Most ancient cities were built close to water. Some by the sea, some close to rivers, but always for the same reasons: to access the water itself, its resources and its convenience for long-distance trade. Water also makes for beautiful cities with important touristic appeal. Despite all the advantages, developing a city close to a water source seriously complexifies decision-making processes. “Water brings economic growth, but also social and environmental stresses like potential floods. It’s difficult to estimate the impact and consequences of public action. And that’s not even considering multilevel decision processes adopted by public administrations, a history of decision-making driven by intuition rather than data (until the last decade or so), and the fact that decision makers often struggle to properly use available data,” says Filareti Tsalakanidou, research associate at ITI-CERTH and one of the coordinators of the CUTLER (Coastal Urban developmenT through the LEnses of Resiliency) project. According to Tsalakanidou, what waterfront cities really need is to incorporate Big Data and data science into their policymaking process. By creating a platform to that effect, she hopes these cities will finally be able to live up to their full potential. “We’ve recently seen an explosion in the amount of data generated by cities every day. So why not put it to good use? Our proposal consists in combining real-time data from hardwired sensors, user-contributed content (from social media for instance), official statistical data and GIS data. By doing so, we can considerably improve policymaking,” she adds. CUTLER’s main innovation is a decision-support platform based on an innovative methodological approach for policy development. The platform compiles data from all sources mentioned above and uses big data analytics methods to measure economic activity, assess environmental impact and evaluate the social consequences of examined policies. The resulting evidence can then be used to support the decision-making process. Concretely, the CUTLER platform relieves decision makers of considerable burden. First, it enables access to data from public administrations, the private sector, academia and research institutions while providing a robust legal framework for the use of this data. It offers a holistic view of policy problems by presenting relevant data, modelling the impact and consequences of decision-making, and capturing citizen feedback. Last but not least, it modernises public administrations. It does so by bridging the gap between big data and existing policy-development routines while smoothly introducing new IT applications into their daily routine.
Five cities, different water bodies and urban development policies
The CUTLER platform is being extensively tested in five cities: Thessaloniki (Greece), Antalya (Turkey), Antwerp (Belgium), Cork (Ireland) and Vicenza (Italy). In Antwerp, the pilot focuses on climate change impact and adaptation scenarios, examining measures such as ‘garden streets’ to reduce flooding. In Cork, the team focused on enabling visitor access to Camden Fort Meagher – a fort built in the 16th century in Cork Harbour – by creating new access points and facilities. “We’ve also been working with the authorities of Antalya to increase visitor numbers at the Düden Waterfall area while implementing measures to maintain the water level throughout the year,” notes Tsalakanidou. “Meanwhile in Vicenza, we’ve been examining possible defensive measures against flooding of the Bacchiglione River. Finally, in Thessaloniki, we focused on optimising a controlled parking system near the Thermaikos Bay.” With the different software components and theoretical methodologies now refined, the team will begin producing the final versions of the pilot-specific dashboards, as well as disseminating the project’s outcomes. “Our platform will hopefully lead to more balanced, precise, resilient, legitimate and effective decisions,” Tsalakanidou concludes.
CUTLER, decision-making, waterfront cities, coastal urban development, Big Data