8,778 research outputs found
Exploring the Design Space of Immersive Urban Analytics
Recent years have witnessed the rapid development and wide adoption of
immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft
HoloLens. These immersive devices have the potential to significantly extend
the methodology of urban visual analytics by providing critical 3D context
information and creating a sense of presence. In this paper, we propose an
theoretical model to characterize the visualizations in immersive urban
analytics. Further more, based on our comprehensive and concise model, we
contribute a typology of combination methods of 2D and 3D visualizations that
distinguish between linked views, embedded views, and mixed views. We also
propose a supporting guideline to assist users in selecting a proper view under
certain circumstances by considering visual geometry and spatial distribution
of the 2D and 3D visualizations. Finally, based on existing works, possible
future research opportunities are explored and discussed.Comment: 23 pages,11 figure
Interactive visual exploration of a large spatio-temporal dataset: Reflections on a geovisualization mashup
Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the clataset, the specific tools used and the 'rnashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here
Exploranative Code Quality Documents
Good code quality is a prerequisite for efficiently developing maintainable
software. In this paper, we present a novel approach to generate exploranative
(explanatory and exploratory) data-driven documents that report code quality in
an interactive, exploratory environment. We employ a template-based natural
language generation method to create textual explanations about the code
quality, dependent on data from software metrics. The interactive document is
enriched by different kinds of visualization, including parallel coordinates
plots and scatterplots for data exploration and graphics embedded into text. We
devise an interaction model that allows users to explore code quality with
consistent linking between text and visualizations; through integrated
explanatory text, users are taught background knowledge about code quality
aspects. Our approach to interactive documents was developed in a design study
process that included software engineering and visual analytics experts.
Although the solution is specific to the software engineering scenario, we
discuss how the concept could generalize to multivariate data and report
lessons learned in a broader scope.Comment: IEEE VIS VAST 201
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