen in the blockchain-based DMP visualization approaches. First, heterogeneous data and non-standard DMP add to the difficulties. A lack of proper visualization tools and mediums, together with a poor understanding of the visualization domain, all challenge the current practices of blockchain-based DMP visualization. Building on the findings, guidelines were developed for users to visualize the blockchain-based DMP and thereby harness the powers of these systems in CEM. The guidelines comprise five major steps: (1) targeting the visualization domain, (2) planning blockchain visualization, (3) choosing a visualization tool, (4) selecting a visualization medium, and (5) fine-tuning the visualization solution. The usefulness of the guidelines was demonstrated and assessed in a case study of blockchain applications in offsite modular housing production.
This study brings both theoretical contributions and practical implications. Compared with the previous blockchain studies, the theoretical contribution of this study first lies in its systematic articulation of the status quo of blockchain-based DMP visualization in the context of CEM. Second, this study identifies key challenges in visualizing blockchain-based DMPs from the existing blockchain literature related to CEM. Third, this study develops novel guidelines that enable construction practitioners to collaborate with system developers to visualize and comprehend the processes of data submission, endorsement, secure storage, and invocation on blockchain systems.
The proposed guidelines for visualizing blockchain-based DMPs also have practical implications for construction stakeholders. First, the guidelines facilitate collaboration between construction practitioners and system developers by providing a shared understanding of how data submission, endorsement, secure storage, and invocation occur on blockchain systems. This collaboration can lead to more effective decision-making and problem-solving processes. Secondly, the proposed guidelines help to streamline decision-making processes. Clear visualization of the blockchain-based DMP processes enables construction stakeholders to make more informed decisions. By understanding the flow of data and the interactions between different entities on the blockchain, stakeholders can identify potential bottlenecks, inefficiencies, or vulnerabilities, leading to more effective decision-making and process optimization. Thirdly, the proposed guidelines help to enhance trust among stakeholders. Blockchain technology is known for its ability to provide trust and security. By visualizing the processes involved in DMPs on the blockchain using the guidelines, construction stakeholders can gain confidence in the integrity of the data and the overall system. This increased trust can foster better relationships among stakeholders, including contractors, clients, and regulators.
The limitations of this research present significant opportunities for future investigations. First, the proposed guidelines were only demonstrated in one case project. Future studies should test the guidelines in more CEM scenarios. Secondly, the evaluation of the proposed guidelines was conducted only in a qualitative manner. More systematic and quantitative assessment frameworks should be studied and the guidelines should be refined based on further evaluation. Thirdly, the project performance after adopting blockchain-based DMP visualization guidelines remains to be studied. Additional research is necessary to investigate how visualization solutions for blockchain-based DMP affect project performance in CEM.
Appendix A
The Author(s). This article is published with open access at link.springer.com and journal.hep.com.cn
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