Microsoft Research
Computational User Experiences

Faceted Browsing for Scalable Information Exploration

In conjunction with VIBEViz, we are working on new user interfaces that present faceted metadata to make searching and browsing various data sources simpler and more informative. We’re particularly interested in an approach that works over a large range of display sizes, with a diverse collection of data domains, over many different sizes of dataset.


Project Team



FacetLens is a follow-on interface to prior work on FacetMap and PaperLens. FacetLens is an appropriate visualization tool for nearly any item/attribute based dataset expressed as a SQL database. Provided with a description of the types and locations of item metadata, FacetLens dynamically generates SQL queries to probe the data distributions and present them to the user in a data-rich, animated way. The user can  interactively click on values to apply filter criteria, and can use drag/drop operations to explore trends. FacetLens scales up to any size display by revealing progressively more detail as space grows.


FacetLens Video [Small size: .wmv (18.5MB), Large size: .wmv (43.3MB)]


FacetLens: Exposing Trends and Relationships to Support Sensemaking within Faceted Datasets

Bongshin Lee, Greg Smith, George G Robertson, Mary Czerwinski, Desney S Tan

Proceedings of ACM CHI 2009, pp. 1293-1302

FacetMap: A Scalable Search and Browse Visualization

Greg Smith, Mary Czerwinski, Brian Meyers, Daniel Robbins, George Robertson, Desney S Tan

IEEE Transactions on Visualization and Computer Graphics, 12(5), pp. 797-804, 2006

Understanding Research Trends in Conferences using PaperLens

Bongshin Lee, Mary Czerwinski, George Robertson, Benjamin B Bederson

Extended Abstracts of CHI, pp. 1969-1972, 2005

Understanding Eight Years of InfoVis Conferences using PaperLens

Bongshin Lee, Mary Czerwinski, George Robertson, Benjamin B Bederson

Posters Compendium of InfoVis, pp. 53-54, 2004

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