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Articles | Volume XLVI-4/W5-2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-437-2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-437-2021
23 Dec 2021
 | 23 Dec 2021

TOWARDS EFFECTIVE PROJECT DOCUMENTATION, TRANSPARENCY, AND DATA-DRIVEN DECISION-MAKING THROUGH BIM-BLOCKCHAIN BASED APPLICATIONS

F. Raco, M. Stefani, M. Balzani, and L. Ferrari

Keywords: Digital documentation, BIM, Blockchain, Common Data Environment (CDE), Bigdata

Abstract. Even in the context of increasing digitisation, the construction sector continues to be characterised by redundancy, multiplication and, at the same time, a lack of transparency and disaggregation of data and information, leading to ineffective management of the time, costs and quality of the project life cycle. This paper shows the results of the development of an ICT application, TRL 4-5, based on the integration of Building Information Modeling and blockchain technologies and designed to foster digitisation processes in the supply chain, in the direction of greater transparency of information flows, knowledge-based organisations and decision-making processes based on unambiguous ordered data. Starting from a broader industrial research collaboration, the project involves a university spin-off, companies operating as system integrators and leaders in the customisation of BIM solutions for the Italian construction market. The project, launched as part of a network of public and private stakeholders established in 2019 and developed between September 2020 and March 2021, is part of a territorial development strategy financed by European Structural Funds. As a result, the research output is a prototype of ICT tool, which implements the Common Data Environment, CDE, making the life cycle management unambiguous, certified and clear. In this regard, the results of the project are meant to respond to the supply chain's need to encourage the digitisation and automation of processes, as well as to encourage the acquisition of unambiguous data, according to a big data approach.