Originally created as a research project by Jeff Heer’s Interactive Data Lab (IDL) at the University of Washington, with implementation led by Kanit Wongsuphasawat and Dominik Moritz, Voyager is a visualization browser for exploring the breadth of datasets with ease through automated visualization recommendations. In collaboration with IDL, the Bocoup Data Visualization team helped make Voyager a more performant, accessible, and user-friendly data visualization tool with the help of a Knight Foundation Prototype Grant.
University of Washington Interactive Data Lab
Making data exploration and visual analysis more accessible with Voyager
Data visualization tools that enable custom exploration are a luxury for most practitioners. The tools often come with the burden of expensive license fees and tend to be close-sourced technologies that cannot be extended, customized, or modified in any way by their users.
When the Bocoup Data Visualization Team first saw Jeff Heer present his research group’s work on Voyager, we were struck by the project’s potential to expand the space of visual exploration tools and to bridge the gap between data science and visualization. We collaborated with Jeff Heer’s Interactive Data Lab at the University of Washington on securing grant funding to apply our expertise in designing and developing exploratory visualization tools for the open web to make Voyager an even more robust and accessible tool for new users.
With the mission of encouraging data exploration for all in mind, we focused on improving Voyager to make it a valuable addition to people’s exploratory data analysis. To that end, we decided to focus our time on four impact areas:
Ensuring Speedy Data Exploration
- identified and fixed performance bottlenecks to create an optimal user experience for data-sets of any size by removing UI blocking behaviours and speeding up internal data processing.
Making Custom Dataset Exploration Discoverable
- redesigned the custom data-set loading experience to improve its discoverability and ease of use
- added support for exploring CSV datasets in the tool using a simpler drag-and-drop interface
Improving UX and UI
- conducted user testing to identify opportunities for functionality improvements in visual hierarchy and color scheme to reduce visual clutter and polish the UI
- introduced a new logo for the project
Creating a Great Experience for New Users
- defined learning objectives to describe what first time Voyager users should be able to accomplish with the tool
- developed an initial welcome screen and in-application tutorial to onboard new users based on learning objectives
- designed and implemented a streamlined first-use experience
The audience for Voyager includes everyone who has data they wish to explore visually to better understand it. We want to encourage data exploration for all, especially groups who may avoid data visualization due to its inherent technical barrier to entry. We’re excited to help bring Voyager to the broader data visualization community and public in collaboration with the UW Interactive Data Lab and Knight Foundation.
Through our collaboration, Voyager offers users a faster, more intuitive, and more welcoming experience to explore their data through a gallery of recommended visualizations, ranked by both data properties and perceptual principles. Before our collaboration, Voyager was already a powerful tool: it automatically generated visualizations based on the user’s data, thereby allowing users to visually explore many facets of their data. Now, through our work together, we’ve been able to make it easier for a broader audience to benefit from this open source technology.
The Interactive Data Lab team at the University of Washington has been leading the charge to democratize these tools for practitioners. Among many significant projects, their contributions include Lyra, a powerful interactive environment for visualization design, and Vega, a full declarative visualization grammar suitable for expressive custom interactive visualization design and programmatic generation. We were thrilled with our working together to improve Voyager and bring it to more users.
Some of the speed improvements we implemented will be incorporated into Voyager’s companion tool Polestar, which implements a Tableau-style interface for creating visualizations easily using drag-and-drop interfaces using Open Web technologies.
Read about the other projects funded by this round of the Prototype Fund here.
Read more work from the UW Interactive Data Lab here.
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