Information Visualisation

We present ArtVis, an advanced user interface combining state-of-the-art visualisation techniques and tangible interaction to explore the Web Gallery of Art digital artwork collection consisting of almost 28000 European artworks. The graphical ArtVis interface contains three separate visualisation panels that allow users to temporally, semantically and geographically investigate the digital artwork collection. The goal of ArtVis is that users can gain new insights by visually analysing and exploring a large data set rather than to only provide detailed information about individual artworks. This explorative ArtVis interaction style is further fostered by a tangible user interface where physical artefacts can be used as simple handles to drive the faceted browsing of the rich digital information space.

Purpose-The purpose of this study is to investigate the effectiveness of diagrammatic visualisation techniques versus sentential learning contexts in an accounting subject using the theoretical lens of cognitive load theory (CLT). Design/methodology/approach-The present study used four groups of students; two groups completed a task using diagrammatic visualisation learning materials, with one of the groups undertaking their leaning activities collaboratively and another on an individual basis, whereas two comparison groups were given a sentential learning context without diagrams, with one group undertaking their leaning activities collaboratively and the other individually. In addition to performance grades, cognitive load selfreport scores were also elicited from participants. Findings-The findings of this study indicate support for diagrammatic visualisation techniques for students working collaboratively. Compared with sentential learners, the authors find significantly improved test performance for students who work collaboratively in a diagrammatic visualisation environment. Students in the visualisation environments obtained higher grades than those in the sentential group. In terms of mental effort, students in the visualisation conditions reported the lowest cognitive load. Practical implications-The authors conclude that diagrammatic visualisation learning techniques enhance student performance outcomes, particularly for those who work collaboratively. CLT assists in the understanding of the mental processes involved in learning. Instructional designers need to consider CLT when developing diagrammatic visualisation material to enable students to obtain the best possible learning outcomes. Originality/value-This study addresses a gap in the literature by examining the use of diagrammatic visualisation materials as an alternative to text when learning accounting. The study explores the effect of visualisation material on students' cognitive load by analysing their mental effort. The study contributes useful findings on visualisation as a conduit to enhancing the understanding of accounting using CLT principles.

Gennady Andrienko, Natalia Andrienko, Steven Drucker, Jean-Daniel Fekete, Danyel Fisher, Stratos Idreos, Tim Kraska, Guoliang Li, Kwan-Liu Ma, Jock D. Mackinlay, Antti Oulasvirta, Tobias Schreck, Heidrun Schmann, Michael Stonebraker, David Auber, Nikos Bikakis, Panos K. Chrysanthis, George Papastefanatos, Mohamed Sharaf. "Big Data Visualization and Analytics: Future Research Challenges and Emerging Applications" In 3rd Intl. Workshop on Big Data Visual Exploration & Analytics (BigVis 2020)

_ abstract
In the context of data visualization and analytics, this report out-lines some of the challenges and emerging applications that arise in the Big Data era. In particularly, fourteen distinguished scientists from academia and industry, and diverse related communities, i.e., Information Visualization, Human-Computer Interaction, Machine Learning, Data management & Mining, and Computer Graphics have been invited to express their opinions.

NetvizGL is a C++ OpenGL application for the visualisation of network graphs. It is a lightweight application designed to be minimal, extensible and scalable. NetvizGL can draw networks per a set of graph drawing algorithms. These algorithms are either be pre-packaged or a user may choose to write their own. With an an adaptation mechanism in place a user can write a relatively small amount of code to integrate it into the framework. The application provides a highly interactive visual interface which allows to pan, zoom and rotate graph layouts, as well as to interactively edit colours and labels. Layouts can be export as either PNG images or vector graphics files.

Existing research in the field of information visualisation has shown that interactive data exploration and storytelling can significantly improve the extraction and transfer of knowledge from raw data. Established visualisation techniques help viewers to strengthen their mental model and improve the understanding of the underlying data. However, these techniques are not yet manifested in slide decks created by existing presentation tools which offer little to no support beyond static charts for transferring knowledge. Based on a detailed analysis of interactive and narrative data visualisation solutions and the shortcomings of existing presentation tools, we derived a set of requirements for interactive information visualisation in presentation tools. The presented prototype of a presentation tool for interactive data visualisation addresses these requirements and has been implemented as a plug-in for the MindXpres presentation platform. Our approach for rich presentation-based data exploration and storytelling enables the presenter to predefine a series of interactive views as support for their oral narrative, but also allows them to freely explore the data during presentation time.