Workshop to be held adjacent to the IEEE Smart Cities Conference (ISC2) 2021
Submission deadline June 30, 2021
Today, citizens can rely on applications to predict the fastest route from point A to B or consult personalized apps to suggest the best activity for a night out. City administrations and local communities also benefit from the increased predictability of urban processes and change, for example by relying on digital twins. While these systems help to reduce search costs or insecurities, they might fall prey to merely repeating historic patterns found in the data. How can we ensure that these applications still allow for serendipitous encounters instead of resulting in 'urban filter bubbles'? And to what extent current practices of data collection and predictive modeling are capable of dealing with uncertainties and unexpected events. Especially in the contemporary urban context, where resilience plays an important role, it is crucial that decision-makers are able to deal with the unexpected and not blinded by patterns from the past.
This workshop is open to all parties interested in discussing serendipity in the smart city. We welcome contributions from academics, innovators, local governments, and practitioners.
The topics of interest of this workshop include, but are not limited to:
Ethical implications of predictive systems in a smart city
Design principles for systems that engender urban serendipity
Applications of personalization in smart cities
Bias and inequalities in urban data
User evaluations of urban serendipity
Governance models of urban serendipity
Business models for urban serendipity
Volunteered geographic information to encourage data diversity
Predictive and pattern modelling on open linked data
(Open) data management
Digital twin applications for predictive analysis
Research papers reporting original results as well as position papers proposing novel and ground-breaking ideas pertaining to the workshop topics are solicited. Accepted papers will be published in IEEE ISC2 conference proceedings.