LAUSR

Abstract Smart infrastructure has the potential to revolutionise how infrastructure is delivered, managed and automatically controlled. Data and digital twins offer an opportunity for this purpose. However, before using data to aid stakeholders for their decisions, one should have a data plan, collect useful data, assess the quality of the data, have the language for enabling communication related to data, manage the data and have or acquire the skills that are needed to integrate and analyse data. To this end, this paper aims to provide an explanation and description of several challenges related to the data. The article concludes by suggesting that the industry addresses the challenges related to the availability, accessibility, quality, volume, variety and longevity of data by considering user-centric approaches, blending methodologies and identifying the organizational needs. The industry should plan and act on these challenges as part of its data analytics strategies of today to expedite the artificial intelligence applications of the future.