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This article reviews two decades of research in topics in Information Visualisation emerging from the Data Visualisation and Immersive Analytics Lab at Monash University Australia (Monash IA Lab). The lab has been influential with contributions in algorithms, interaction techniques and experimental results in Network Visualisation, Interactive Optimisation and Geographic and Cartographic visualisation. It has also been a leader in the emerging topic of Immersive Analytics, which explores natural interactions and immersive display technologies in support of data analytics. We reflect on advances in these areas but also sketch our vision for future research and developments in data visualisation more broadly.

We present a generic model for providing blind and severely vision-impaired readers with access to online information graphics. The model supports fully and semi-automatic transcription and allows the reader a choice of presentation mediums. We evaluate the model through a case study: online house floor plans. To do so, we conducted a formative user study with severely vision impaired users to determine what information they would like from an online floor plan and how to present the floor plan as a text-only description, tactile graphic, and on a touchscreen with audio feedback. We then built an automatic transcription tool using specialized graphics recognition algorithms. Finally, we measured the quality of system recognition as well as conducted a second user study to evaluate the usefulness of the accessible graphics produced by the tool for each of the three formats. The results generally support the design of the generic model and the usefulness of the tool we have produced. However, they also reveal the inability of current graphics recognition algorithms to handle unforeseen graphical conventions. This highlights the need for automatic transcription systems to return a level of confidence in the recognized components and to present this to the end-user so they can have an appropriate level of trust.

We present a new network diagram authoring tool, Dunnart, that provides continuous network layout . It continuously adjusts the layout in response to user interaction, while still maintaining the layout style and, where reasonable, the current layout topology. The diagram author uses placement constraints, such as alignment and distribution, to tailor the layout style and can guide the layout by repositioning diagram components or rerouting connectors. The key to the flexibility of our approach is the use of topology-preserving constrained graph layout.

Constrained graph layout is a recent generalisation of force-directed graph layout which allows constraints on node placement. We give a constrained graph layout algorithm that takes an initial feasible layout and improves it while preserving the topology of the initial layout. The algorithm supports poly-line connectors and clusters. During layout the connectors and cluster boundaries act like impervious rubber-bands which try to shrink in length. The intended application for our algorithm is dynamic graph layout, but it can also be used to improve layouts generated by other graph layout techniques.

Immersive analytics turns the very space surrounding the user into a canvas for data analysis, supporting human cognitive abilities in myriad ways. We present the results of a design study, contextual inquiry, and longitudinal evaluation involving professional economists using a Virtual Reality (VR) system for multidimensional visualization to explore actual economic data. Results from our preregistered evaluation highlight the varied use of space depending on context (exploration vs. presentation), the organization of space to support work, and the impact of immersion on navigation and orientation in the 3D analysis space. Refereed/Peer-reviewed

We explore network visualisation on a two-dimensional torus topology that continuously wraps when the viewport is panned. That is, links may be “wrapped” across the boundary, allowing additional spreading of node positions to reduce visual clutter. Recent work has investigated such pannable wrapped visualisations, finding them not worse than unwrapped drawings for small networks for path-following tasks. However, they did not evaluate larger networks nor did they consider whether torus-based layout might also better display high-level network structure like clusters. We offer two algorithms for improving toroidal layout that is completely autonomous and automatic panning of the viewport to minimiswe wrapping links. The resulting layouts afford fewer crossings, less stress, and greater cluster separation. In a study of 32 participants comparing performance in cluster understanding tasks, we find that toroidal visualisation offers significant benefits over standard unwrapped visualisation in terms of improvement in error by 62.7% and time by 32.3%.

This paper presents a systematic literature review of 292 publications from 97 unique venues on touch-based graphics for people who are blind or have low vision, from 2010 to mid-2020. It is the first review of its kind on touch-based accessible graphics. It is timely because it allows us to assess the impact of new technologies such as commodity 3D printing and low-cost electronics on the production and presentation of accessible graphics. As expected our review shows an increase in publications from 2014 that we can attribute to these developments. It also reveals the need to: broaden application areas, especially to the workplace; broaden end-user participation throughout the full design process; and conduct more in situ evaluation. This work is linked to an online living resource to be shared with the wider community., Comment: To appear in ACM CHI Conference on Human Factors in Computing Systems (CHI '21), May 8-13, 2021, Yokohama, Japan

We argue that visualization research has overwhelmingly focused on users from the economically developed world. However, billions of people around the world are rapidly emerging as new users of information technology. Most of the next billion users of visualization technologies will come from parts of the world that are extremely populous but historically ignored by the visualization research community. Their needs may be different to the types of users that researchers have targeted in the past, but, at the same time, they may have even more to gain in terms of access to data potentially affecting their quality of life. We propose a call to action for the visualization community to identify opportunities and use cases where users can benefit from visualization; develop universal design principles; extend evaluations by including the general population; and engage with a wider global population.

In this paper, we report on a study of visual representations for cyclical data and the effect of interactively wrapping a bar chart 'around its boundaries'. Compared to linear bar chart, polar (or radial) visualisations have the advantage that cyclical data can be presented continuously without mentally bridging the visual 'cut' across the left-and-right boundaries. To investigate this hypothesis and to assess the effect the cut has on analysis performance, this paper presents results from a crowdsourced, controlled experiment with 72 participants comparing new continuous panning technique to linear bar charts (interactive wrapping). Our results show that bar charts with interactive wrapping lead to less errors compared to standard bar charts or polar charts. Inspired by these results, we generalise the concept of interactive wrapping to other visualisations for cyclical or relational data. We describe a design space based on the concept of one-dimensional wrapping and two-dimensional wrapping, linked to two common 3D topologies; cylinder and torus that can be used to metaphorically explain one- and two-dimensional wrapping. This design space suggests that interactive wrapping is widely applicable to many different data types.

Despite centuries of using mathematical notation, surprisingly little is known about how mathematicians perceive equations. The present experiment provides an initial step in understanding what sort of internal representation is used by experienced mathematicians. In particular, we examined if mathematical syntax plays a role in how mathematicians encode algebraic equations, or if just a simple memory strategy is used. Participants in the experiment performed a memory recognition task that required them to identify both well-formed (syntactically correct) and non-well-formed sub-expressions of equations. As hypothesised, performance was significantly better for well-formed sub-expressions, a result which suggests that mathematicians do indeed use an internal representation based on mathematical syntax to encode equations.

Efficient optimisation algorithms have become important tools for finding high-quality solutions to hard, real-world problems such as production scheduling, timetabling, or vehicle routing. These algorithms are typically "black boxes" that work on mathematical models of the problem to solve. However, many problems are difficult to fully specify, and require a "human in the loop" who collaborates with the algorithm by refining the model and guiding the search to produce acceptable solutions. Recently, the Problem-Solving Loop was introduced as a high-level model of such interactive optimisation. Here, we present and evaluate nine recommendations for the design of interactive visualisation tools supporting the Problem-Solving Loop. They range from the choice of visual representation for solutions and constraints to the use of a solution gallery to support exploration of alternate solutions. We first examined the applicability of the recommendations by investigating how well they had been supported in previous interactive optimisation tools. We then evaluated the recommendations in the context of the vehicle routing problem with time windows (VRPTW). To do so we built a sophisticated interactive visual system for solving VRPTW that was informed by the recommendations. Ten participants then used this system to solve a variety of routing problems. We report on participant comments and interaction patterns with the tool. These showed the tool was regarded as highly usable and the results generally supported the usefulness of the underlying recommendations., Comment: 9+2 pages, 6 figures, VAST 2020

A critical component of the worldwide response to the novel coronavirus COVID-19 pandemic has been providing the general public with information about the virus and the health measures designed to slow its spread. Much of this information has been presented as visual graphics. Have people who are blind or have low vision (BLV) been able to gain access to this information through nonvisual media and, if so, how? We investigate this issue using Australia as a case study.

While developments in 3D printing have opened up opportunities for improved access to graphical information for people who are blind or have low vision (BLV), they can provide only limited detailed and contextual information. Interactive 3D printed models (I3Ms) that provide audio labels and/or a conversational agent interface potentially overcome this limitation. We conducted a Wizard-of-Oz exploratory study to uncover the multi-modal interaction techniques that BLV people would like to use when exploring I3Ms, and investigated their attitudes towards different levels of model agency. These findings informed the creation of an I3M prototype of the solar system. A second user study with this model revealed a hierarchy of interaction, with BLV users preferring tactile exploration, followed by touch gestures to trigger audio labels, and then natural language to fill in knowledge gaps and confirm understanding., Paper presented at ACM CHI 2020: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, ACM, New York, April 2020; Replacement: typos corrected

We introduce Tilt Map, a novel interaction technique for intuitively transitioning between 2D and 3D map visualisations in immersive environments. Our focus is visualising data associated with areal features on maps, for example, population density by state. Tilt Map transitions from 2D choropleth maps to 3D prism maps to 2D bar charts to overcome the limitations of each. Our paper includes two user studies. The first study compares subjects' task performance interpreting population density data using 2D choropleth maps and 3D prism maps in virtual reality (VR). We observed greater task accuracy with prism maps, but faster response times with choropleth maps. The complementarity of these views inspired our hybrid Tilt Map design. Our second study compares Tilt Map to: a side-by-side arrangement of the various views; and interactive toggling between views. The results indicate benefits for Tilt Map in user preference; and accuracy (versus side-by-side) and time (versus toggle)., Comment: IEEE Transactions on Visualization and Computer Graphics (TVCG), to appear

We investigate visualisations of networks on a 2-dimensional torus topology, like an opened-up and flattened doughnut. That is, the network is drawn on a rectangular area while “wrapping” specific links around the border. Previous work on torus drawings of networks has been mostly theoretical, limited to certain classes of networks, and not evaluated by human readability studies. We offer a simple interactive layout approach applicable to general graphs. We use this to find layouts affording better aesthetics in terms of conventional measures like more equal edge length and fewer crossings. In two controlled user studies we find that torus layout with either additional context or interactive panning provided significant performance improvement (in terms of error and time) over torus layout without either of these improvements, to the point that it is comparable to standard non-torus layout.

The visualization research community can and should reach broader audiences beyond data-savvy groups of people, because these audiences could also greatly benefit from visual access to data. In this article, we discuss four research topics—personal data visualization, data visualization on mobile devices, inclusive data visualization, and multimodal interaction for data visualization—that, individually and collaboratively, would help us reach broader audiences with data visualization, making data more accessible.

The Web and digital media require documents whose appearance and content adapt to the viewing context and to user interaction. While most previous research has focussed on adaptation for textual and multimedia content, this is also true for diagrammatic content. We (a) identify the reasons for adaptation and the different kinds of adaptation that make sense for diagrams; (b) present an aspect-oriented model for diagram adaptation that separates adaptation into different orthogonal components; (c) describe a diagram authoring tool based on this model; and (d) present the results of a user evaluation of the tool. Our model uses layout “configurations” to model significantly different layout alternatives and geometric constraints to perform minor layout adjustment. The author can also specify alternate representations for an object, alternate styles and alternate textual content. The resulting space of different versions of the diagram is the cross product of these different alternatives. At display time the version is selected from this cross product and constructed automatically, taking into account the author specified preference order on the alternatives, current viewing environment, and user interaction.

The emerging field of Immersive Analytics investigates how novel display and interaction technologies can enable people to better explore and analyse data and complex information. Collaboration is a crucial aspect of Immersive Analytics. In this paper we present ContextuWall, a system for interactive local and remote collaboration using touch and mobile devices as well as displays of various sizes. The system enables groups of users located on different sites to share content to a jointly used virtual desktop which is accessible over a secured network. This virtual desktop can be shown on different large displays simultaneously, taking advantage of their high resolution. To enable users to intuitively share, arrange as well as annotate image content, a purpose-built client software has been developed and can easily be adapted with plug-ins for existing data analytics software. We show exemplary use cases and describe the system architecture and its implementation.

Immersive analytics is a recent research initiative growing out of the fields of data visualization, human–computer interaction, AR/VR, and computer graphics among others. This special issue presents recent work in the field including the introduction of novel immersive visualization concepts and techniques for different types of data and a critical reflection on the history and development of the field.

Visualisations are commonly used to understand social, biological and other kinds of networks. Currently, we do not know how to effectively present network data to people who are blind or have low-vision (BLV). We ran a controlled study with 8 BLV participants comparing four tactile representations: organic node-link diagram, grid node-link diagram, adjacency matrix and braille list. We found that the node-link representations were preferred and more effective for path following and cluster identification while the matrix and list were better for adjacency tasks. This is broadly in line with findings for the corresponding visual representations., Comment: To appear in the ACM CHI Conference on Human Factors in Computing Systems (CHI 2020)

Node-link diagrams are widely used to visualise networks. However, even the best network layout algorithms ultimately result in 'hairball' visualisations when the graph reaches a certain degree of complexity, requiring simplification through aggregation or interaction (such as filtering) to remain usable. Until now, there has been little data to indicate at what level of complexity node-link diagrams become ineffective or how visual complexity affects cognitive load. To this end, we conducted a controlled study to understand workload limits for a task that requires a detailed understanding of the network topology---finding the shortest path between two nodes. We tested performance on graphs with 25 to 175 nodes with varying density. We collected performance measures (accuracy and response time), subjective feedback, and physiological measures (EEG, pupil dilation, and heart rate variability). To the best of our knowledge, this is the first network visualisation study to include physiological measures. Our results show that people have significant difficulty finding the shortest path in high-density node-link diagrams with more than 50 nodes and even low-density graphs with more than 100 nodes. From our collected EEG data we observe functional differences in brain activity between hard and easy tasks. We found that cognitive load increased up to a certain level of difficulty after which it decreased, likely because participants had given up. We also explored the effects of global network layout features such as size or number of crossings, and features of the shortest path such as length or straightness on task difficulty. We found that global features generally had a greater impact than those of the shortest path., Comment: To be presented at IEEE Conference on Information Visualization (InfoVis 2020)

Access to information is a fundamental problem for people with vision impairment (PVI). Textual information are considerably more accessible with the use of screen readers that work on desktop and mobile devices. However, access to graphical information is still a challenging problem. There are different technologies to present graphics to PVI, but almost all of them suffer from practicality and portability. This paper describes the GraVVITAS (Graphics Viewer using Vibration Interactive Touch and Speech) framework which aims to be a complementary system for other assistive technologies; a solution that can be carried in one's pocket.

Providing people who are blind or have low vision with accessible versions of artworks is important not just for equity, but also for inclusion, greater engagement with the community at large, and raising awareness about these issues. In 2018, a value-sensitive design methodology was used with the Bendigo Art Gallery and key stakeholders to develop a model that provides three different ways of accessing the gallery, depending upon visual acuity and mobility: virtual tours, self-guided tours and guided tours. As a pilot implementation of the model, we developed different tactile representations of key artworks using tactile graphics, laser-cut layered graphics, 3D printed models, soundscapes, role plays, and a website featuring information and representations requested by workshop participants. To highlight the work, this paper will present two of the key works in more detail to highlight different representations that should be considered when presenting accessible artworks.

The difficulty and consequent fear of travel is one of the most disabling consequences of blindness and severe vision impairment, affecting confidence and quality of life. Traditional tactile graphics are vital in the Orientation and Mobility training process, however 3D printing may have the capacity to enable production of more meaningful and inclusive maps. This study explored the use of 3D printed maps on site at a public event to examine their suitability and to identify guidelines for the design of future 3D maps. An iterative design process was used in the production of the 3D maps, with feedback from visitors who are blind or have low vision informing the recommendations for their design and use. For example, it was found that many representational 3D icons could be recognised by touch without the need for a key and that such a map helped form mental models of the event space. Complex maps, however, require time to explore and should be made available before an event or at the entrance in a comfortable position. The maps were found to support the orientation and mobility process, and importantly to also promote a positive message about inclusion and accessibility.

Showing flows of people and resources between multiple geographic locations is a challenging visualisation problem. We conducted two quantitative user studies to evaluate different visual representations for such dense many-to-many flows. In our first study we compared a bundled node-link flow map representation and OD Maps [37] with a new visualisation we call MapTrix. Like OD Maps, MapTrix overcomes the clutter associated with a traditional flow map while providing geographic embedding that is missing in standard OD matrix representations. We found that OD Maps and MapTrix had similar performance while bundled node-link flow map representations did not scale at all well. Our second study compared participant performance with OD Maps and MapTrix on larger data sets. Again performance was remarkably similar., Presented at IEEE Conference on Information Visualization (InfoVis 2016). Awarded Best Paper Honorable Mention. Part of PhD thesis arXiv:1908.00662

We have compared three common visualisations for hierarchical quantitative data, treemaps, icicle plots and sunburst charts as well as a semicircular variant of sunburst charts we call the sundown chart. In a pilot study, we found that the sunburst chart was least preferred. In a controlled study with 12 participants, we compared treemaps, icicle plots and sundown charts. Treemap was the least preferred and had a slower performance on a basic navigation task and slower performance and accuracy in hierarchy understanding tasks. The icicle plot and sundown chart had similar performance with slight user preference for the icicle plot., Presented at IEEE VIS 2019 in Vancouver, Canada and included in the VIS 2019 conference proceedings. Improved the image quality in the paper

International audience; We introduce IATK, the Immersive Analytics Toolkit, a software package for Unity that allows interactive authoring and exploration of data visualisation in immersive environments. The design of IATK was informed by interdisciplinary expert-collaborations as well as visual analytics applications and iterative refinement over several years. IATK allows for easy assembly of visualisations through a grammar of graphics that a user can configure in a GUI— in addition to a dedicated visualisation API that supports the creation of novel immersive visualisation designs and interactions. IATK is designed with scalability in mind, allowing visualisation and fluid responsive interactions in the order of several million points at a usable frame rate. This paper outlines our design requirements, IATK’s framework design and technical features, its user interface, as well as application examples.

This paper presents the use of a projector-based spatial augmented reality system in an industrial quality assurance setting to highlight spot-weld locations on vehicle panels for manual welding operators. The aim of this work is to improve the precision and accuracy of manual spot-weld placements with the aid of visual cues as a proactive step by the automotive manufacturer to enhance product quality. The prototype system was deployed at General Motors (GM) Holden plant in Elizabeth, Australia on the production line building Holden Cruze vehicles. Production trials were conducted and techniques developed to analyse and validate the precision and accuracy of spot-welds both with and without the visual cues. A reduction of 52 % of the standard deviation of manual spot-weld placement was observed when using augmented reality visual cues. The average standard deviation with-AR assistance (19 panels and 114 spot-welds) was calculated at 1.94 mm compared to without-AR (45 panels and 270 spot-welds) at 4.08 mm. All welds were within the required specification and panels evaluated in this study were used as the final product made available to consumers. The visual cues enabled operators to spot-weld at a higher degree of precision and accuracy. Refereed/Peer-reviewed

With the massive growth of online learning, there has been a decrease in students' face-to-face interactions, leading to rising feelings of isolation. This in turn contributes to several issues such as motivation loss, increased course attrition rates and poor learning experiences. Strong Online Learning Communities (OLCs) have been suggested as a means to help improve the situation, however the formation of OLCs is strongly influenced by learners' individual characteristics and their preferences regarding how and with whom they would want to form study groups. Taking students as its focus, this research attempts to develop a learning partner recommender system (LPRS) to facilitate finding compatible study peers in order to promote informal learning communities among students. From a synthesis of related literature and using data from a study of the student' preferences, a collection of learners' individual characteristics has been identified as a set of matching criteria in our LPRS model. A proof of concept based on the conceptual model has been developed and evaluated with a small group of target users. Results of the investigation showed positive feedback from participants and good prospects of the recommender system.

Immersive virtual- and augmented-reality headsets can overlay a flat image against any surface or hang virtual objects in the space around the user. The technology is rapidly improving and may, in the long term, replace traditional flat panel displays in many situations. When displays are no longer intrinsically flat, how should we use the space around the user for abstract data visualisation? In this paper, we ask this question with respect to origin-destination flow data in a global geographic context. We report on the findings of three studies exploring different spatial encodings for flow maps. The first experiment focuses on different 2D and 3D encodings for flows on flat maps. We find that participants are significantly more accurate with raised flow paths whose height is proportional to flow distance but fastest with traditional straight line 2D flows. In our second and third experiment, we compared flat maps, 3D globes and a novel interactive design we call MapsLink, involving a pair of linked flat maps. We find that participants took significantly more time with MapsLink than other flow maps while the 3D globe with raised flows was the fastest, most accurate, and most preferred method. Our work suggests that careful use of the third spatial dimension can resolve visual clutter in complex flow maps., Comment: Presented at IEEE Conference on Information Visualization (InfoVis 2018). Part of PhD thesis arXiv:1908.00662

We propose Graph Thumbnails , small icon-like visualisations of the high-level structure of network data. Graph Thumbnails are designed to be legible in small multiples to support rapid browsing within large graph corpora. Compared to existing graph-visualisation techniques our representation has several advantages: (1) the visualisation can be computed in linear time; (2) it is canonical in the sense that isomorphic graphs will always have identical thumbnails; and (3) it provides precise information about the graph structure. We report the results of two user studies. The first study compares Graph Thumbnails to node-link and matrix views for identifying similar graphs. The second study investigates the comprehensibility of the different representations. We demonstrate the usefulness of this representation for summarising the evolution of protein-protein interaction networks across a range of species.

Tactile maps are widely used in Orientation and Mobility (O&M) training for people with blindness and severe vision impairment. Commodity 3D printers now offer an alternative way to present accessible graphics, however it is unclear if 3D models offer advantages over tactile equivalents for 2D graphics such as maps. In a controlled study with 16 touch readers, we found that 3D models were preferred, enabled the use of more easily understood icons, facilitated better short term recall and allowed relative height of map elements to be more easily understood. Analysis of hand movements revealed the use of novel strategies for systematic scanning of the 3D model and gaining an overview of the map. Finally, we explored how 3D printed maps can be augmented with interactive audio labels, replacing less practical braille labels. Our findings suggest that 3D printed maps do indeed offer advantages for O&M training.

Prior research into network layout has focused on fast heuristic techniques for layout of large networks, or complex multi-stage pipelines for higher quality layout of small graphs. Improvements to these pipeline techniques, especially for orthogonal-style layout, are difficult and practical results have been slight in recent years. Yet, as discussed in this paper, there remain significant issues in the quality of the layouts produced by these techniques, even for quite small networks. This is especially true when layout with additional grouping constraints is required. The first contribution of this paper is to investigate an ultra-compact, grid-like network layout aesthetic that is motivated by the grid arrangements that are used almost universally by designers in typographical layout. Since the time when these heuristic and pipeline-based graph-layout methods were conceived, generic technologies (MIP, CP and SAT) for solving combinatorial and mixed-integer optimization problems have improved massively. The second contribution of this paper is to reassess whether these techniques can be used for high-quality layout of small graphs. While they are fast enough for graphs of up to 50 nodes we found these methods do not scale up. Our third contribution is a large-neighborhood search meta-heuristic approach that is scalable to larger networks.

Automatic layout of tables is useful in word processing applications and is required in online applications because of the need to tailor the layout to viewport width, choice of font, and dynamic content. However, if the table contains text, minimizing the height of the table for a given maximum width is a difficult combinatorial optimization problem because of the need to find the right choice of height/width configuration for each cell in the table. We investigate the modelling decisions involved in formulating this problem for use with standard combinatorial optimization techniques that are guaranteed to find the minimal-height table. To the best of our knowledge, we are the first to do so. We provide a detailed empirical evaluation of the resulting models using mixed integer programming and constraint programming with lazy clause generation.

International audience; Immersive Analytics is a new research initiative that aims to remove barriers between people, their data and the tools they use for analysis and decision making. Here we clarify the aims of immersive analytics research, its opportunities and historical context, as well as providing a broad research agenda for the field. In addition, we review how the term immersion has been used to refer to both technological and psychological immersion, both of which are central to immersive analytics research.

Modern virtual reality display technologies engender spatial immersion by using a variety of depth cues such as perspective and head-tracked binocular presentation to create visually realistic 3D worlds. While 3D visualisations are common in scientific visualisation, they are much less common in information visualisation. In this chapter we explore whether immersive analytic applications should continue to use traditional 2D information visualisations or whether there are situations when 3D may offer benefits. We identify a number of potential applications of 3D depth cues for abstract data visualisation: using depth to show an additional data dimension, such as in 2.5D network layouts, views on non-flat surfaces and egocentric views in which the data is placed around the viewer, and visualising abstract data with a spatial embedding. Another important potential benefit is the ability to arrange multiple views in the 3D space around the user and to attach abstract visualisations to objects in the real world.

We present an initial design framework for immersive analytics based on Brehmer and Munzner’s “What-Why-How” data visualisation framework. We extend their framework to take into account Who are the people or teams of people who are going to use the system, and Where is the system to be used and what are the available devices and technology. In addition, the How component is extended to cater for collaboration, multisensory presentation, interaction with an underlying computational model, degree of fidelity and organisation of the workspace around the user. By doing so we provide a framework for understanding immersive analytics research and applications as well as clarifying how immersive analytics differs from traditional data visualisation and visual analytics.

This paper presents a context-aware design pattern for situated analytics called Blended Model View Controller. Our approach is an event-driven design, allowing a seamless transition between the physical space and information space during use. The Blended Model View Controller allows common user interface controls to work in tandem with printed information on a physical object by adapting the operation and presentation based on a semantic matrix. Also presented is an authoring tool that has been developed to assign the parameters of the semantic matrix. We demonstrate the use of the design pattern with a set of augmented reality interactions including; pinch zoom, menus, and details-on-demand. We analyse each control to highlight how the physical and virtual information spaces work in tandem to provide a rich interaction environment in augmented reality. Refereed/Peer-reviewed

While visual cues are traditionally used for visual analytics, multimodal interaction technologies offer many new possibilities. This chapter explores the opportunities and challenges for developers and users to utilize and represent data through non-visual sensory channels to help them understand and interact with data. Users are able to experience data in new ways: variables from complex datasets can be conveyed through different senses; presentations are more accessible to people with vision impairment and can be personalized to specific user needs; interactions can involve multiple senses to provide natural and transparent methods. All these techniques enable users to obtain a better understanding of the underlying information. While the emphasis of this chapter is towards non-visual immersive analytics, we include a discussion on how visual presentations are integrated with different modalities, and the opportunities of mixing several sensory signals, including the visual domain.

We are developing an application to automatically generate an accessible graphic from a floor plan image. Floor plans generally contain large regions with functionally different sub-areas. A problem faced by visually impaired users in exploring such accessible floor plans is understanding the boundaries of these sub-areas. We present an effective method to partition such open plan areas. Initially, we conducted a formative user study to understand how people partition open plan areas. Based on the findings of the study, we identified a general set of guidelines for partitioning open plans. These guidelines were used to generate a set of candidate lines for sub-areas. An obstacle avoiding shortest-path Voronoi diagram was used to determine boundaries for each sub-area. Candidate lines such as wall extensions were automatically generated to replace the identified boundaries. We selected the best replacement for each boundary by scoring candidate lines using a set of criteria such as line length. Finally the proposed method was tested on a standard floor plan corpus using three novel measures.

The fields of operations research and computer science have long sought to find automatic solver techniques that can find high-quality solutions to difficult real-world optimisation problems. The traditional workflow is to exactly model the problem and then enter this model into a general-purpose “black-box” solver. In practice, however, many problems cannot be solved completely automatically, but require a “human-in-the-loop” to iteratively refine the model and give hints to the solver. In this paper, we explore the parallels between this interactive optimisation workflow and the visual analytics sense-making loop. We assert that interactive optimisation is essentially a visual analytics task and propose a problem-solving loop analogous to the sense-making loop. We explore these ideas through an in-depth analysis of a use-case in prostate brachytherapy, an application where interactive optimisation may be able to provide significant assistance to practitioners in creating prostate cancer treatment plans customised to each patient's tumour characteristics. However, current brachytherapy treatment planning is usually a careful, mostly manual process involving multiple professionals. We developed a prototype interactive optimisation tool for brachytherapy that goes beyond current practice in supporting focal therapy - targeting tumour cells directly rather than simply seeking coverage of the whole prostate gland. We conducted semi-structured interviews, in two stages, with seven radiation oncology professionals in order to establish whether they would prefer to use interactive optimisation for treatment planning and whether such a tool could improve their trust in the novel focal therapy approach and in machine generated solutions to the problem.

Libraries are increasingly offering on-line digital access to their collections. However, traditional search-based interfaces are restrictive and do not encourage the user to explore the collection in the same way that a physical collection does. We present the Mitchell WordCloud, a novel on-line interface to the David Scott Mitchell collection of the State Library of New South Wales. Based on interface design principles for explorative search, it presents the user with a word cloud derived from the collection and a list of titles. As the user drags words from the word cloud to tell the system what they like or dislike the title list is reordered. The surrounding interface elements -- image bar, time line and Dewey bar -- provide complementary insights into the collection. The traditional vector space model for measuring text similarity was extended to take account of user dislikes and to order words in the word cloud. User studies confirmed that the Mitchell WordCloud is easy to use and encourages exploration.

Document engineering is all about building systems and tools that allow people to work with documents and document collections. A key aspect is the usefulness and usability of these tools. In this tutorial, we will look at the many different kinds of user studies and user evaluations that can be used to inform the design and improve utility and usability of document engineering applications. The tutorial will be based on actual studies and will also give participants a chance to explore how they might use these techniques in their research or system development.

We explore the relative merits of matrix, node-link and combined side-by-side views for the visualisation of weighted networks with three controlled studies: (1) finding the most effective visual encoding for weighted edges in matrix representations; (2) comparing matrix, node-link and combined views for static weighted networks; and (3) comparing MatrixWave, Sankey and combined views of both for event-sequence data. Our studies underline that node-link and matrix views are suited to different analysis tasks. For the combined view, our studies show that there is a perceptually complementary effect in terms of improved accuracy for some tasks, but that there is a cost in terms of longer completion time than the faster of the two techniques alone. Eye-movement data shows that for many tasks participants strongly favour one of the two views, after trying both in the training phase.

We explore the effectiveness of visualizing dense directed graphs by replacing individual edges with edges connected to 'modules'-or groups of nodes-such that the new edges imply aggregate connectivity. We only consider techniques that offer a lossless compression: that is, where the entire graph can still be read from the compressed version. The techniques considered are: a simple grouping of nodes with identical neighbor sets; Modular Decomposition which permits internal structure in modules and allows them to be nested; and Power Graph Analysis which further allows edges to cross module boundaries. These techniques all have the same goal--to compress the set of edges that need to be rendered to fully convey connectivity--but each successive relaxation of the module definition permits fewer edges to be drawn in the rendered graph. Each successive technique also, we hypothesize, requires a higher degree of mental effort to interpret. We test this hypothetical trade-off with two studies involving human participants. For Power Graph Analysis we propose a novel optimal technique based on constraint programming. This enables us to explore the parameter space for the technique more precisely than could be achieved with a heuristic. Although applicable to many domains, we are motivated by--and discuss in particular--the application to software dependency analysis.

Automatic layout of tables is required in online applications because of the need to tailor the layout to the viewport width, choice of font, and dynamic content. However, if the table contains text, minimizing the height of the table for a fixed maximum width is NP-hard. Thus, more efficient heuristic algorithms are required. We evaluate the HTML table layout recommendation and find that while it generally produces quite compact layout it is brittle and can lead to quite uncompact layout. We present an alternate heuristic algorithm. It uses a greedy strategy that starts from the widest reasonable layout and repeatedly chooses to narrow the column for which narrowing leads to the least increase in table height. The algorithm is simple, fast enough to be used in online applications, and gives significantly more compact layout than is obtained with HTML’s recommended table layout algorithm.

International audience; In this paper, we investigate Confluent Drawings (CD), a technique for bundling edges in node-link diagrams based on network connectivity. Edge-bundling techniques are designed to reduce edge clutter in node-link diagrams by coalescing lines into common paths or bundles. Unfortunately, traditional bundling techniques introduce ambiguity since edges are only bundled by spatial proximity, rather than network connectivity; following an edge from its source to its target can lead to the perception of incorrect connectivity if edges are not clearly separated within the bundles. Contrary, CDs bundle edges based on common sources or targets. Thus, a smooth path along a confluent bundle indicates precise connectivity. While CDs have been described in theory, practical investigation and application to real-world networks (i.e., networks beyond those with certain planarity restrictions) is currently lacking. Here, we provide the first algorithm for constructing CDs from arbitrary directed and undirected networks and present a simple layout method, embedded in a sand box environment providing techniques for interactive exploration. We then investigate patterns and artifacts in CDs, which we compare to other common edge-bundling techniques. Finally, we present the first user study that compares edge-compression techniques, including CD, power graphs, metro-style, and common edge bundling. We found that users without particular expertise in visualization or network analysis are able to read small CDs without difficulty. Compared to existing bundling techniques, CDs are more likely to allow people to correctly perceive connectivity.

High-quality immersive display technologies are becoming mainstream with the release of head-mounted displays (HMDs) such as the Oculus Rift. These devices potentially represent an affordable alternative to the more traditional, centralised CAVE-style immersive environments. One driver for the development of CAVE-style immersive environments has been collaborative sense-making. Despite this, there has been little research on the effectiveness of collaborative visualisation in CAVE-style facilities, especially with respect to abstract data visualisation tasks. Indeed, very few studies have focused on the use of these displays to explore and analyse abstract data such as networks and there have been no formal user studies investigating collaborative visualisation of abstract data in immersive environments. In this paper we present the results of the first such study. It explores the relative merits of HMD and CAVE-style immersive environments for collaborative analysis of network connectivity, a common and important task involving abstract data. We find significant differences between the two conditions in task completion time and the physical movements of the participants within the space: participants using the HMD were faster while the CAVE2 condition introduced an asymmetry in movement between collaborators. Otherwise, affordances for collaborative data analysis offered by the low-cost HMD condition were not found to be different for accuracy and communication with the CAVE2. These results are notable, given that the latest HMDs will soon be accessible (in terms of cost and potentially ubiquity) to a massive audience. Refereed/Peer-reviewed