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Review of Big Data Integration in Construction Industry Digitalization

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TLDR
In this paper, the authors present a comprehensive study of the literature, investigating the potential application of big data integration in the construction industry, and present the current utilization, the issues, and ways for potential works along with the challenges companion with the implementation.
Abstract
The 2030 agenda for sustainable development has embraced the importance of sustainable practices in the construction industry. In parallel with the revolution of industry 4.0, the advancement of technology offering advanced data management which the construction practices have been revolutionized by the capability to process and extract value from data. This phenomenon attracts the requirement of Big Data (BD). The construction industry deals with large volumes of heterogeneous data; which is expected to increase exponentially following an intense use of modern technologies. This research presents a comprehensive study of the literature, investigating the potential application of BD integration in the construction industry. The adoption of such technologies in this industry remains at a nascent stage and lags broad uptake of these technologies in other fields. The Construction Industry is driving to boost its productivity through the implementation of data technologies; hence, significant research is needed in this area. Currently, there is a lack of deep comprehensive research on BD integration applications that provide insight for the construction industry. This research closes the gap and gives an overview of the literature. The discussion presented the current utilization, the issues, and ways for potential works along with the challenges companion with the implementation.

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References
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Journal ArticleDOI

Beyond the hype

TL;DR: The need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats is highlighted and the need to devise new tools for predictive analytics for structured big data is reinforced.
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The rise of big data on cloud computing

TL;DR: The definition, characteristics, and classification of big data along with some discussions on cloud computing are introduced, and research challenges are investigated, with focus on scalability, availability, data integrity, data transformation, data quality, data heterogeneity, privacy, legal and regulatory issues, and governance.
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Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings

TL;DR: The proposed solutions for collecting and managing sensors’ data in a smart building could lead us in an energy efficient smart building, and thus in a Green Smart Building.
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Big Data in the construction industry

TL;DR: This paper presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry and discusses the future potential of such technologies across the multiple domain-specific sub-areas of theConstruction industry.
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EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology

TL;DR: This paper looks into existing efforts in obtaining an ifcOWL ontology from the EXPRESS schemas of IFC and analyses which features would be required in a usable and recommendable ifcowL ontologies.
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Why big data skills is important in construction industry ?

The paper does not explicitly mention why big data skills are important in the construction industry.