*2.1. New Real Time Information*

The rapid developments in ICT, leveraged through advances in hydroinformatics, have created the basis for a phenomenal increase in the types and amounts of water-related data collected and analyzed, following the trend (and to some extent hype) of the so-called Big Data currently evident in numerous other fields and sectors [24]. Although the volume of water data currently collected by the sector is certainly unprecedented, attributed to an increasing deployment of dedicated sensors of various types, the data in the water sector cannot really be considered big, at least not yet. Water data are often structured data and do not usually include the main types of unstructured data (such audio, images, video, and unstructured text) that account for 95% of big data at the global scale [24]. A notable (and promising) exception is when crowdsourcing is also taken into account as a means of supplementing data obtained from more traditional sources [25]. The arrival of big data is also coinciding with a strong movement by individuals, learned societies and governments to open data for the benefit of individuals and society in general. The availability and use of open data—that anyone can access, use or share—can also increase opportunities for the collaboration and engagemen<sup>t</sup> of stakeholders, particularly in cities. The rise of the 'Smart City' concept, where ICT (and IoT) are used

to enhance a city's livability, workability and sustainability, is another factor that impacts on the use of big data in urban water managemen<sup>t</sup> [26]. The developments in this (growing) nexus between water and ICT (often termed digital water, Water 4.0 or water informatics), allow water companies to now be able to monitor in (near) real time their entire supply and value chain, from the sources to the consumers' tap and then 'downstream' to the wastewater plant. Smart sensors and smart meters (e.g., [27]) are becoming ubiquitous allowing for a substantial increase in coverage (e.g., [28]), resolution (e.g., [29]) and diversity (e.g., [30]) of water-related information, including water quality [30–32], which has long been the most difficult water characteristic to reliably monitor remotely. Interestingly, new water related information is not only collected by smart sensors and devices. It is also increasingly collected by the citizens/water users themselves. For example, the paper-based water quality sensor and smartphone that was used in Sicard et al. [33], or work by Farnham et al. [34] on using citizen-based water quality monitoring for combined sewer overflows.
