Daniel Filonik

Measuring Aesthetics for Information Visualization

Aesthetics is an unsolved problem of information visualization, because there is no satisfactory understanding of what constitutes aesthetic effect. This survey paper gives an overview of approaches to model aesthetics, starting with Birkhoff’s aesthetic measure and continuing to recent ones based on mathematical and information theoretical concepts. Common concepts in the different models are highlighted, such as the effects of order and complexity. Further, practical techniques for generating aesthetic visualizations are shown together with examples of recent work in this field. Finally, the paper discusses some of the key issues regarding aesthetics and the human factor in the visualization process. Empirical studies have shown a correlation between perceived aesthetics and usability, meaning that a better understanding of aesthetics could improve the usability of visualizations.

A Mobile Application to Support Phatic Communication in the Hybrid Space

This paper presents a prototype implementation of the PengYo application that offers a cross-platform interaction method between an online social community and mobile users based on the “beeping” phenomenon. PengYo provides a novel interface that explicitly supports the practice of beeping, a nearly-globally applied implicit communication method of calling somebody and hanging up before the call is answered. In contrast to the traditional beeping-method, PengYo provides a custom tailored user interface and user interaction style for beeping, following the real-life cognitive model of “tapping someone on the shoulder”. PengYo builds a platform for further investigation of the beeping phenomenon and its usage patterns, that very little research has been done on so far. The results of further research studies that base on PengYo might deliver crucial information for redesigning and enhancing existing channels following the user-led communication phenomenon of beeping.

Street computing: towards an integrated open data application programming interface (API) for cities

This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing Workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer-Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges, and foundations of this research trajectory. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarizes related work in this field of interest. We conclude by introducing the papers that have been contributed to this special issue.

DataChopin - Designing Interactions for Visualisation Composition in a Co-Located, Cooperative Environment

This article presents our interaction design for DataChopin, based on an extensive survey and classification of visualisation for exploratory data analysis. Its distinctive characteristics are the use of a large-scale display wall as a shared desktop, as well as flexible composition mechanisms for incremental and piece-wise construction of visualisations. We chose composability as a guiding principle in our design, since it is essential to open-ended exploration, as well as collaborative analysis. For one, it enables truly exploratory inquiry by letting users freely examine different combinations of data, rather than offering a predetermined set of choices. Perhaps more importantly, it provides a foundation for data analysis through collaborative interaction with visualisations. If data and visualisations are composable, they can split into independent parts and recombined during the analytical process, allowing analysts to seamlessly transition between closely- and loosely-coupled work.

Collaborative Data Exploration Interfaces - From Participatory Sensing to Participatory Sensemaking

As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

Participatory Data Analytics: Collaborative Interfaces for Data Composition and Visualisation

This research proposes the development of interfaces to support collaborative, community-driven inquiry into data, which we refer to as Participatory Data Analytics. Since the investigation is led by local communities, it is not possible to anticipate which data will be relevant and what questions are going to be asked. Therefore, users have to be able to construct and tailor visualisations to their own needs. The poster presents early work towards defining a suitable compositional model, which will allow users to mix, match, and manipulate data sets to obtain visual representations with little-to-no programming knowledge. Following a user-centred design process, we are subsequently planning to identify appropriate interaction techniques and metaphors for generating such visual specifications on wall-sized, multi-touch displays.

Glance: generalized geometric primitives and transformations for information visualization in AR/VR environments

This paper outlines Glance, a unifying framework for exploring multidimensional, multivariate data in the context of AR/VR environments, along with specific implementation techniques that utilize programmable GPUs. The presented techniques extend the graphics pipeline through programmable shaders in order to support more general geometries and operations. Our point of departure from existing structural theories of graphics is a general spatial substrate, where data is encoded using higher-dimensional geometric primitives. From there, we define a series of processing stages, utilizing shaders to enable flexible and dynamic coordinate transformations. Furthermore, we describe how advanced visualization techniques, such as faceting and multiple views, can be integrated elegantly into our model. Bridging between Computer Graphics and Information Visualization theories, the elements of our framework are composable and expressive, allowing a diverse set of visualizations to be specified in a universal manner (see figure 1).

Grids and networks: two exploratory approaches for visualising bibliometric data on very large displays

Current personal single-user devices, such as smartphones, tablets, or laptops, struggle to provide the contextual awareness and coordination capabilities required for the effective collaborative analysis of large datasets. Instead, large interactive displays offer unique opportunities for co-located collaboration in meeting room environments. However, supporting collaborative interaction across multiple large displays presents distinctive challenges for interaction designers. This paper explores and compares novel interaction techniques and visualisations for large displays, with a focus on two distinct approaches for collaborative browsing and filtering of multivariate datasets: (i) shared zoomable grid view, and (ii) multiple individual network views. In order to evaluate the effectiveness of our proposed interfaces for multi-user exploratory analysis, we applied the designs to a specific use case, namely the problem of displaying research metadata from bibliographic databases to extract and collate narratives and overarching themes for research grant proposals. Following an agile design methodology, we created two prototypes incorporating our designs. We weigh the benefits and limitations of each approach by comparing them along two key dimensions: (i) methods of interaction, and (ii) visual representation. Subsequently, we compare the two design approaches and discuss the circumstances and situations that would be beneficial for use. This research and its implications are intended to inform future research exploring the design of collaborative interfaces for large-scale interaction environments.