By Nidhi DhullReviewed by Susha Cheriyedath, M.Sc.Nov 6 2024A recent review article published in Advanced Engineering Informatics explored the present and emerging data management approaches in construction informatics using a critical interpretive synthesis (CIS). Current technologies such as Open Schema, Information Container, Common Data Environments, Linked Data, and future Web3 technologies such as blockchain and decentralized data protocols were discussed.
Study: From BIM to Web3: A critical interpretive synthesis of present and emerging data management approaches in construction informatics. Image Credit: metamorworks/Shutterstock.com
Background
Complex construction projects require the generation, revision, and transfer of large amounts of data across multiple stages and fields. Despite adopting digitization and data-driven processes, cross-phase and cross-party data integration in the construction industry is challenging. This is due to a fragmented industry structure characterized by non-standardized collaboration among various stakeholders.
The information silos resulting from multiple models and tools limit opportunities for data processing, extractability, and usability. Therefore, interoperability during data integration is necessary. This requires effective data integration methods between different systems, tools, and stakeholders.
However, current construction informatics is unintegrated and confusing. To address this, the researchers adopted the CIS method to review theoretical and empirical literature and derive relevant interpretations. Using CIS rather than a systematic literature review facilitated a more nuanced and context-specific analysis of the research in the field of construction informatics.
Data Management in Construction Informatics
Two main dimensions of data management in construction research were identified: storage and processing mode. The storage modes in construction informatics include local, cloud, and web-of-data. These govern the accessibility of data and reflect the evolution of technology and increasing online availability of generated data.
The local mode is prone to risks such as data loss, hardware failure, and theft, and the cloud mode raises concerns about data security, privacy, and ownership. Alternatively, the Web-of-data mode integrates heterogeneous data from multiple sources into a unified, interconnected platform. This facilitates advanced analytics, machine learning, and artificial intelligence applications, enabling the extraction of insights and data-driven decision-making.
Data processing involves technology and analytical methods to transform, manipulate, and analyze data for informed decision-making on business operations. This enhances project management, safety, quality control, and sustainability in construction through real-time insights into project performance, identifying areas of improvement, and predicting potential problems before they occur.
Current Data Management Approaches
CIS identified six distinct categories of data management: open schema, closed schema, open source frameworks, traditional software, information containers, and Web3. These can be mapped using the two data management approaches: storage and processing modes.
Building Information Modeling (BIM) represents how data management transcends the boundaries of a single technology. According to one strategy, BIM can be implemented using a local storage paradigm combining closed and open schema data. This model synchronizes across different internal servers by using information containers. Alternatively, a cloud-based approach can be adopted using a closed schema, an open schema, or an open-source framework.
Similarly, Common Data Environments can be technically implemented using cloud-based infrastructures employing information containers, open-source frameworks, or both closed and open schema strategies.
Integrating Web3 Technologies
Web3 systems can potentially transform data storage, data access, ownership mechanisms, and data management. Specifically, decentralized Web3 networks can displace traditional, centralized paradigms. However, Web3 technologies are generally separated from traditional data management strategies and lack an integrated perspective despite their intrinsic nature as data management systems.
Layer 1 (L1) technologies in the Web3 stack, including zero/low trust interaction protocols and data distribution protocols, promote broad access and interconnectivity of data across various nodes within the network, along with providing mechanisms for data processing. Specifically, blockchain allows accessibility and verifiability of data points across the network of nodes. Similarly, decentralized storage networks (DSNs) handle structured data points that can be accessed, updated, and manipulated individually.
Web3 can be a disruptive solution to the inherent systemic data management constraints. Moreover, Web3 technologies allow the integration of decentralization capabilities in conventional construction data management practices. Therefore, the potential of such collaborations in various construction-related scenarios should be explored objectively.
Despite the potential advantages of Web3 in improving individual use cases and streamlining processes, it is not sufficient to address systemic limitations in construction informatics.
Conclusion
Overall, the researchers introduced a pioneering framework integrating emerging Web3 technologies for data management in construction informatics. The proposed framework can organize data management procedures and minimize uncertainty in the incorporation of Web3 technologies.
However, this study has certain limitations. The rapidly evolving concept of Web3 technologies and their complex integration with existing data management strategies are challenging and not addressable in this study. Therefore, the researchers suggest future studies on the empirical validation of the proposed framework through small-scale practical implementations and projects.
Despite these limitations, the researchers claim the practical relevance of the presented framework to the construction industry. Implementing Web3 technologies can significantly enhance data transparency and collaboration, resulting in more effective and efficient project management. Web3 technologies should be gradually integrated into current construction informatics, starting with pilot projects designed to effectively measure impact and scalability.
Journal Reference
Bucher, D. F., Hunhevicz, J. J., Soman, R. K., Pauwels, P., & Hall, D. M. (2024). From BIM to Web3: A critical interpretive synthesis of present and emerging data management approaches in construction informatics. Advanced Engineering Informatics, 62, 102884. DOI: 10.1016/j.aei.2024.102884, https://www.sciencedirect.com/science/article/pii/S1474034624005329
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