Streamlining Visualization Authoring in D3 Through User-Driven Templates

TL;DR

This paper analyzes common D3 visualization implementations to create reusable code templates, aiming to simplify D3 visualization authoring and reduce the learning curve for users.

Contribution

It provides a qualitative analysis of D3 visualizations, identifies common implementation patterns, and offers reusable code templates for eight popular visualization types.

Findings

Five visualization types account for 80% of D3 visualizations

Underlying code structures are similar across different visualization types

Reusable templates can facilitate easier D3 visualization creation

Abstract

D3 is arguably the most popular tool for implementing web based visualizations. Yet D3 has a steep learning curve that may hinder its adoption and continued use. To simplify the process of programming D3 visualizations, we must first understand the space of implementation practices that D3 users engage in. We present a qualitative analysis of 2500 D3 visualizations and their corresponding implementations. We find that 5 visualization types (Bar Charts, Geomaps, Line Charts, Scatterplots, and Force Directed Graphs) account for 80% of D3 visualizations found in our corpus. While implementation styles vary slightly across designs, the underlying code structure for all visualization types remains the same; presenting an opportunity for code reuse. Using our corpus of D3 examples, we synthesize reusable code templates for eight popular D3 visualization types and share them in our open source repository. Based on our results, we discuss design considerations for leveraging users' implementation patterns to reduce visualization design effort through design templates and auto-generated code recommendations.