A visualisation framework for collaborative virtual environment usage information

Due to the popularity of modern Collaborative Virtual Environments, there has been a related increase in their size and complexity. Developers therefore need visualisations that expose usage patterns from logged data, to understand the structures and dynamics of these complex environments. This chapter presents a new framework for the process of visualising virtual environment usage data. Major components, such as an event model, designer task model and data acquisition infrastructure are described. Interface and implementation factors are also developed, along with example visualisation techniques that make use of the new task and event model. A case study is performed to illustrate a typical scenario for the framework, and its benefits to the environment development team.

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.

Multi-faceted visualisation of worklists

Due to the popularity of modern Collaborative Virtual Environments, there has been a related increase in their size and complexity. Developers therefore need visualisations that expose usage patterns from logged data, to understand the structures and dynamics of these complex environments. This chapter presents a new framework for the process of visualising virtual environment usage data. Major components, such as an event model, designer task model and data acquisition infrastructure are described. Interface and implementation factors are also developed, along with example visualisation techniques that make use of the new task and event model. A case study is performed to illustrate a typical scenario for the framework, and its benefits to the environment development team.

Visualising invisible networks as collaborative arts practice

This paper examines approaches to the visualisation of ‘invisible’ communications networks. It situates network visualisation as a critical design exercise, and explores how community artists might use such a practice to develop telematic art projects – works that use communications networks as their medium. The paper’s hypotheses are grounded in the Australian community media arts field, but could be applied to other collaborative contexts.

Science and engineering for whole of life : integrating education, research and public engagement in a collaborative environment

Policy makers increasingly recognise that an educated workforce with a high proportion of Science, Technology, Engineering and Mathematics (STEM) graduates is a pre-requisite to a knowledge-based, innovative economy. Over the past ten years, the proportion of first university degrees awarded in Australia in STEM fields is below the global average and continues to decrease from 22.2% in 2002 to 18.8% in 2010 [1]. These trends are mirrored by declines between 20% and 30% in the proportions of high school students enrolled in science or maths. These trends are not unique to Australia but their impact is of concern throughout the policy-making community. To redress these demographic trends, QUT embarked upon a long-term investment strategy to integrate education and research into the physical and virtual infrastructure of the campus, recognising that expectations of students change as rapidly as technology and learning practices change. To implement this strategy, physical infrastructure refurbishment/re-building is accompanied by upgraded technologies not only for learning but also for research. QUT’s vision for its city-based campuses is to create vibrant and attractive places to learn and research and to link strongly to the wider surrounding community. Over a five year period, physical infrastructure at the Gardens Point campus was substantially reconfigured in two key stages: (a) a >$50m refurbishment of heritage-listed buildings to encompass public, retail and social spaces, learning and teaching “test beds” and research laboratories and (b) destruction of five buildings to be replaced by a $230m, >40,000m2 Science and Engineering Centre designed to accommodate retail, recreation, services, education and research in an integrated, coordinated precinct. This landmark project is characterised by (i) self-evident, collaborative spaces for learning, research and social engagement, (ii) sustainable building practices and sustainable ongoing operation and; (iii) dynamic and mobile re-configuration of spaces or staffing to meet demand. Innovative spaces allow for transformative, cohort-driven learning and the collaborative use of space to prosecute joint class projects. Research laboratories are aggregated, centralised and “on display” to the public, students and staff. A major visualisation space – the largest multi-touch, multi-user facility constructed to date – is a centrepiece feature that focuses on demonstrating scientific and engineering principles or science oriented scenes at large scale (e.g. the Great Barrier Reef). Content on this visualisation facility is integrated with the regional school curricula and supports an in-house schools program for student and teacher engagement. Researchers are accommodated in a combined open-plan and office floor-space (80% open plan) to encourage interdisciplinary engagement and cross-fertilisation of skills, ideas and projects. This combination of spaces re-invigorates the on-campus experience, extends educational engagement across all ages and rapidly enhances research collaboration.

A virtual environment for medical radiation collaborative learning

Asoftware-based environment was developed to provide practical training in medical radiation principles and safety. The Virtual Radiation Laboratory application allowed students to conduct virtual experiments using simulated diagnostic and radiotherapy X-ray generators. The experiments were designed to teach students about the inverse square law, half value layer and radiation protection measures and utilised genuine clinical and experimental data. Evaluation of the application was conducted in order to ascertain the impact of the software on students’ understanding, satisfaction and collaborative learning skills and also to determine potential further improvements to the software and guidelines for its continued use. Feedback was gathered via an anonymous online survey consisting of a mixture of Likert-style questions and short answer open questions. Student feedback was highly positive with 80 % of students reporting increased understanding of radiation protection principles. Furthermore 72 % enjoyed using the software and 87 %of students felt that the project facilitated collaboration within small groups. The main themes arising in the qualitative feedback comments related to efficiency and effectiveness of teaching, safety of environment, collaboration and realism. Staff and students both report gains in efficiency and effectiveness associated with the virtual experiments. In addition students particularly value the visualisation of ‘‘invisible’’ physical principles and increased opportunity for experimentation and collaborative problembased learning. Similar ventures will benefit from adopting an approach that allows for individual experimentation while visualizing challenging concepts.

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.