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FacetMap: A scalable search and browse visualization.

Greg Smith1, Mary Czerwinski, Brian Meyers

  • 1Microsoft Research. gregsmi@microsoft.com

IEEE Transactions on Visualization and Computer Graphics
|November 4, 2006
PubMed
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FacetMap offers an interactive visualization for searching personal data stores, improving upon traditional text-based methods. This visual approach uses metadata facets for filtering and displaying results, enhancing data exploration.

Area of Science:

  • Information Science
  • Human-Computer Interaction
  • Data Visualization

Background:

  • Traditional data store searching relies on text-based input and scrollable result lists.
  • Personal information stores contain heterogeneous data and rich metadata, presenting challenges for text-based search.

Purpose of the Study:

  • To introduce FacetMap, an interactive, query-driven visualization tool.
  • To demonstrate FacetMap's generalizability to various metadata-rich data stores.
  • To compare the effectiveness of a visual search approach against traditional text-based methods.

Main Methods:

  • Developed FacetMap, a visualization system employing a visual metaphor for input and output.
  • Utilized metadata facets as interactive filters within the FacetMap interface.

Related Experiment Videos

  • Conducted a user study to evaluate FacetMap against text-oriented search approaches.

    • Main Results:

    • FacetMap provides an alternative to text-based search by using visual metaphors for data exploration.
    • User study results offer insights into the trade-offs between graphical and text-oriented search methods.
    • The effectiveness of FacetMap in handling heterogeneous data and rich metadata was explored.

    Conclusions:

    • Interactive visualizations like FacetMap can enhance the search and browsing of personal information stores.
    • Visual approaches offer potential advantages over traditional text-based methods for complex data.
    • Further research is needed to fully understand the benefits and limitations of visual data exploration tools.