DataVizard: Recommending Visual Presentations for Structured Data
Rema Ananthanarayanan, Pranay Kr. Lohia, Srikanta Bedathur

TL;DR
DataVizard is an automated system that recommends suitable visualizations for structured data, reducing manual effort and improving accuracy in selecting visual representations for query results and web tables.
Contribution
The paper introduces DataVizard, a novel system that automatically suggests appropriate visualizations for structured data, streamlining the visualization selection process.
Findings
High accuracy in visualization recommendations on real-world data.
Effective in both SQL query results and web table scenarios.
Positive user feedback on visualization relevance.
Abstract
Selecting the appropriate visual presentation of the data such that it preserves the semantics of the underlying data and at the same time provides an intuitive summary of the data is an important, often the final step of data analytics. Unfortunately, this is also a step involving significant human effort starting from selection of groups of columns in the structured results from analytics stages, to the selection of right visualization by experimenting with various alternatives. In this paper, we describe our \emph{DataVizard} system aimed at reducing this overhead by automatically recommending the most appropriate visual presentation for the structured result. Specifically, we consider the following two scenarios: first, when one needs to visualize the results of a structured query such as SQL; and the second, when one has acquired a data table with an associated short description…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Visualization and Analytics · Advanced Text Analysis Techniques · Video Analysis and Summarization
