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| In the curent issue of the ''IEEE Computer Graphics and Applications'' Journal, [[Chen, Chaomei|Chaomei Chen]] points out the '''Top 10 Unsolved Information Visualization Problems''' [Chen, 2005] (article available at http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=31454&arnumber=1463074&count=14&index=3, requires IEEE subscription). | | In the curent issue of the ''IEEE Computer Graphics and Applications'' Journal, [[Chen, Chaomei|Chaomei Chen]] points out the '''Top 10 Unsolved Information Visualization Problems''' [Chen, 2005] (article available at http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=31454 |
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| The article itself is a revised and extended version of the top unresolved problems pointed out at a panel discussion at IEEE Visualization 2004 conference.
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| The Top 10 Unresolved Problems identified by [[Chen, Chaomei|C. Chen]] are:
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| #'''Usability'''<br>too less usability studies and empirical evaluations are conducted; new evaluative methodologies are needed;
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| #'''Understanding elementary perceptual–cognitive tasks'''<br>the general understanding of elementary perceptual-cognitive tasks must be substantially revised and updated in the context of information visualization; empirical evidence has to be gathered;
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| #'''Prior knowledge'''<br>information visualization and its users must have a common ground; users need two types of prior knowledge: ''knowledge of how to operate the device'' & ''domain knowledge of how to interpret the content''; level of necessary prior knowledge has to be determined;
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| #'''Education and training'''<br>''internally:'' share various principles and skills of visual communication and semiotics; consolidation of the field's theoretical foundations<br>''externally:'' need to show the value of information visualization to potential beneficiaries outside the field; need for compelling showcase examples, widely accessible tutorials for general audiences, raising the awareness of inormation visualization's potential;
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| #'''Intrinsic quality measures'''<br>need to establish intrinsic quality metrics;
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| #'''Scalability'''<br>large amounts of data; parallel computing; high-performance techniques;
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| #'''Aesthetics'''<br>understanding of how insights and aesthetics interact; insightful and visually appealing information visualization;
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| #'''Paradigm shift from structures to dynamics'''<br>shift the structure-centric paradigm to the visualization of dynamic properties of underlying phenomena;
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| #'''Causality, visual inference, and predictions'''<br>InfoVis as a powerful medium for finding causality, forming hypotheses, and assessing available evidence; complex analysis algorithms needed; features that facilitate users in finding what-ifs and test their hypotheses should be provided;
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| #'''Knowledge domain visualization'''<br>information vs. knowledge (values established by social construction process); conveying information structures with added values (knowledge); show amounts of information that are beyond the capacity of textual display;
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| == References ==
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| *[Chen, 2005]: Chen, C. [http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=31454&arnumber=1463074&count=14&index=3 Top 10 Unsolved Information Visualization Problems], IEEE Computer Graphics and Applications, 25(4):12-16, July-Aug. 2005.
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| [[Category:News]][[Category:2005/07]]
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