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DIVI deconstructs SVG charts to infer semantic components, reconstruct scales and encodings, and decouple interaction logic from chart specification. It enables linking and composition across tools and chart types without prior interaction specification. A taxonomy formalizes standard interactions by chart element, interaction type, and input event, demonstrated via a usability study with 13 participants.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":30,"@type":76,"position":81},"https://docshare.wps.com/document/technology/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/divi-dynamically-interactive-visualization/657598/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/divi-dynamically-interactive-visualization/657598.png","ImageObject",300,407,{"name":92,"@type":93},"CatatanPagi","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-10-26",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is DIVI (Dynamically Interactive Visualization)?","Question",{"text":112,"@type":113},"DIVI is a method for orchestrating interactions within and across static visualizations. It infers chart semantics from SVG at runtime and coordinates user input across linked views.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does DIVI enable interaction without prior specification?",{"text":117,"@type":113},"DIVI deconstructs rendered SVG charts to infer semantic components, reconstructs scales and encodings, and then enumerates candidate data transformations for linking. This supports dynamic interaction without requiring complex hand-authored interaction logic.",{"name":119,"@type":110,"acceptedAnswer":120},"What role does the DIVI interaction taxonomy play?",{"text":121,"@type":113},"The taxonomy formalizes standard interactions by target chart element, interaction type, and input event. It also helps generate the metadata needed to perform interactions and disambiguate similar gestures (e.g., brushing vs. panning).","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},657598,1793073925,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962090894170,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","© 2023 IEEE. This is the author’s version of the article that has been published in IEEE Transactions on Visualization and Computer Graphics. The final version of this record is available at: 10.1109/TVCG.2023.3327172  \nDIVI: Dynamically Interactive Visualization  \nLuke S. Snyder  and Jeffrey Heer   \nFig. 1: Automatic multi-view, cross-tool interactions with DIVI. Dynamically interactive charts of Seattle weather data, from left to right: Matplotlib bar chart (weather vs. sum(precip)), ggplot2 scatter plot (temp_max vs. precip), and Excel scatter plot (date vs. temp_max) . DIVI automatically deconstructs charts to identify semantic components and coordinate user input. Here DIVI links temp_max and weather between scatter plots, and also leverages the source dataset to infer bar chart aggregation of sum(precip) over weather. Interactions are linked: the user brushes an area in the ggplot2 scatter plot with low temp_max and high precip, re-aggregating the bar chart and propagating the selection to the Excel scatter plot to indicate seasonal wintry periods.  \nAbstract—Dynamically Interactive Visualization (DIVI) is a novel approach for orchestrating interactions within and across static visualizations. DIVI deconstructs Scalable Vector Graphics charts at runtime to infer content and coordinate user input, decoupling interaction from specification logic. This decoupling allows interactions to extend and compose freely across different tools, chart types, and analysis goals. DIVI exploits positional relations of marks to detect chart components such as axes and legends, reconstruct scales and view encodings, and infer data fields. DIVI then enumerates candidate transformations across inferred data to perform linking between views. To support dynamic interaction without prior specification, we introduce a taxonomy that formalizes the space of standard interactions by chart element, interaction type, and input event. We demonstrate DIVI’s usefulness for rapid data exploration and analysis through a usability study with 13 participants and a diverse gallery of dynamically interactive visualizations, including single chart, multi-view, and cross-tool configurations.  \nIndex Terms—Interaction, Visualization Tools, Charts, SVG, Exploratory Data Analysis  \n1 INTRODUCTION  \nA variety of people including data analysts, journalists, and teachers use visualizations to explore, analyze, and communicate data. Though a range of tools support visualization creation, authoring interactive visualizations is notably difficult. Visualization developers may implement interactions by modifying visual encodings using low-level event handlers (as in D3 [3]) or declarative selection specifications (as in Vega-Lite [31]) . Graphical tools such as Lyra 2 [40] support custom interaction design without writing textual code, while libraries such as ggplot2 [37] and Matplotlib [21] support only static plots.  \nA central concern is that interactions are tightly coupled with chart specification logic. For instance, to select or zoom within a D3 scatter plot, one must manipulate the underlying Document Object Model (DOM) representation, while the same interactions in Vega-Lite instead require declarative specifiers. These interactions require increasingly complex modifications and state handling for linked charts. As a result, interaction reuse and flexibility is limited across different tools and chart configurations needed for rapid exploratory analysis. Evolving user preferences, data sources, and analysis goals may additionally bring alternative unforeseen interaction needs.  \nInformed by discussions with data analysts, we present Dynamically Interactive Visualization (DIVI), a novel approach for automatically orchestrating interactions with static visualizations. DIVI contributesa three-part model to enable dynamic interaction (Fig. 2): (1) deconstruct Scalable Vector Graphics (SVG) to automatically infer chart  \n• Luke S. Snyder and Jeffrey Heer are with the","cbCailKUuHloQ6HZ","https://ap.wps.com/l/cbCailKUuHloQ6HZ","pdf",4682477,11,"English","# Introduction\n## Problem: interaction coupling across tools\n## DIVI approach: SVG deconstruction and decoupled interaction logic\n## Interaction taxonomy and supported linking\n## Evaluation approach and usability study","[{\"question\":\"What is DIVI (Dynamically Interactive Visualization)?\",\"answer\":\"DIVI is a method for orchestrating interactions within and across static visualizations. It infers chart semantics from SVG at runtime and coordinates user input across linked views.\"},{\"question\":\"How does DIVI enable interaction without prior specification?\",\"answer\":\"DIVI deconstructs rendered SVG charts to infer semantic components, reconstructs scales and encodings, and then enumerates candidate data transformations for linking. This supports dynamic interaction without requiring complex hand-authored interaction logic.\"},{\"question\":\"What role does the DIVI interaction taxonomy play?\",\"answer\":\"The taxonomy formalizes standard interactions by target chart element, interaction type, and input event. It also helps generate the metadata needed to perform interactions and disambiguate similar gestures (e.g., brushing vs. panning).\"}]","DIVI: Dynamically Interactive Visualization | PDF",1792984339,28]