The Stitch in Time project extends a traditional timeline visualisation of Australian convict women's lives by creating physical data embroideries drawing from the available historical data of individual women. Th...
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ISBN:
(纸本)9798350381627
The Stitch in Time project extends a traditional timeline visualisation of Australian convict women's lives by creating physical data embroideries drawing from the available historical data of individual women. The timelines visualise the individual life courses of over 13,600 nineteenth century Australian convict women according to the paper trail left behind in the Colonial Archives. In this project we created 18 embroideries of 21 convict women, based on sketches inspired by specific pieces of information in each woman's life. This novel approach illuminates the personal lives of individual subjects, of whom little imagery has survived. By exhibiting the embroideries in the Penitentiary Chapel in Hobart, Tasmania, we hope to arouse interest in the largely forgotten lives of this first coerced generation of European settlers. We use the unusual medium of embroidery on fabric because it is tightly connected to the daily experiences of convict women. By extending traditional data visualisation using this specific form of data physicalisation, data embroidery, we aim to create compelling access points to engage with individual Australian convict stories and therefore make this significant part of Australian history more approachable1.
While social media promises open access to information, prior works suggest that it also plays a role as a catalyst for the social divide, which is often attributed to a shift towards algorithmic content curation base...
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ISBN:
(纸本)9798350307160
While social media promises open access to information, prior works suggest that it also plays a role as a catalyst for the social divide, which is often attributed to a shift towards algorithmic content curation based on users' digital footprints. To combat this issue, methods that support serendipity have received attention in recent years that aim to provide information beyond a user's viewpoint or preference. However, the utility of systems that promote serendipity in raising awareness of opposing viewpoints remains underexplored, especially in the political context. To that end, we conducted a study where we asked 14 participants to explore tweets about two politically charged topics- gun control and immigration- using an interaction-driven visual analytics tool that visualizes users' exploration patterns and provides serendipitous suggestions from opposing viewpoints. We found that as participants explored the tweets, they gradually became aware of opposing viewpoints and identified information they had not considered before which helped them gain knowledge about arguments from all sides. We also found while people were keen to use technology that promotes serendipity to cover more topical information, they do not necessarily trust the information found on social media. We hope that our work will motivate future researchers to investigate serendipitous aspects in visualizations to promote a more holistic exploration of various viewpoints.
Contraction Hierarchies (CH) are one of the most popular techniques for accelerating shortest path queries. In previous works, it has been shown that CH in principle can be instrumented to also produce variable level-...
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ISBN:
(纸本)9798350393811;9798350393804
Contraction Hierarchies (CH) are one of the most popular techniques for accelerating shortest path queries. In previous works, it has been shown that CH in principle can be instrumented to also produce variable level-of-detail renderings of road networks. Yet, the existing approach still suffers from severe drawbacks like topological inconsistencies or distortion of the overall shape of the road network, which impairs the practical usability. We significantly improve upon the existing approach both in terms of quality of the visual representation as well as query times. As a result, we obtain a lightweight augmentation of the CH data structure that allows for very efficient and visually pleasing rendering of massive road network data.
Physical visualizations (i.e., data representations by means of physical objects) have been used for many centuries in medical and anatomical education. Recently, 3D printing techniques started also to emerge. Still, ...
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ISBN:
(纸本)9781728180144
Physical visualizations (i.e., data representations by means of physical objects) have been used for many centuries in medical and anatomical education. Recently, 3D printing techniques started also to emerge. Still, other medical physicalizations that rely on affordable and easy-to-find materials are limited, while smart strategies that take advantage of the optical properties of our physical world have not been thoroughly investigated. We propose the Anatomical Edutainer, a workflow to guide the easy, accessible, and affordable generation of physicalizations for tangible, interactive anatomical edutainment. The Anatomical Edutainer supports 2D printable and 3D foldable physicalizations that change their visual properties (i.e., hues of the visible spectrum) under colored lenses or colored lights, to reveal distinct anatomical structures through user interaction.
Legible labels should not overlap with other marks in a chart. The state-of-the-art labeling algorithm detects overlaps using a set of points to approximate each mark's shape. This approach is inefficient for larg...
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ISBN:
(纸本)9781728180144
Legible labels should not overlap with other marks in a chart. The state-of-the-art labeling algorithm detects overlaps using a set of points to approximate each mark's shape. This approach is inefficient for large marks or many marks as it requires too many points to detect overlaps. In response, we present a Bitmap-Based label placement algorithm, which leverages occupancy bitmap to accelerate overlap detection. To create an occupancy bitmap, we rasterize marks onto a bitmap based on the area they occupy in the chart. With the bitmap, we can efficiently place labels without overlapping existing marks, regardless of the number and geometric complexity of the marks. This Bitmap-Based algorithm offers significant performance improvements over the state-of-the-art approach while placing a similar number of labels.
Transitions are widely used in data videos to seamlessly connect data-driven charts or connect visualizations and non-data-driven motion graphics. To inform the transition designs in data videos, we conduct a content ...
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ISBN:
(纸本)9781728180144
Transitions are widely used in data videos to seamlessly connect data-driven charts or connect visualizations and non-data-driven motion graphics. To inform the transition designs in data videos, we conduct a content analysis based on more than 3500 clips extracted from 284 data videos. We annotate visualization types and transition designs on these segments, and examine how these transitions help make connections between contexts. We propose a taxonomy of transitions in data videos, where two transition categories are defined in building fluent narratives by using visual variables.
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