Information visualisation researchers have posited that author-driven narratives will allow information to be conveyed efficiently and argue for the adoption of storytelling techniques in information visualisation. However, there is limited work describing the effects of author-driven narratives in users' comprehension and memorability of visualisations in relation to interactive visualisations. Recommendations for author-driven visualisation stories are largely based on anecdotal reports or research from the arts, and not on studies in information visualisation. To investigate these issues, we carried out a study that compared purely author-driven narratives with interactive visualisations devoid of author narratives, in terms of comprehension and short-term and long-term memorability. We found that the presence of narration in author-driven stories significantly aided the understanding of information but had no significant effect on the long-term recall of information from visualisations.

Visual data storytelling has gained widespread adoption as a means of communicating information visualisation. This is partly due to the increased interest in data journalism. Besides being engaging, it has been shown to foster better comprehension and memorability of information to target audiences. The visual data story authoring process involves several stages. However, current tools neither consolidate the visual data story creation process nor integrate the essential features, such as the recommendation of logically sequenced story pieces, for producing coherent narratives. This paper briefly demonstrates our approach and framework for supporting the creation of logically sequenced visual data stories.

With the proliferation of Internet of Things (IoT) devices, there is a demand for technologies to support high-velocity, dynamic resource provisioning to provide secure, cost-efficient, and real-time IoT services in resource-constrained environments. Conventional fog computing by itself cannot address such requirements and needs to be complemented with opportunistic fog computing, by providing mobile fog resources on-demand. In this paper, we discuss key issues in this area, and investigate potential solutions from existing work. We conclude this paper with a summary of gaps, and propose an opportunistic architecture for future work.

Today it is very common for software systems to be built by teams located in more than one country. For example, a project team may be located in the US while the team lead resides in Sweden. How then should students be trained for this kind of work? Senior design or capstone projects offer students real-world hands-on experience but rarely while working internationally. One reason is that most instructors do not have international business contacts that allow them to find project sponsors in other countries. Another reason is the fear of having to invest a huge amount of time managing an international project. In this paper we present the general concepts related to "International Capstone Project Exchanges", the basic model behind the exchanges (student teams are led by an industry sponsor residing in a different country) and several alternate models that have been used in practice. We will give examples from projects in the US, Germany, Sweden, Australia, and Colombia. We have extended the model beyond software projects to include engineering projects as well as marketing, and journalism. We conclude with a description of an International Capstone Project Exchange website that we have developed to aid any university in establishing their own international project exchange.

Effective visualisation plays a vital role in generating insights from data. The selection of graph types however, is highly dependent on the analysis tasks and data types at hand. For example, spatio-temporal visualisations encode changes in data over time and space. Although they have the potential of revealing overall tendencies and movement patterns, building effective spatio-temporal visualisations is challenging because it requires encoding all three attributes of spatio-temporal data i.e. thematic (values of attributes), temporal and spatial in a single visualisation. In this application design study, we present PedaViz for representing hour-level spatio-temporal attributes within a single visualisation; a 24-hour radial visual metaphor that encodes hour-level temporal and daily temperature attributes while utilising a thematic map display to present spatial attributes. The design was applied on city planning domain using Melbourne's pedestrian count and temperature data. Results of our preliminary user evaluation suggest that our visualisation is easily understandable by users; and supports users in carrying out selected analysis tasks.

Modern enterprise software systems often need to interact with a large number of distributed and\nheterogeneous systems. As a result, integration testing has become a critical step in their software\ndevelopment lifecycle. Service virtualization is an emerging technique for creating testing environments with realistic executable models of server side production-like behaviours. However, building models in existing service virtualization approaches is very challenging, requiring either significant human effort or the availability of interactive tracing records. In this paper, we present a domain-specific modeling approach to generate complex, virtualized testing environments. Our approach allows domain experts to use a suite of domain-specific visual modeling languages to model key interface layers of applications at a high level of abstraction. These layered models are then transformed into a testing runtime environment for application integration testing. We have conducted a technical comparison with two other existing approaches and also carried out a user study. The user study demonstrated the acceptance of our new testing environment emulation approach from software testing experts and developers.

We present an interactive visualisation tool for recommending travel trajectories. This system is based on new machine learning formulations and algorithms for the sequence recommendation problem. The system starts from a map-based overview, taking an interactive query as starting point. It then breaks down contributions from different geographical and user behavior features, and those from individual points-of-interest versus pairs of consecutive points on a route. The system also supports detailed quantitative interrogation by comparing a large number of features for multiple points. Effective trajectory visualisations can potentially benefit a large cohort of online map users and assist their decision-making. More broadly, the design of this system can inform visualisations of other structured prediction tasks, such as for sequences or trees.

We present a visualisation of Melbourne pedestrian count data and a visual metaphor for representing hour-level temporal dimension in this context. The pedestrian count data is captured from sensors located around the city. A visualisation web application is implemented that incorporates a thematic map of these sensor locations with a 24-hour clocklike polygon that shows pedestrian counts at every hour, and alongside a display of daily temperature. Our visualisation allows users to analyse how the city is used by pedestrians. Moreover, the design of our visualisation was driven by the type of analysis tasks carried out by city planners. The visualisation would help city planners better understand the dynamics of pedestrian activity within the city and aid them in urban management and design policy recommendation.

Software environment emulation provides a means for simulating an operational environment of a system. This process involves approximation of systems’ external behaviors and their communications with a system to be tested in the environment. Development of such an environment is a tedious task and involves complex low level coding. Model driven engineering is an avenue to raise the level of abstraction beyond programming by specifying solution directly using problem domain concepts. In this paper we propose a novel domain-specific modeling tool to generate complex testing environments. Our tool employs a suite of domain-specific visual modeling languages for modeling emulation environment at a high level of abstraction. These high level specifications are then automatically transformed to runtime environment for application integration testing, boosting development productivity and ease of use. The tool demonstration video can be accessed here: https://youtu.be/H3Vg20Juq80.

Software integration testing plays an increasingly important role as the software industry has experienced a major change from isolated applications to highly distributed computing environments. Conducting integration testing is a challenging task because it is often very difficult to replicate a real enterprise environment. Emulating testing environment is one of the key solutions to this problem. However, existing specification-based emulation techniques require manual coding of their message processing engines, therefore incurring high development cost. In this paper, we present a suite of domain-specific visual modeling languages to describe emulated testing enviroements at a high abstraction level. Our solution allows domain experts to model a testing environment from abstract interface layers. These layer models are then transformed to runtime environment for application testing. Our user study shows that our visual languages are easy to use, yet with sufficient expressive power to model complex testing applications.

This paper demonstrates a multi-view framework for Rapid APPlication Tool (RAPPT). RAPPT enables rapid development of mobile applications. It employs a multilevel approach to mobile application development: a Domain Specific Visual Language to define the high level structure of mobile apps, a Domain Specific Textual Language to define behavioural concepts, and concrete source code for fine grained improvements.

Visualizing road traffic datasets involves representing junctions, their links, and the attributes of those links. Current traffic visualization techniques are not sufficient for professional traffic engineers, as they are limited in the number of attributes that can be represented. This paper proposes a new approach to visualize multiple attributes on graph edges without compromising their visibility. In particular, we introduce a parameterized connector symbol that increases the number of attributes that can be displayed on graph edges. We demonstrate that our approach can significantly increase the number of traffic parameters that can be displayed compared to existing traffic visualizations.

Visual notations are a key aspect of visual languages. They provide a direct mapping between the intended information and set of graphical symbols. Visual notations are most often implemented using the low level syntax of programming languages which is time consuming, error prone, difficult to maintain and hardly human-centric. In this paper we describe an alternative approach to generating visual notations using by-example model transformations. In our new approach, a semantic mapping between model and view is implemented using model transformations. The notations resulting from this approach can be reused by mapping varieties of input data to their model and can be composed into different visualizations. Our approach is implemented in the CONVErT framework and has been applied to many visualization examples. Three case studies for visualizing statistical charts, visualization of traffic data, and reuse of a Minard's map visualization's components, are presented in this paper. A detailed user study of our approach for reusing notations and generating visualizations has been provided. 80% of the participants in this user study agreed that the novel approach to visualization was easy and 87% stated that they quickly learned to use the tool support.

Visual notations are a key aspect of visual languages. They provide a direct mapping between the intended information and set of graphical symbols. Visual notations are most often implemented using the low level syntax of programming languages which is time consuming, error prone, difficult to maintain and hardly human-centric. In this paper we describe an alternative approach to generating visual notations using by-example model transformations. In our new approach, a semantic mapping between model and view is implemented using model transformations. The notations resulting from this approach can be reused by mapping varieties of input data to their model and can be composed into different visualisations. Our approach is implemented in the CONVErT framework and has been applied to many visualisation examples. Two case studies for visualising statistical charts and visualisation of traffic data are presented in this paper. A detailed user study of our approach for reusing notations and generating visualisations has been provided that shows good reusability and general acceptance of the novel approach.

The CONcrete Visual assistEd Transformation (CONVErT) framework provides facilities to generate reusable notations and compose them to form a wide variety of visualisations. With an increased number of notations in large scale visualisations, it is crucial to use advanced layout algorithms to improve understandability of such complex visualisations. This showpiece paper demonstrates how advanced layout algorithms can be integrated into the notation specifications of CONVErT to generate layouts of complex visualisations.

Complex model transformation is crucial in several domains, including Model-Driven Engineering (MDE), information visualisation and data mapping. Most current approaches use meta-model-driven transformation specification via coding in textual scripting languages. This paper demonstrates a novel approach and tool support that instead provides for specification of correspondences between models using concrete visualisations of source and target models, and generates transformation scripts from these by-example model correspondence specifications.

Model transformations are an important part of Model Driven Engineering (MDE). To generate a transformation with current MDE approaches, users are required to specify (or provide) complex meta-models and then engage in quite low-level coding in textual transformation scripting languages. This paper introduces a new approach to visualising source and target models that allows specifiers of complex data transformations to use the resultant visual notations for specifying transformations by example using drag and drop. We demonstrate the applicability of our new approach by an example case study.

Model transformations are the key part of Model Driven Engineering (MDE). However, their specification is not user-friendly, due to excessive use of metamodels and textual representation of transformation languages. This paper briefly describes the approach and tool under development for user-centric transformation generation using concrete model visualisations.

Model Driven Engineering (MDE) has become a commonly used approach in software engineering. It promotes using models as primary artefacts and proposes methods for transforming them to desired software products. However, the specification of models and their transformations in MDE with current techniques is not user-friendly, due to excessive use of high level abstract models and textual representation of transformation languages. This paper briefly describes CONVErT, an approach and tool developed for user-centric transformation generation using concrete model visualisations.