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    User Preferences of Spatio-Temporal Referencing Approaches For Immersive 3D Radar Charts

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    The use of head-mounted display technologies for virtual reality experiences is inherently single-user-centred, allowing for the visual immersion of its user in the computer-generated environment. This isolates them from their physical surroundings, effectively preventing external visual information cues, such as the pointing and referral to an artifact by another user. However, such input is important and desired in collaborative scenarios when exploring and analyzing data in virtual environments together with a peer. In this article, we investigate different designs for making spatio-temporal references, i.e., visually highlighting virtual data artifacts, within the context of Collaborative Immersive Analytics. The ability to make references to data is foundational for collaboration, affecting aspects such as awareness, attention, and common ground. Based on three design options, we implemented a variety of approaches to make spatial and temporal references in an immersive virtual reality environment that featured abstract visualization of spatio-temporal data as 3D Radar Charts. We conducted a user study (n=12) to empirically evaluate aspects such as aesthetic appeal, legibility, and general user preference. The results indicate a unified favour for the presented location approach as a spatial reference while revealing trends towards a preference of mixed temporal reference approaches dependent on the task configuration: pointer for elementary, and outline for synoptic references. Based on immersive data visualization complexity as well as task reference configuration, we argue that it can be beneficial to explore multiple reference approaches as collaborative information cues, as opposed to following a rather uniform user interface design.Comment: 29 pages, 9 figures, 1 tabl

    Specification and implementation of mapping rule visualization and editing : MapVOWL and the RMLEditor

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    Visual tools are implemented to help users in defining how to generate Linked Data from raw data. This is possible thanks to mapping languages which enable detaching mapping rules from the implementation that executes them. However, no thorough research has been conducted so far on how to visualize such mapping rules, especially if they become large and require considering multiple heterogeneous raw data sources and transformed data values. In the past, we proposed the RMLEditor, a visual graph-based user interface, which allows users to easily create mapping rules for generating Linked Data from raw data. In this paper, we build on top of our existing work: we (i) specify a visual notation for graph visualizations used to represent mapping rules, (ii) introduce an approach for manipulating rules when large visualizations emerge, and (iii) propose an approach to uniformly visualize data fraction of raw data sources combined with an interactive interface for uniform data fraction transformations. We perform two additional comparative user studies. The first one compares the use of the visual notation to present mapping rules to the use of a mapping language directly, which reveals that the visual notation is preferred. The second one compares the use of the graph-based RMLEditor for creating mapping rules to the form-based RMLx Visual Editor, which reveals that graph-based visualizations are preferred to create mapping rules through the use of our proposed visual notation and uniform representation of heterogeneous data sources and data values. (C) 2018 Elsevier B.V. All rights reserved
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