From October 30th – 31st, DunavNET organizes a meeting on the topic of smart cities and sustainable development in order to present the official enrollment of the cities of Novi Sad and Subotica in the OASC Association. In addition, the event will present experiences gained through the introduction of smart services in several European cities, a panel with representatives of European projects, cities from Serbia and the domestic economy to discuss current activities, challenges and ways of cooperation.
During the event, world-renowned IoT experts will discuss the current state of smart and sustainable cities in the world, as well as what we can expect in the coming period. Within this framework, Open & Agile Smart Cities with support of EIT Digital, Digital Enabler and Engineering have been invited to host a workshop on data driven innovation, inviting all Serbian city representatives, who want to
- offer better services for their citizens based on better data;
- launch a process of data-driven innovation in their municipality;
- stimulate exchange on data between departments;
- learn about open source tools based on OASC mechanisms to better integrate data and make it visible.
A few details on the workshop’s agenda
Each and every municipality is collecting and storing vast amounts of the most important resource in today’s digital world: data. But often, data collected within a city or community is spread across different departments or city utilities. This makes it more difficult for the city administration to be aware of what data is available and which data needs to be collected in the future to help solve challenges a city faces – from traffic management to waste collection – in order to provide better services and, hence, quality of life for its citizens.
The participants in the workshop will have the chance to deal with issues like
- the pressing challenges that cities face nowadays
- datastorming phenomenon, i.e. the type of data available now and respective projections for the future
- opportunities to come, i.e. what datasets (current and future) might present opportunities to tackle our pressing challenges and of course, identify these opportunities.