The datafication of contemporary cities increases the opportunity for predictive analysis, which promises great efficiency gains. Citizens can rely on applications to predict the fastest route from point A to B or consult personalized recommender systems 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. Local administrations, for example, increasingly rely on virtual representations of their city to inform decision making and long-term policy planning, so-called ‘digital twins’.

While these systems help reduce search costs or insecurities, they might fall prey to repeating historical patterns found in the data merely. In this way, they risk reducing serendipity, which happens when we encounter resources that we find interesting in unplanned ways. Indeed, in the case of personalized recommendations, these systems are often built on the premise that users are looking for information similar to what they (or similar users) have been looking for before. The trend is towards serving predictable, popular and homogeneous content, often referred to as resulting in “filter bubbles”. In an urban context, this means that people are no longer exposed to the diversity of cities and their inhabitants, which has negative consequences for the open and democratic character of the city.

A similar line of thought can be expressed for applications that inform decision-making at policy levels. Here, the question is to what extent current practices of data collection and predictive modelling are capable of dealing with uncertainties and unexpected events. Especially in the contemporary urban context, where resilience plays an important role, decision-makers must deal with the unexpected and not blinded by – perhaps departed – patterns from the past.

This is a timely issue and there is a societal call for a transition towards applications that promote diversity and serendipity. However, what is missing today is a clear understanding of the meaning and value of serendipity in urban environments, and how this can be engendered in digital applications that are thriving in today’s smart cities.

Those questions are not merely normative in nature, but hold great challenges in terms of technical feasibility. How susceptible to learned biases are contemporary information systems, and can this problem be alleviated by diversifying the training data? Are publicly available data resources sufficiently diverse themselves, and if not, how can we gather more information? How can the design of the application allow for serendipitous actions? How can predictive models account for unexpected events?

The goal of this workshop is to explore this timely topic and address open challenges and discuss novel ideas. We aim to bring together an interdisciplinary group of researchers, with a shared interest in the relationship between smart cities and serendipity.

Research papers reporting original results as well as position papers proposing novel and ground-breaking ideas pertaining to the workshop topics are solicited.

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

We welcome contributions covering a wide range of domains, such as information system design, user studies, policy research, philosophy of the city, urban planning, open data, business modelling, and recommender systems research. This workshop is open to all parties interested in discussing the role of information systems in smart cities and how they could impact the democratic and serendipitous character of urban life. We welcome contributions from academics, innovators, local governments, and practitioners.