Data Quality Assurance in Environmental Product Declaration Electronic Database: An Integrated Clark-Wilson Model, Machine Learning and Blockchain Conceptual Framework.

Construction materials environmental product declaration (EPD) is becoming an essential data source for whole building life cycle assessment (WBLCA). In recent years, EPD programme operators have begun to digitalise the existing EPDs into a more useful data format through an electronic database. Therefore, it is essential to ensure the quality of EPD inserted in this electronic database in order to produce a reliable WBLCA. This paper aims to develop a conceptual framework for data quality assurance (DQA) in the EPD electronic database. The paper methodology is divided into two phases. Firstly, existing works of literature were examined to reveal the methods or technologies that can support DQA in an electronic database. Secondly, ten EPDs were reviewed to ascertain the data structure of existing EPDs, which will be used to determine the data to be extracted in the EPD electronic database. The information generated was used to develop a conceptual framework for a DQA embedded database design for construction materials EPD. The paper revealed that the Clark-Wilson model, blockchain and machine learning could enhance DQA in EPD electronic database. These findings have direct implications for the development of future electronic databases for EPDs. Future studies would leverage this conceptual framework to develop a working prototype for the EPD electronic database.