To maintain the reliability and accuracy of measurement outputs from flow meters, they are typically calibrated and maintained under fixed time-intervals, for example once every year, this is known as time-based calibration (TBC). However, as the world continues to move forward with digitalisation strategies, there is an increased interest in adopting advanced modelling techniques to analyse big data gathered in industry and enable condition-based monitoring (CBM), whereby the need to repair or recalibrate flow meters is dependent on their condition which is detectable in the data. This approach will ensure that no meters are taken out of operations for unnecessary maintenance as well as minimise any unexpected downtime and improve end-users strategical and operational decision-making. To prevent data from becoming the new plastic, high-quality input data is needed. This requires end-users to have a well maintained and structured data system and a better understanding of the intricacies that lie within the data. Input from industry experts is also needed to account for human experience in specific scenarios to optimise the information that can be extracted and realise the true impact of data modelling techniques for industry. Consequently, to better understand the requirements and specifications from end-users from different industries, TÜV SÜD National Engineering Laboratory (hereinafter NEL) has conducted surveys as well as engaged with clients in webinars, conferences and commercial projects to construct a user requirements specification (URS) on CBM and users' expectations and requirements.