scispace - formally typeset
Search or ask a question
Author

Alison Duffy

Bio: Alison Duffy is an academic researcher from City University London. The author has contributed to research in topics: Data visualization & Visualization. The author has an hindex of 2, co-authored 2 publications receiving 77 citations.

Papers
More filters
Journal ArticleDOI
TL;DR: This work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed and is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development.
Abstract: We enhance a user-centered design process with techniques that deliberately promote creativity to identify opportunities for the visualization of data generated by a major energy supplier. Visualization prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open - enabling successful exploration of possibilities for visualization in Smart Home data analysis. The process gives rise to novel designs and design metaphors including data sculpting. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. It is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development, paving the way for further use and study of creativity methods in visualization design.

77 citations

Proceedings ArticleDOI
Graham Dove1, Sara Jones1, Jason Dykes1, Amanda Brown1, Alison Duffy1 
17 Jun 2013
TL;DR: In this article, the authors present a case study in which they employ data visualization within a service design workshop, where participants gain insights that are later realized in design ideas, and compare the effectiveness of two different styles of data visualization.
Abstract: Creativity workshops have proved effective in drawing out unexpected requirements and giving form to participants' novel ideas. Here, we introduce a new addition to the workshop designer's toolkit: interactive data visualization, used as stimuli to prompt insight and inspire creativity. We first describe a pilot study in which we compare the effectiveness of two different styles of data visualization. Here we found that a less ambiguous style was more effective in supporting idea generation. Following this, we report a case study in which we employ data visualization within a service design workshop, where participants gain insights that are later realized in design ideas.

8 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: The design activity framework is introduced, a process model that explicitly connects to the nested model, a well-known visualization design decision model, which provides several research outcomes in the domain of cybersecurity, including an extended data abstraction and rich opportunities for future visualization research.
Abstract: An important aspect in visualization design is the connection between what a designer does and the decisions the designer makes. Existing design process models, however, do not explicitly link back to models for visualization design decisions. We bridge this gap by introducing the design activity framework, a process model that explicitly connects to the nested model, a well-known visualization design decision model. The framework includes four overlapping activities that characterize the design process, with each activity explicating outcomes related to the nested model. Additionally, we describe and characterize a list of exemplar methods and how they overlap among these activities. The design activity framework is the result of reflective discussions from a collaboration on a visualization redesign project, the details of which we describe to ground the framework in a real-world design process. Lastly, from this redesign project we provide several research outcomes in the domain of cybersecurity, including an extended data abstraction and rich opportunities for future visualization research.

112 citations

Journal ArticleDOI
TL;DR: This survey first summarizes frequently used data types in urban visual analytics, and then elaborate on existing visualization techniques for time, locations and other properties of urban data, and discusses how visualization can be combined with automated analytical approaches.
Abstract: Nowadays, various data collected in urban context provide unprecedented opportunities for building a smarter city through urban computing. However, due to heterogeneity, high complexity and large volumes of these urban data, analyzing them is not an easy task, which often requires integrating human perception in analytical process, triggering a broad use of visualization. In this survey, we first summarize frequently used data types in urban visual analytics, and then elaborate on existing visualization techniques for time, locations and other properties of urban data. Furthermore, we discuss how visualization can be combined with automated analytical approaches. Existing work on urban visual analytics is categorized into two classes based on different outputs of such combinations: 1) For data exploration and pattern interpretation , we describe representative visual analytics tools designed for better insights of different types of urban data. 2) For visual learning , we discuss how visualization can help in three major steps of automated analytical approaches (i.e., cohort construction; feature selection & model construction; result evaluation & tuning) for a more effective machine learning or data mining process, leading to sort of artificial intelligence, such as a classifier, a predictor or a regression model. Finally, we outlook the future of urban visual analytics, and conclude the survey with potential research directions.

101 citations

Journal ArticleDOI
TL;DR: A new perspective on research conducted through visualization design study is developed that emphasizes design as a method of inquiry and the broad range of knowledge-contributions achieved through it as multiple, subjective, and socially constructed.
Abstract: We develop a new perspective on research conducted through visualization design study that emphasizes design as a method of inquiry and the broad range of knowledge-contributions achieved through it as multiple, subjective, and socially constructed. From this interpretivist position we explore the nature of visualization design study and develop six criteria for rigor. We propose that rigor is established and judged according to the extent to which visualization design study research and its reporting are INFORMED , REFLEXIVE , ABUNDANT , PLAUSIBLE , RESONANT , and TRANSPARENT . This perspective and the criteria were constructed through a four-year engagement with the discourse around rigor and the nature of knowledge in social science, information systems, and design. We suggest methods from cognate disciplines that can support visualization researchers in meeting these criteria during the planning, execution, and reporting of design study. Through a series of deliberately provocative questions, we explore implications of this new perspective for design study research in visualization, concluding that as a discipline, visualization is not yet well positioned to embrace, nurture, and fully benefit from a rigorous, interpretivist approach to design study. The perspective and criteria we present are intended to stimulate dialogue and debate around the nature of visualization design study and the broader underpinnings of the discipline.

98 citations

Journal ArticleDOI
TL;DR: The Five Design Sheet (FdS) methodology enables users to create information visualization interfaces through lo-fidelity methods through sketching and an evaluation of the FdS using the System Usability Scale.
Abstract: Sketching designs has been shown to be a useful way of planning and considering alternative solutions. The use of lo-fidelity prototyping, especially paper-based sketching, can save time, money and converge to better solutions more quickly. However, this design process is often viewed to be too informal. Consequently users do not know how to manage their thoughts and ideas (to first think divergently, to then finally converge on a suitable solution). We present the Five Design Sheet (FdS) methodology. The methodology enables users to create information visualization interfaces through lo-fidelity methods. Users sketch and plan their ideas, helping them express different possibilities, think through these ideas to consider their potential effectiveness as solutions to the task (sheet 1); they create three principle designs (sheets 2,3 and 4); before converging on a final realization design that can then be implemented (sheet 5). In this article, we present (i) a review of the use of sketching as a planning method for visualization and the benefits of sketching, (ii) a detailed description of the Five Design Sheet (FdS) methodology, and (iii) an evaluation of the FdS using the System Usability Scale, along with a case-study of its use in industry and experience of its use in teaching.

86 citations