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Machine Learning (ML) opens exciting scientific opportunities in K-12 STEM classrooms. However, students struggle with interpreting ML patterns due to limited data literacy. Face glyphs offer unique benefit by leveraging our brain’s facial feature processing. Yet, they have limitations like lacking contextual information and data biases. To address this, we created three enhanced face glyph visualizations: feature-independent and feature-aligned range views, and the sequential feature inspector. In a study with 25 high school students, feature-aligned range visualization helped contextual analysis, and the sequential feature inspector reduced missing data risks. Face glyphs also benefit the global interpretation of data.
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Associative Forms for Encoding Multivariate Climate Data
We are perpetually present in our environment, experiencing it with our senses. Scientific data describes the same environment quantitatively. Our goal is to use scientific and artistic methods to combine these environmental expressions and personal experience through the creation of glyphs visually abstracted from and associated with forms in nature in the representation of climate data. The use of these glyphs removes the distinctions between scientific data and sensory experience, to allow a fuller intuitive association between the two, creating an embodied experience and increasing awareness of the climate effects and changes all around us.
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- Award ID(s):
- 1704904
- PAR ID:
- 10474120
- Editor(s):
- Hinrichs, U.
- Publisher / Repository:
- IEEE VIS 2023
- Date Published:
- Journal Name:
- IEEE VIS Arts Program
- ISSN:
- 2767-6994
- Subject(s) / Keyword(s):
- Glyphs environmental visualization visual association art and design principles
- Format(s):
- Medium: X
- Location:
- Melbourne, AU
- Sponsoring Org:
- National Science Foundation
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We investigate how to co-opt the perception of causality to aid the analysis of multivariate data. We propose Dynamic Glyphs (DyGs), an animated extension to traditional glyphs. DyGs encode data relations through seemingly physical interactions between glyph parts. We hypothesize that this representation gives rise to impressions of causality, enabling observers to reason intuitively about complex, multivariate dynamics. In a crowdsourced experiment, participants’ accuracy with DyGs exceeded or was comparable to non-animated alternatives. Moreover, participants showed a propensity to infer higher-dimensional relations with DyGs. Our findings suggest that visual causality can be an effective ‘channel’ for communicating complex data relations that are otherwise difficult to think about. We discuss the implications and highlight future research opportunities.more » « less
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Hinrichs, Uta Perin (Ed.)As scientific data continues to grow in size, complexity, and density, the representation scope of three-dimensional spaces, data sampling methods, and transfer functions have improved in parallel, allowing visualization practitioners to produce richer multidimensional encodings. Glyphs, in particular, have become an essential encoding tool due to their versatile applications in co-located multi-variate volumetric datasets. While prior work has been conducted investigating the perceptual attributes of computationally-generated three-dimensional glyph-forms for scientific visualization, their affective and expressive qualities have yet to be examined. Further, our prior work has demonstrated the benefits of artist hand-created glyph forms in contrast to commonly-used synthetic forms in increasing visual diversity, discrimination, and expressive association in complex environmental datasets. In order to begin to address this gap, we establish preliminary groundwork for an affective design space for hand-created glyph forms, produce a novel set of glyphforms based on this design space, describe a non-verbal method for discovering affective classifications of glyph-forms adopted from current affect theory, and report the results of two studies that explore how these three-dimensional forms produce consistent affective responses across assorted study cohorts.more » « less
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Hinrichs, Ute; Perin, Charles (Ed.)As scientific data continues to grow in size, complexity, and density, the representation scope of three-dimensional spaces, data sampling methods, and transfer functions have improved in parallel, allowing visualization practitioners to produce richer multidimensional encodings. Glyphs, in particular, have become an essential encoding tool due to their versatile applications in co-located multivariate volumetric datasets. While prior work has been conducted investigating the perceptual attributes of computationally-generated three-dimensional glyph-forms for scientific visualization, their affective and expressive qualities have yet to be examined. Further, our prior work has demonstrated the benefits of artist hand-created glyph forms in contrast to commonly-used synthetic forms in increasing visual diversity, discrimination, and expressive association in complex environmental datasets. In order to begin to address this gap, we establish preliminary groundwork for an affective design space for hand-created glyph forms, produce a novel set of glyph forms based on this design space, describe a non-verbal method for discovering affective classifications of glyph-forms adopted from current affect theory, and report the results of two studies that explore how these three-dimensional forms produce consistent affective responses across assorted study cohorts.more » « less
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Accepted Manuscript1.0
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- The DOI is not currently available.
