This article presents the urban data visualization (UDV) card deck, a tool designed to facilitate reflective discussions and inform the collaborative design process of urban data visualization. The UDV card deck was developed to bridge the gap between theoretical knowledge and practice in workshop settings, fostering inclusive and reflective approaches to visualization design. Drawing from urban visualization design literature and the results from a series of expert workshops, these cards summarize key considerations when designing urban data visualizations. The card deck guides different activities in an engaging, collaborative, and structured format, promoting inclusion of diverse urban actors. We introduce the card deck and its goals, demonstrate its use in four case studies, and discuss our findings. Feedback from workshop participants indicates that the urban data visualization card deck can serve as a supportive and reflective tool for urban data visualization researchers, designers, and practitioners.

Transdisciplinary research processes often involve the integration of knowledge and stakeholders from various backgrounds. Here, we introduce the story of the research project AMA (A Mindset for the Anthropocene) on the role of mindsets in the context of sustainability and present an interactive visualization tool that we developed for stakeholder mapping and research communication. Through this platform, we provide access and navigation to everyone interested in this field of research and we have simultaneously created a channel for all stakeholders to co-create content. Here, we describe the design and functionalities of the platform and the participatory way it was developed as part of our stakeholder engagement. We discuss upon how such a design allows for reflection of potential biases in transdisciplinary research processes and simultaneously catalyzing self-organization in stakeholder networks.

Taxonomy building is a task that requires interpreting and classifying data within a given frame of reference, which comes to play in many areas of application that deal with knowledge and information organization. In this paper, we explore how taxonomy building can be supported with systems that integrate machine learning (ML). However, relying only on black-boxed ML-based systems to automate taxonomy building would sideline the users’ expertise. We propose an approach that allows the user to iteratively take into account multiple model’s outputs as part of their sensemaking process. We implemented our approach in two real-world use cases. The work is positioned in the context of HCI research that investigates the design of ML-based systems with an emphasis on enabling human-AI collaboration.

As urban areas around the world seek to transform themselves into smart cities, new technologies are being interwoven into the urban fabric that surrounds us. This process is often technology-driven and revolves around issues of quantification, cost reduction, and efficiency. This perspective is increasingly being challenged by more inclusive perspectives that seek to empower civil society and which focus on its needs and demands. A major concern with smart city technologies in public spaces is the lack of protection for individual privacy as a result of surveillance. In this paper, we have chosen the use case of traffic counting as an example to illustrate how the use of advanced technologies and integrated planning strategies can shift the balance between administrative and business interests on the one hand, and privacy concerns on the other, towards a privacy-centric approach. We propose a privacy-centric planning and development approach for smart city technologies. Through our use case, we demonstrate a privacy-centric participatory development process that led to a prototypical technical solution for privacy-friendly and human-centric traffic counting. We conclude this paper by deriving suggestions for more privacy-friendly smart city development processes from our specific use case.

Effective use of data is an essential asset to modern cities. Visualization as a tool for analysis, exploration, and communication has become a driving force in the task of unravelling our complex urban fabrics. This paper outlines the findings from a series of three workshops from 2018-2020 bringing together experts in urban data visualization with the aim of exploring multidisciplinary perspectives from the human-centric lens. Based on the rich and detailed workshop discussions identifying challenges and opportunities for urban data visualization research, we outline major human-centric themes and considerations fundamental for CityVis design and introduce a framework for an urban visualization design space.

Abstract. We see more cartographic products in our digital world than ever before. But what role does cartography play in the modern production of cartographic products? In this position paper, we will argue that the democratization and diffusion of cartographic production has also led to the presumed “fading relevance” of cartography. As an argument against this notion, we highlight starting points for the field of cartography to improve modern cartographic production through its inherent cartographic knowledge.

With the continuing diffusion of Global-Positioning-System (GPS)-enabled technologies, the accumulation of spatio-temporal information is growing to unprecedented extends. Many use cases are centered around commercial data-driven services for citizens, companies, and government institutions, as well as academic research. Aside from these domains, a number of applications try to enable citizens to explore their own data, instead of merely using their data to drive a certain third-party service. This article investigates research projects and applications that explore such reflective practices on personal user-generated spatio-temporal data. The exemplars discussed in this paper all share the overall goal to provide users with new insights into their own spatia-temporal behavior.

Over the last few years, data visualization, especially the visualization of spatial data, has become of ever-increasing importance in modern online journalism. While there is a broad range of research projects that focus on developing new methods, techniques, and implementations, empirical analysis of the potential implications of this trend is still rare. In this paper, the potential influence of visualizations in online journalism is in the focus: perceived credibility. The need for such empirical research is emphasized by presenting a preliminary quantitative study that assesses the impact of maps and information visualization on the perceived credibility of online news articles.

AbstractOver the last two decades, data visualisation has diffused into the broader realm of mass communication. Before this shift, tools and displays of data-driven geographic- and information visualisation were mostly used in expert contexts. By now, they are also used in casual contexts, for example on newspaper websites, government data portals and many other public outlets. This diversification of the audience poses new challenges within the visualisation community. In this paper we proposepersonal relevanceas one factor to be taken into account when designing casual data visualisations, which are meant for the communication with non-experts. We develop a conceptual model and present a related set of design techniques for interactive web-based visualisations that are aimed at activating personal relevance. We discuss our proposed techniques by applying them to a use case on the visualisation of air pollution in London (UK).

Location recommendation (LR) or rather location-based recommender systems (LBRS) are an integral part of modern location-based services (LBS). Most LR algorithms only focus on location-specific attributes when calculating recommendations, while completely ignoring the urban structure surrounding the locations. (In this paper we refer to a geographic coordinate (latitude and longitude) as position. Locations and places in contrast refer to physical entities e.g. a restaurant, a bus stop or a lake). This paper demonstrates how the urban structure can be modelled in LR calculations by using data from OpenStreetMap (OSM) and the location data itself. Based on these datasets, we present two approaches to extend the LR process by (1) including the urban structure in direct proximity of the location (Proximity Indicators and Areal Descriptors) and by (2) not only looking for individual locations but location clusters (Similarity Clusters). Thereby we acknowledge the complexity of a location, which can not be perceived as a detached entity. A location is part of a given urban structure and we need to include the parameters of this structure in our algorithms. A prototypical implementation compares locations from four major German cities: Berlin, Hamburg, Munich and Cologne and thereby highlights the applicability of the underlying data structures derived from OSM and the location data itself. We conclude by outlining the potential of the presented approaches in the context of LR as well as their relevancy for urban planning and neighboring disciplines.

Personal and subjective perceptions of urban space have been a focus of various research projects in the area of cartography, geography, and related fields such as urban planning. This paper illustrates how personal georeferenced activity data can be used in algorithmic modelling of certain aspects of mental maps and customised spatial visualisations. The technical implementation of the algorithm is accompanied by a preliminary study which evaluates the performance of the algorithm. As a linking element between personal perception, interpretation, and depiction of space and the field of cartography and geography, we include perspectives from artistic practice and cultural theory.

The growing amount of gathered, stored and available data is creating a need for useful mass-data visualizations in many domains. The mapping of large spatial data sets is not only of interest for experts anymore, but, with regard to the latest advances in web cartography, also moves into the domain of public cartographic applications. One interactive web-based cartographic interface design pattern that helps with visualizing and interacting with large, high density data sets is the marker cluster; a functionality already in use in many web-based products and solutions. In this article, the author will present their ongoing research on the problem of "too many markers." They will present an empirical evaluation and comparison of marker cluster techniques and similar approaches, including heatmaps and tiled heatmaps. They conclude with a first concept for overcoming some of the obstacles that they were able to identify in their study and thereby introduce a new direction for further research.

In recent years, access to cultural heritage has been closely connected to digitisation. We argue the case for recognising this digital shift as an opportunity to create interfaces to cultural heritage that are, first of all, more inviting to the public. Secondly, we want to encourage critical approaches towards the representation of cultural production and allow for alternative or even conflicting narratives and interpretations to surface. We present related work, use cases, and concepts for visualisations and interfaces that invite the reconsideration of modes of categorisation, presentation and clustering. Our intent is to develop ways to scrutinise modes of exclusion, carry out critical evaluations and pursue interventional strategies. We discuss the specific potential of visualisation, annotation and dynamic expansion of digital cultural collections. Building on critical approaches in human-computer interaction, visualisation and cultural theories, we explore how the interface could be a means of reflection, critique and inclusion. 86 Culture and Computer Science – Cross Media

This paper introduces an approach for visualizing large spatial time series data sets on mobile devices. The HeatTile system (Meier et al. 2014) is used and extended with a progressive loading approach, the stream approach. By combining those two approaches, this study aimed to overcome the performance and bandwidth limitations inherent to mobile devices. This chapter focuses on the technological advantages of the presented approach in a performance comparison with other common approaches. Furthermore, an animated time series visualization is introduced, as well as an interface designed specifically for the presented method in order to emphasize the advantages of the approach. To further highlight the possible applications of the method, two real-world use cases are presented.