Animated Vega-Lite: Unifying Animation with a Grammar of Interactive Graphics

Zong, Jonathan; Wootton, Dylan; Satyanarayan, Arvind; Pollock, Josh

doi:10.1109/tvcg.2022.3209369

Cited by 16 publications

(2 citation statements)

References 39 publications

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“…If our survey prompts any prediction, it is that new visualization languages will continue to be developed -some of which may be in the JSON-style. Since the final update to our survey in June 2022, we have observed a variety of additional JSON DSLs [199,326,420], suggesting there will long be many more.…”

Section: Discussionmentioning

confidence: 99%

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

McNutt¹

2023

Preprint

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Domain-specific languages represented in data serialization formats (such as Javascript Object Notation or JSON) are an increasingly common means to control numerous systems.These range from database queries to application configuration, narrative generation, Twitter bots, data visualization, and many other areas.These languages allow potentially unsophisticated human users to concisely specify their intent through logic and notation that is relevant to task domain.Further, they provide a means for computational agents to easily manipulate that form, allowing for powerful recommendation engines and systems of automated analyses.In this thesis, we consider how end-user agency might be enhanced and maintained through the design of tools that support these domain-specific languages, as well as through the study of the design of the languages themselves.In support of this goal, we conducted four interconnected projects which variously study how JSON-based DSLs are designed, how abstraction can be integrated into those languages, how interfaces can be designed to specifically facilitate their manipulation, as well as how those programs might be automatically validated.Through these projects, we demonstrate that giving primacy to these textual interfaces as design elements can be valuable for end users.We find that this style of interventions are useful for helping end users learn, use, and re-use programs written in these languages.We primarily consider languages focused on data visualization tasks, as there has been substantial work in the visualization research community on this form of interface—although the lessons learned could be applied to any relevant domain.

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Section: Discussionmentioning

confidence: 99%

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

McNutt¹

2023

Preprint

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“…For example, gg-plot2 [53] is a charting library in R based on visual encodings. Vega-Lite [44] and its Python-wrapper Altair [49] extend the traditional grammar of graphics design with rules for layered and multi-view displays, as well as interactions, and Animated Vega-Lite [63] further extends it to support animations. These grammars hide low-level implementation details and are concise.…”

Section: Related Workmentioning

confidence: 99%

Data Formulator: AI-powered Concept-driven Visualization Authoring

Wang,

Thompson,

Lee

2023

IEEE Trans. Visual. Comput. Graphics

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With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a new visualization paradigm, concept binding, that separates high-level visualization intents and low-level data transformation steps, leveraging an AI agent. We realize this paradigm in Data Formulator, an interactive visualization authoring tool. With Data Formulator, authors first define data concepts they plan to visualize using natural languages or examples, and then bind them to visual channels. Data Formulator then dispatches its AI-agent to automatically transform the input data to surface these concepts and generate desired visualizations. When presenting the results (transformed table and output visualizations) from the AI agent, Data Formulator provides feedback to help authors inspect and understand them. A user study with 10 participants shows that participants could learn and use Data Formulator to create visualizations that involve challenging data transformations, and presents interesting future research directions.

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Emergence of Omicron FN.1 a descendent of BQ.1.1 in Botswana

Choga,

Gustani-Buss,

Tegally

et al. 2024

Virus Evolution

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Botswana, like the rest of the world, has been significantly impacted by SARS-CoV-2. In December 2022, we detected a monophyletic cluster of genomes comprising a sublineage of the Omicron variant of concern (VOC) designated as B.1.1.529.5.3.1.1.1.1.1.1.74.1 (alias FN.1, clade 22E). These genomes were sourced from both epidemiologically linked and unlinked samples collected in three close locations within the district of Greater Gaborone. In this study, we assessed the worldwide prevalence of the FN.1 lineage, evaluated its mutational profile, and conducted a phylogeographic analysis to reveal its global dispersal dynamics. Among approximately 16 million publicly available SARS-CoV-2 sequences generated by September 30, 2023, only 87 were of the FN.1 lineage, including 22 from Botswana, 6 from South Africa, and 59 from the United Kingdom. The estimated time to the most recent common ancestor (tMRCA) of the 87 FN.1 sequences was October 22, 2022 (95% highest posterior density (HPD): September 02, 2022 - November 24, 2022), with the earliest of the 22 Botswana sequences having been sampled on December 7, 2022. Discrete trait reconstruction of FN.1 identified Botswana as the most probable place of origin. The FN.1 lineage is derived from the BQ.1.1 lineage and carries two missense variants in the Spike protein, S:K182E in NTD and S:T478R in RDB. Among the over 90 SARS-CoV-2 lineages circulating in Botswana between September 2020 and July 2023, FN.1 was most closely related to BQ.1.1.74 based on maximum likelihood phylogenetic inference, differing only by the S:K182E mutation found in FN.1. Given the early detection of numerous novel variants from Botswana and its neighboring countries, our study underscores the necessity of continuous surveillance to monitor the emergence of potential VOCs, integrating molecular and spatial data to identify dissemination patterns enhancing preparedness efforts.

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Animated Vega-Lite: Unifying Animation with a Grammar of Interactive Graphics

Cited by 16 publications

References 39 publications

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

Data Formulator: AI-powered Concept-driven Visualization Authoring

Emergence of Omicron FN.1 a descendent of BQ.1.1 in Botswana

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