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Visualizating the Non-Visual: Spatial Analysis and Interaction with Information from Text Documents

Visualizating the Non-Visual: Spatial Analysis and Interaction with Information from Text Documents. J.A. Wise, J.J. Thomas, K. Pennock, D. Lantrip, M. Pottier, A. Schur, and V. Crow. Bongshin Lee April 4, 2001. Paper Outline. Introduction Visualizing text

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Visualizating the Non-Visual: Spatial Analysis and Interaction with Information from Text Documents

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  1. Visualizating the Non-Visual:Spatial Analysis and Interaction with Information from Text Documents J.A. Wise, J.J. Thomas, K. Pennock, D. Lantrip, M. Pottier, A. Schur, and V. Crow Bongshin Lee April 4, 2001

  2. Paper Outline • Introduction • Visualizing text • Visualization transformations: from text to pictures • Examples from the MVAB Project • Conclusions and directions for future research and development CMSC838b Information Visualization

  3. Introduction • Current Visualization approaches • For visualizing mostly structured and/or hierarchical information • Some research in information retrieval • Utilized graph theory or figural display • Information returned is documents in text form • Users still have to read • Causes a severe upper limit • Open Source digital information • Available text overwhelms the traditional reading methods of inspection, sift and synthesis CMSC838b Information Visualization

  4. Visualizing text • True text visualizations • Must represent textual content and meaning without the user having to read it • Result from content abstraction and spatialization of the text document • Use primarily preattentive, parallel processing powers of visual perception • Goal is to spatially transform text information into a new visual representation CMSC838b Information Visualization

  5. Visualization transformations: from text to pictures • Four important technical considerations • Clear definition of text • what comprises text • how it can be distinguished from other symbolic representations • Way to transform raw text into a different visual form • Foundation for meaningful visualization • Suitable mathematical procedures and analytical measures • A database management system CMSC838b Information Visualization

  6. Processing Text • Requirements of text processing engine • Identification and extraction of text features • Frequency-based measures on words • Higher order statistics taken on the words • Semantic in nature • Efficient and flexible representation of documents in terms of these text features • Support for information retrieval and visualization • Pre-process, indexing CMSC838b Information Visualization

  7. Visualizing output from text processing • Representing the document • a vector in high dimensional feature space • Comparisons, filters, and transformations can be applied • Clustering using the normalized document vectors • Projection • Principal Components Analysis • Multi-Dimensional Scaling • Exponential order of complexity • Clustering in the high-dimensional feature space • Visualize the cluster centroids CMSC838b Information Visualization

  8. Managing the representation • Two basic classes of data • Raw text files • Static in nature, Simple in structure • Easy to manage • Visual forms of the text • Extensive and dynamic • Object-Oriented Database • Flexibility of data representation • Power of inheritance • Ease of data access CMSC838b Information Visualization

  9. Interface design for text visualization • Backdrop • Central display resource • Workshop • Grid having resizable windows to hold multiple views • Chronicle • Area where views are placed and linked to form a visual story CMSC838b Information Visualization

  10. Examplesfrom the MVAB Project • MVAB • Multidimensional Visualization and Advanced Browsing Project • Visualization and analysis of textual information • Showcased in SPIRE • SPIRE • Spatial Paradigm for Information Retrieval and Exploration • Starfields and Topographical maps metaphors • Galaxies and Themescapes CMSC838b Information Visualization

  11. Galaxies • Displays cluster and document interrelatedness • 2D scatterplot of ‘docupoints’ • Simple point and click exploration • Sophisticated tools • Facilitate more in-depth analysis • Ex) temporal slicer CMSC838b Information Visualization

  12. Galaxies Screen Shot CMSC838b Information Visualization

  13. ThemeScapes • Abstract, 3D landscapes of information • Convey relevant information about topic or themes without the cognitive load • Spatial relationships reveal the intricate interconnection of thems CMSC838b Information Visualization

  14. ThemScapes - Advantages • Displays much of the complex content of the document database • Utilizes innate human abilities for pattern recognition and spatial reasoning • Communicative invariance across levels of textual scale • Promote analysis CMSC838b Information Visualization

  15. ThemeScapes Screen Shot CMSC838b Information Visualization

  16. Conclusions • Text visualizations can overcome much of the user limitations • Enhanced insight and time savings (35 mins vs 2 weeks) • Creative with the tool • Querying and analytical manipulation come together in a single visualization • Permits a different kinds of querying • Text visualizations will have to access and utilize the cognitive and visual processes CMSC838b Information Visualization

  17. Directions for Future R & D • Visual Data Analysis • Elaborate the visual metaphors • Addition of sensory modalities • Virtual interaction CMSC838b Information Visualization

  18. My Favorite Sentence The bottleneck in the human processing and understanding of information in large amounts of text can be overcome if the text is specialized in a manner that takes advantage of common powers of perception. CMSC838b Information Visualization

  19. Contributions • Explorations of new visualizations • Discussion of the process for mapping Raw Data Document collections into visualizations CMSC838b Information Visualization

  20. Notes on the Reference • Designing Interaction: Psychology at the Human Computer Interaction • Interfaces Issues and Interaction Strategies for Information Retrieval Systems • Clustering and Dimensionality Reduction in SPIRE CMSC838b Information Visualization

  21. Critique – Strengths and Weaknesses • Strengths • Provide natural visual metaphors • Enable the users to see the relationships between documents with minimal required reading • Weaknesses • No validation of some conclusions CMSC838b Information Visualization

  22. What has happened to this topic? • 1996 R&D 100 Award • OCSB • On-line Citation Searching and Browsing in UMD • "ThemeScape" is now a trademarked term of Cartia, Inc. • WebThemeTM • an interactive tool that provides a visual display of the common themes in collections of web-based documents CMSC838b Information Visualization

  23. WebTheme Screen Shot CMSC838b Information Visualization

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