Modern information technology promises to improve service encounters through automated documentation or better decision traceability. At the same time, research suggests a negative impact of technology on human-to-human advisory services: including the possibility that computers might degrade the quality of interpersonal communication and reinforce unpleasant behaviors. Consequently, despite obvious improvements, information technology might have a negative impact on how the participants perceive the service. This might imply serious consequences for the service provider: dissatisfied clients, ineffective information exchange, and/or lack of transparency. This scenario slows down the diffusion of computers into advisory services in banks and insurance companies, and so designing systems for use in interpersonal services remains a challenge. This article provides evidence that LivePaper, a system designed alongside the material practices of a financial advisory encounter, helps to improve important service quality dimensions, making the services not only more pleasant for the participants, but also improving key marketing and business metrics of the service. In experimental advisory services, the sessions supported with LivePaper outperformed conventional services with regard to overall bank service quality and satisfaction, salesperson listening and interaction rating scores, as well as information transparency. This shows that a carefully designed system not only preserves the perceived quality of a service, but might improve it objectively, and has implications for the marketing and business value of the service.

Advisory services are ritualized encounters between an expert and an advisee. Empathetic, high-touch relationship between those two parties was identified as the key aspect of a successful advisory encounter. To facilitate the high-touch interaction, advisors established rituals which stress the unique, individual character of each client and each single encounter. Simultaneously, organizations like banks or insurances rolled out tools and technologies for use in advisory services to offer a uniform experience and consistent quality across branches and advisors. As a consequence, advisors were caught between the high-touch and high-tech aspects of an advisory service. This manuscript presents a system that accommodates for high-touch rituals and practices and combines them with high-tech collaboration. The proposed solution augments pen-and-paper practices with digital content and affords new material performances coherent with the existing rituals. The evaluation in realistic mortgage advisory services unveils the potential of mixed reality approaches for application in professional, institutional settings. The blow-by-blow analysis of the conversations reveals how an advisory service can become equally high-tech and high-touch thanks to a careful ritual-oriented system design. As a consequence, this paper presents a solution to the tension between the high-touch and high-tech tendencies in advisory services.

This paper presents 4D User Experience design principles (4D-UX), as well as a software implementation and applications of how to communicate spatial and temporal data. The foundation is built on tightly coupling multiple dimensions into one application, adding a sequential story line and finally decluttering the front-end to enhance the emotional and cognitive functions of audiences. The framework suggests a combination of a sequential story-telling approach with 2D, 3D, 4D elements such as interactive sliders added to the flow of argumentation. With those design principles in place, the authors then present a software platform called "Singapore Views" based on the "Unity" game engine. The communication challenge of research groups that had to convey the insights on their studies about the "Urban Heat Island Effect" and "Dense and Green Building Typologies" in Singapore to a diverse group of stakeholders were taken as examples. The paper presents a multi-disciplinary approach with authors from computer science, architecture, design, communication, business administration and urban development. It contributes to the current discussion of how to visualize knowledge and plan future cities.

Urban forms at human-scale, i.e., urban environments that individuals can sense (e.g., sight, smell, and touch) in their daily lives, can provide unprecedented insights on a variety of applications, such as urban planning and environment auditing. The analysis of urban forms can help planners develop high-quality urban spaces through evidence-based design. However, such analysis is complex because of the involvement of spatial, multi-scale (i.e., city, region, and street), and multivariate (e.g., greenery and sky ratios) natures of urban forms. In addition, current methods either lack quantitative measurements or are limited to a small area. The primary contribution of this work is the design of StreetVizor, an interactive visual analytics system that helps planners leverage their domain knowledge in exploring human-scale urban forms based on street view images. Our system presents two-stage visual exploration: 1) an AOI Explorer for the visual comparison of spatial distributions and quantitative measurements in two areas-of-interest (AOIs) at city- and region-scales; 2) and a Street Explorer with a novel parallel coordinate plot for the exploration of the fine-grained details of the urban forms at the street-scale. We integrate visualization techniques with machine learning models to facilitate the detection of street view patterns. We illustrate the applicability of our approach with case studies on the real-world datasets of four cities, i.e., Hong Kong, Singapore, Greater London and New York City. Interviews with domain experts demonstrate the effectiveness of our system in facilitating various analytical tasks.

This paper presents a framework which allows urban planners to navigate and interact with large datasets fused with social feeds in real-time, enhanced by a virtual reality (VR) capability, which further promotes the knowledge discovery process and allows to interact with urban data in natural yet immersive way. A challenge in urban planning is making decisions based on datasets which are many times ambiguous, together with effective use of newly available yet unstructured sources of information like social media. Providing expert users with novel ways of representing knowledge can be beneficial for decision making. Game engines have evolved into capable testbeds for novel visualization and interaction techniques. We therefore explore the possibility of using a modern game engine as a platform for knowledge representation in urban planning and how it can be used to model ambiguity. We also investigate how urban planners can benefit from immersion when it comes to data exploration and knowledge discovery. We apply the concept of using primitives to publicly available transportation datasets and social feeds of New York city, we discuss a gesture-based VR extension of our framework and lastly, we conclude the paper with feedback from expert users in urban planning and with an outlook of future challenges.

This paper presents a method and case study to visualize the urban stock of materials and its availability for use in building future cities. Re-using material from existing buildings for new buildings can be seen as a source for construction materials in times of depleting natural resources. The authors explain the concept of "urban mining" and the challenges, such as "How much resources are available in a city? Today? In the near future?" We explore what data are needed to answer the questions, and then discuss how to best visualize the data in an effective and intuitive way. We apply the concept to an exemplary real-world district in Singapore that is in transformation. Then, we discuss features of a visual tool prototype and explain the thinking behind the design, e.g., how the spatial and temporal dimensions can be presented. Lastly, we conclude the paper with an outlook of future challenges. The paper presents a multi-disciplinary approach with researchers from computer science, architecture, graphic design and material science, and contributes to the discussion of how to visualize knowledge and plan sustainable future cities.

In transportation studies, one fundamental problem is to analyze the departures and arrivals at locations in order to predict the travel demands for urban planning and traffic management. These movements can relate to many factors, e.g., activity distributions and household demographics. This paper presents how we use visualization to explore the relationship between people movements and activity distributions that are characterized by the points of interest (POIs). To effectively model and visualize such relationship, we introduce POI-mobility signature, a compact visual representation with two main components. 1) A mobility component to present major people movements information across temporal dimension. 2) A POI component to present the activity context over an area of interest in spatial domain. To derive the signature, we study assorted analytical tasks after discussing with transportation researchers, consider essential design principles, and apply the representation to study a real-world dataset, which is the massive public transportation data in Singapore with over 30 million trajectories and crowd-sourcing POIs retrieved from Foursquare. Finally, we conduct three case studies and interview three transportation experts to verify the efficacy of our method.

Human’s daily movements exhibit high regularity in a space–time context that typically forms circadian rhythms. Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners, transportation analysts, to business strategists. In this paper, we present an interactive visual analytics design for understanding and utilizing data collected from tracking human’s movements. The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time. Case studies using real-world human movement data, including massive urban public transportation data in Singapore and the MIT reality mining dataset, and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system.