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Using Network Analysis Theory to Extract Critical Data from a Construction Project

Author(s): ORCID
ORCID

Medium: journal article
Language(s): English
Published in: Buildings, , n. 6, v. 13
Page(s): 1539
DOI: 10.3390/buildings13061539
Abstract:

Construction projects are inherently complex and entail extensive information processing. Thus, they require effective information management, which, in turn, requires the preservation of critical construction data (CD). Although BIM and blockchain methodology use the “change type of query and storage for data management” to improve the service quality of data, data redundancy still causes inefficient retrieval. Moreover, project managers face various source limitations, which prevent the contents of the database from being managed efficiently. This study uses network analysis theory to design an information network (IN). Critical CD were extracted, and an IN structure was built using data from construction practices (network nodes) and data relation (network links). Three metrics were used for performance evaluation of the data references and data delivery. The refurbishment of heritage buildings in Kinmen, Taiwan, was used as a case study to extract critical CD such as the “inspection record checklist” and “architect design plan drawing”. Lastly, CD can be applied as the elementary item of a backstage database for BIM and blockchain applications of DM. The combined system of critical DM can play an important role in obtaining comprehensive information for a construction project. Customized metrics of IN analysis can be developed as an integrated composite to decide the priority of CD.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10732811
  • Published on:
    04/08/2023
  • Last updated on:
    07/08/2023
 
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