Safire is a two-dimensional conceptual model that defines visualization similarity via comparison criteria and representation modalities to support retrieval system design and analysis.
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A qualitative study of South Korean parents shows that trauma and healing after learning a child is LGBTQ+ leads to identity reconstruction as supportive parents and more critical, protective informating practices.
The authors conduct a systematic literature review and real-world analysis to define Crowdsourced Context Systems and map a six-aspect design space with normative implications.
A literature review concludes that pursuing consensus in data annotation creates biased AI by dismissing subjective disagreements and enforcing geographic hegemony, and proposes mapping diversity instead.
Visualization retrieval systems can transform static collections of visualizations into dynamic, inquiry-based environments that support design exploration, data consumption, and resource management for data literacy education.
citing papers explorer
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Safire: Similarity Framework for Visualization Retrieval
Safire is a two-dimensional conceptual model that defines visualization similarity via comparison criteria and representation modalities to support retrieval system design and analysis.
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Journeys of Parents with LGBTQ+ Children: How Trauma and Healing Reshape Identity and (Mis)Informating Practices
A qualitative study of South Korean parents shows that trauma and healing after learning a child is LGBTQ+ leads to identity reconstruction as supportive parents and more critical, protective informating practices.
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Beyond Community Notes: A Framework for Understanding and Building Crowdsourced Context Systems for Social Media
The authors conduct a systematic literature review and real-world analysis to define Crowdsourced Context Systems and map a six-aspect design space with normative implications.
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The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation
A literature review concludes that pursuing consensus in data annotation creates biased AI by dismissing subjective disagreements and enforcing geographic hegemony, and proposes mapping diversity instead.
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Visualization Retrieval for Data Literacy: Position Paper
Visualization retrieval systems can transform static collections of visualizations into dynamic, inquiry-based environments that support design exploration, data consumption, and resource management for data literacy education.