Metadata
Title
Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations
Category
general
UUID
1b60e4c2321c453c93fe5c3b357bdcac
Source URL
https://idl.uw.edu/papers/voyager
Parent URL
https://news.cs.washington.edu/
Crawl Time
2026-03-11T01:48:21+00:00
Rendered Raw Markdown

Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations

Source: https://idl.uw.edu/papers/voyager Parent: https://news.cs.washington.edu/

Kanit Wongsuphasawat, Dominik Moritz, Anushka Anand, Jock Mackinlay, Bill Howe, Jeffrey Heer. IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis), 2016

Kanit Wongsuphasawat, Dominik Moritz, Anushka Anand, Jock Mackinlay, Bill Howe, Jeffrey Heer

IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis), 2016

Voyager: a recommendation-powered visualization browser. The schema panel (left) lists data variables selectable by users. The main gallery (right) presents suggested visualizations of different variable subsets and transformations.

Materials

PDF | Video | Software | Application

Abstract

General visualization tools typically require manual specification of views: analysts must select data variables and then choose which transformations and visual encodings to apply. These decisions often involve both domain and visualization design expertise, and may impose a tedious specification process that impedes exploration. In this paper, we seek to complement manual chart construction with interactive navigation of a gallery of automatically-generated visualizations. We contribute Voyager, a mixed-initiative system that supports faceted browsing of recommended charts chosen according to statistical and perceptual measures. We describe Voyager’s architecture, motivating design principles, and methods for generating and interacting with visualization recommendations. In a study comparing Voyager to a manual visualization specification tool, we find that Voyager facilitates exploration of previously unseen data and leads to increased data variable coverage. We then distill design implications for visualization tools, in particular the need to balance rapid exploration and targeted question-answering.

BibTeX

@article{2016-voyager,
  title = {Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations},
  author = {Wongsuphasawat, Kanit AND Moritz, Dominik AND Anand, Anushka AND Mackinlay, Jock AND Howe, Bill AND Heer, Jeffrey},
  journal = {IEEE Trans. Visualization \& Comp. Graphics (Proc. InfoVis)},
  year = {2016},
  url = {https://idl.uw.edu/papers/voyager},
  doi = {10.1109/TVCG.2015.2467191}
}

{"status":200,"statusText":"","headers":{},"body":"[\n {\n \"fullName\": \"Proc. ACM Human Factors in Computing Systems (CHI)\",\n \"nickname\": \"CHI\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics (Proc. VIS)\",\n \"nickname\": \"VIS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Computer Graphics Forum (Proc. EuroVis)\",\n \"nickname\": \"EuroVis\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. EuroVis Short Papers\",\n \"nickname\": \"EuroVis-Short\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. IEEE VIS Short Papers\",\n \"nickname\": \"VIS-Short\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM User Interface Software & Technology (UIST)\",\n \"nickname\": \"UIST\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM Computer-Supported Cooperative Work (CSCW)\",\n \"nickname\": \"CSCW\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM Intelligent User Interfaces\",\n \"nickname\": \"IUI\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"ACM Trans. on Computer-Human Interaction\",\n \"nickname\": \"ACM TOCHI\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Advanced Visual Interfaces\",\n \"nickname\": \"AVI\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Conference on Innovative Data Systems Research (CIDR)\",\n \"nickname\": \"CIDR\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Very Large Database Endowment (PVLDB)\",\n \"nickname\": \"PVLDB\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Empirical Methods in Natural Language Processing\",\n \"nickname\": \"EMNLP\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. NAACL-HLT\",\n \"nickname\": \"NAACL-HLT\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. International Conference on Weblogs and Social Media (ICWSM)\",\n \"nickname\": \"ICWSM\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis)\",\n \"nickname\": \"InfoVis\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Beautiful Data\",\n \"nickname\": \"Beautiful Data\",\n \"venueType\": \"book\"\n },\n {\n \"fullName\": \"Information Visualization Journal\",\n \"nickname\": \"IV Journal\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. IEEE Visual Analytics Science & Technology (VAST)\",\n \"nickname\": \"VAST\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Cortex\",\n \"nickname\": \"Cortex\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Hawaii International Conference on Systems Sciences (HICSS)\",\n \"nickname\": \"HICSS\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. IEEE Information Visualization (InfoVis)\",\n \"nickname\": \"InfoVis (Pre-TVCG)\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Ubiquitous Computing\",\n \"nickname\": \"UbiComp\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. WEBKDD Workshop\",\n \"nickname\": \"WEBKDD\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"ACM Trans. on Information Systems\",\n \"nickname\": \"ACM TOIS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Communications of the ACM\",\n \"nickname\": \"CACM\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Workshop on Social Network Mining & Analysis, ACM KDD\",\n \"nickname\": \"SNAKDD\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. Social Visualization Workshop, ACM CHI\",\n \"nickname\": \"CHI Social Vis\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. AVI Workshop on Invisible & Transparent Interfaces\",\n \"nickname\": \"AVI ITI\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. Color Imaging Conference\",\n \"nickname\": \"Color Imaging Conf.\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Workshop on Applications for Topic Models, NIPS\",\n \"nickname\": \"NIPS Topic Model Ws\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. Mining Software Repositories\",\n \"nickname\": \"MSR\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Journal of Animal Ecology\",\n \"nickname\": \"J Anim Eco\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"J Am Med Inform Assoc\",\n \"nickname\": \"JAMIA\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. International Conference on Machine Learning (ICML)\",\n \"nickname\": \"ICML\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Computer Graphics and Applications\",\n \"nickname\": \"CG&A\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. IEEE Biological Data Visualization (BioVis)\",\n \"nickname\": \"BioVis\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Poetics\",\n \"nickname\": \"Poetics\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. ACM Web Search and Data Mining (WSDM)\",\n \"nickname\": \"WSDM\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. User Modeling and User-Adapted Interaction (UMUAI)\",\n \"nickname\": \"UMUAI\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Workshop on Eye Tracking and Visualization (ETVIS)\",\n \"nickname\": \"ETVIS\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Trends in Ecology & Evolution\",\n \"nickname\": \"TREE\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"PLOS ONE\",\n \"nickname\": \"PLOS ONE\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. ACM SIGMOD Human-in-the-Loop Data Analysis (HILDA)\",\n \"nickname\": \"HILDA\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics (Proc. VAST)\",\n \"nickname\": \"VAST-TVCG\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Workshop on Dealing with Cognitive Biases in Visualisations (DECISIVe), IEEE VIS\",\n \"nickname\": \"DECISIVe\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"arXiv\",\n \"nickname\": \"arXiv\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"The Journal of Open Source Software\",\n \"nickname\": \"JOSS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proceedings of the National Academy of Sciences\",\n \"nickname\": \"PNAS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Association for Computational Linguistics (ACL)\",\n \"nickname\": \"ACL\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Distill\",\n \"nickname\": \"Distill\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Harvard Data Science Review\",\n \"nickname\": \"HDSR\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Organizational Behavior and Human Decision Processes\",\n \"nickname\": \"OBHDP\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"EPJ Data Science\",\n \"nickname\": \"EPJ-DS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. IEEE Symposium on Visual Languages and Human Centric Computing (VL/HCC)\",\n \"nickname\": \"VL/HCC\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM Management of Data (SIGMOD)\",\n \"nickname\": \"SIGMOD\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Companion of ACM Management of Data (SIGMOD)\",\n \"nickname\": \"SIGMOD-Demo\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics\",\n \"nickname\": \"TVCG\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. ACM Creativity & Cognition\",\n \"nickname\": \"C&C\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Workshop on Intelligent and Interactive Writing Assistants (In2Writing)\",\n \"nickname\": \"In2Writing\",\n \"venueType\": \"workshop\"\n }\n]\n"} {"status":200,"statusText":"","headers":{},"body":"{\n \"title\": \"Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations\",\n \"year\": 2016,\n \"start_page\": null,\n \"end_page\": null,\n \"volume\": null,\n \"issue\": null,\n \"editors\": \"\",\n \"publisher\": \"\",\n \"location\": \"\",\n \"pdf\": \"https://idl.cs.washington.edu/files/2015-Voyager-InfoVis.pdf\",\n \"abstract\": \"General visualization tools typically require manual specification of views: analysts must select data variables and then choose which transformations and visual encodings to apply. These decisions often involve both domain and visualization design expertise, and may impose a tedious specification process that impedes exploration. In this paper, we seek to complement manual chart construction with interactive navigation of a gallery of automatically-generated visualizations. We contribute Voyager, a mixed-initiative system that supports faceted browsing of recommended charts chosen according to statistical and perceptual measures. We describe Voyager’s architecture, motivating design principles, and methods for generating and interacting with visualization recommendations. In a study comparing Voyager to a manual visualization specification tool, we find that Voyager facilitates exploration of previously unseen data and leads to increased data variable coverage. We then distill design implications for visualization tools, in particular the need to balance rapid exploration and targeted question-answering.\",\n \"thumbnail\": \"images/thumbs/voyager.png\",\n \"figure\": \"images/figures/voyager.png\",\n \"caption\": \"Voyager: a recommendation-powered visualization browser. The schema panel (left) lists data variables selectable by users. The main gallery (right) presents suggested visualizations of different variable subsets and transformations.\",\n \"web_name\": \"voyager\",\n \"visible\": true,\n \"mod_date\": \"2015-08-03\",\n \"note\": null,\n \"pub_date\": \"2016-01-03\",\n \"venue\": \"InfoVis\",\n \"authors\": [\n {\n \"first_name\": \"Kanit\",\n \"last_name\": \"Wongsuphasawat\",\n \"url\": \"https://kanitw.github.io/\"\n },\n {\n \"first_name\": \"Dominik\",\n \"last_name\": \"Moritz\",\n \"url\": \"http://domoritz.de/\"\n },\n {\n \"first_name\": \"Anushka\",\n \"last_name\": \"Anand\"\n },\n {\n \"first_name\": \"Jock\",\n \"last_name\": \"Mackinlay\",\n \"url\": \"https://research.tableau.com/user/jock-mackinlay\"\n },\n {\n \"first_name\": \"Bill\",\n \"last_name\": \"Howe\",\n \"url\": \"https://faculty.washington.edu/billhowe/\"\n },\n {\n \"first_name\": \"Jeffrey\",\n \"last_name\": \"Heer\",\n \"url\": \"http://homes.cs.washington.edu/~jheer/\"\n }\n ],\n \"materials\": [\n {\n \"name\": \"Video\",\n \"link\": \"http://vimeo.com/135417594\"\n },\n {\n \"name\": \"Software\",\n \"link\": \"https://vega.github.io/\"\n },\n {\n \"name\": \"Application\",\n \"link\": \"https://vega.github.io/voyager/\"\n }\n ],\n \"tags\": [\n \"recommendation\"\n ],\n \"doi\": \"10.1109/TVCG.2015.2467191\"\n}"}

{ __sveltekit_17copn9 = { base: new URL("..", location).pathname.slice(0, -1), assets: "/uwdata.github.io" }; const element = document.currentScript.parentElement; const data = [null,null]; Promise.all([ import("../_app/immutable/entry/start.CZdZnu7S.js"), import("../_app/immutable/entry/app.qRA-U4ZQ.js") ]).then(([kit, app]) => { kit.start(app, element, { node_ids: [0, 7], data, form: null, error: null }); }); }