Susan Keller

Creative problem solving in digital space using visual analytics

Interactive visual analytics has a unique process of creative design.Data visualization tools can foster personal and collective creativity.Narratives and metaphors enhance communication of analytic insights.Creative visual analytics supports exploration of big and messy data sets.Human intuition is needed in business decision-making and problem-solving. This article presents a framework for understanding and explaining digital creativity within the growing area of interactive visual analytics. Through the study of extant literature, existing software products, and our own development experience, various aspects of digital creativity are explored in the context of interactive visual analytics and its application to decision-making and problem-solving.The proposed framework explores and fuses a number of models of individual, social, and domain creativity. It explains the challenges of the analyst navigating through rapidly growing and ubiquitous digital data with an objective to explore it, discover its meanings and associations, as well as solve problems and arrive at effective business decisions. As a creative process, interactive visual analytics differs from other forms of digital creativity, as it utilizes analytic models, relies on the analysts mental imagery and involves an iterative process of generation and evaluation of ideas in digital media, as well as planning, execution, and refinement of the associated actions. This process is also characterized as collaborative and social by nature as it comprises of analysts from data, problem, and visual domains, who share ideas and actions during analytic activities.We conclude by suggesting that interactive data visualization may provide opportunities for lay people to creatively engage with data analytics to explore the vast data resources that are freely available and in so doing, gain and communicate insights which may have the potential to impact their private lives and the world at large.

Employability skills : student perceptions of an IS final year capstone subject

Abstract This paper reports on a qualitative study aimed at investigating whether Australian Information Systems (IS) students undertaking a team-based capstone subject with real clients believed the subject had enhanced their employability skills. This research is important because UK and Australian governments and industry are increasingly pressuring universities to focus more on developing employability skills. The paper makes a contribution to the literature since there are few empirical studies examining students’ perceptions of capstone subjects and none, to our knowledge, focusing on employability skills. Our study suggests that students believed the capstone subject did improve a broad range of employability skills and it also demonstrates the interrelated nature of these skills. We conjecture that the team-based, real-client model of capstone is particularly useful, compared to other capstone models, because it is especially effective at integrating the range of employability skills such as teamwork, communication, problem solving and self-management.

Metaphors in Interactive Visual Analytics

We intuitively understand primary metaphors because they spring from our lived experience as humans. This paper explores the role of primary metaphor in interactive visual analytics. We describe and provide examples of several primary metaphors that can be used in designing and communicating visual representations. We also illustrate how rich and immersive visual analytics environment can support intuitive interaction based around natural metaphors.

Interactive Exploration of Data with Visual Metaphors

Visual Analytics (VA) is an approach to data analysis by means of visual manipulation of data representation, which relies on innate human abilities of perception and cognition. Even though current visual toolkits in the Business Analytics (BA) domain have improved the effectiveness of data exploration, analysis and reporting, their features are often not intuitive, and can be confusing and difficult to use. Moreover, visualizations generated from these toolkits are mostly accessible to specialist users. Thus, there is a need for analytic environments that support data exploration, interpretation and communication of insight that do not add to the cognitive load of the analyst and their non-technical clients. In this conceptual paper, we explore the potential of primary metaphors, which arise out of human lived and sensory-motor experiences, in the design of immersive visual analytics environments. Primary metaphors provide ideas for representation of time, space, quantity, similarity, actions and team work. Using examples developed in our own work, we also explain how to combine such metaphors to create complex and cognitively acceptable visual metaphors, such as 3D data terrains that approximate our intuition of reality and create opportunities for data to be viewed, navigated, explored, touched, changed, discussed, reported and described to others, individually or collaboratively.

ICT and Dataveillance

Dataveillance, the collection, storage and mining of data and images, is increasing and new emerging technologies seem to inevitably contribute to ever more dataveillance. In this chapter, we outline the key social drivers for dataveillance and illustrate some of the roles emerging technology plays in dataveillance. We then turn to the question of the relationship of technology to its use and how non-neutral outcomes eventuate. Why does new technology seemingly lead to dataveillance rather than empowerment of the citizen, worker and consumer? To unravel this, we develop a social ecological model of technology cooption. In this model, we show how technology cooption is contested at each stage of technology development. Further, we show that the outcome of such contestation is the non-neutrality of the technology. The technology cooption model provides a middle range theory for empirical analysis by identifying the key elements of technology cooption and their proposed links and the role of the stakeholders in such cooption.