13 research outputs found
iVoLVER : Interactive Visual Language for Visualization Extraction and Reconstruction
We present the design and implementation of iVoLVER, a tool that allows users to create visualizations without textual programming. iVoLVER is designed to enable flexible acquisition of many types of data (text, colors, shapes, quantities, dates) from multiple source types (bitmap charts, webpages, photographs, SVGs, CSV files) and, within the same canvas, supports transformation of that data through simple widgets to construct interactive animated visuals. Aside from the tool, which is web-based and designed for pen and touch, we contribute the design of the interactive visual language and widgets for extraction, transformation, and representation of data. We demonstrate the flexibility and expressive power of the tool through a set of scenarios, and discuss some of the challenges encountered and how the tool fits within the current infovis tool landscape.Postprin
Combining design and performance in a data visualization management system
Interactive data visualizations have emerged as a prominent way to bring data exploration and analysis capabilities to both technical and non-technical users. Despite their ubiquity and importance across applications, multiple design- and performance-related challenges lurk beneath the visualization creation process. To meet these challenges, application designers either use visualization systems (e.g., Endeca, Tableau, and Splunk) that are tailored to domain-specific analyses, or manually design, implement, and optimize their own solutions. Unfortunately, both approaches typically slow down the creation process. In this paper, we describe the status of our progress towards an end-to-end relational approach in our data visualization management system (DVMS). We introduce DeVIL, a SQL-like language to express static as well as interactive visualizations as database views that combine user inpu
VisAhoi: Towards a Library to Generate and Integrate Visualization Onboarding Using High-level Visualization Grammars
Visualization onboarding supports users in reading, interpreting, and
extracting information from visual data representations. General-purpose
onboarding tools and libraries are applicable for explaining a wide range of
graphical user interfaces but cannot handle specific visualization
requirements. This paper describes a first step towards developing an
onboarding library called VisAhoi, which is easy to integrate, extend,
semi-automate, reuse, and customize. VisAhoi supports the creation of
onboarding elements for different visualization types and datasets. We
demonstrate how to extract and describe onboarding instructions using three
well-known high-level descriptive visualization grammars - Vega-Lite,
Plotly.js, and ECharts. We show the applicability of our library by performing
two usage scenarios that describe the integration of VisAhoi into a VA tool for
the analysis of high-throughput screening (HTS) data and, second, into a
Flourish template to provide an authoring tool for data journalists for a
treemap visualization. We provide a supplementary website that demonstrates the
applicability of VisAhoi to various visualizations, including a bar chart, a
horizon graph, a change matrix or heatmap, a scatterplot, and a treemap
visualization
SeeChart: Enabling Accessible Visualizations Through Interactive Natural Language Interface For People with Visual Impairments
Web-based data visualizations have become very popular for exploring data and
communicating insights. Newspapers, journals, and reports regularly publish
visualizations to tell compelling stories with data. Unfortunately, most
visualizations are inaccessible to readers with visual impairments. For many
charts on the web, there are no accompanying alternative (alt) texts, and even
if such texts exist they do not adequately describe important insights from
charts. To address the problem, we first interviewed 15 blind users to
understand their challenges and requirements for reading data visualizations.
Based on the insights from these interviews, we developed SeeChart, an
interactive tool that automatically deconstructs charts from web pages and then
converts them to accessible visualizations for blind people by enabling them to
hear the chart summary as well as to interact through data points using the
keyboard. Our evaluation with 14 blind participants suggests the efficacy of
SeeChart in understanding key insights from charts and fulfilling their
information needs while reducing their required time and cognitive burden.Comment: 28 pages, 13 figure