Knowledge precepts for design and evaluation of information visualizations Export

@article{citeulike:623904, abstract = {The design and evaluation of most current information visualization systems descend from an emphasis on a user's ability to "unpack" the representations of data of interest and operate on them independently. Too often, successful decision-making and analysis are more a matter of serendipity and user experience than of intentional design and specific support for such tasks; although humans have considerable abilities in analyzing relationships from data, the utility of visualizations remains relatively variable across users, data sets, and domains. In this paper, we discuss the notion of analytic gaps, which represent obstacles faced by visualizations in facilitating higher-level analytic tasks, such as decision-making and learning. We discuss support for bridging these gaps, propose a framework for the design and evaluation of information visualization systems, and demonstrate its use.}, author = {Amar, R. A. and Stasko, J. T.}, citeulike-article-id = {623904}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1432689}, journal = {Visualization and Computer Graphics, IEEE Transactions on}, keywords = {597b, data, decision-making, geovisualization, index, information, knowledge, methodologies, methods, preception, representation, system, techniques, terms-theory, visualization}, number = {4}, pages = {432--442}, posted-at = {2006-05-11 22:27:36}, priority = {0}, title = {Knowledge precepts for design and evaluation of information visualizations}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1432689}, volume = {11}, year = {2005} }

TY - JOUR ID - citeulike:623904 L3 - citeulike-article-id:623904 N2 - The design and evaluation of most current information visualization systems descend from an emphasis on a user's ability to "unpack" the representations of data of interest and operate on them independently. Too often, successful decision-making and analysis are more a matter of serendipity and user experience than of intentional design and specific support for such tasks; although humans have considerable abilities in analyzing relationships from data, the utility of visualizations remains relatively variable across users, data sets, and domains. In this paper, we discuss the notion of analytic gaps, which represent obstacles faced by visualizations in facilitating higher-level analytic tasks, such as decision-making and learning. We discuss support for bridging these gaps, propose a framework for the design and evaluation of information visualization systems, and demonstrate its use. IS - 4 JF - Visualization and Computer Graphics, IEEE Transactions on EP - 442 TI - Knowledge precepts for design and evaluation of information visualizations VL - 11 SP - 432 KW - 597b KW - data KW - decision-making KW - geovisualization KW - index KW - information KW - knowledge KW - methodologies KW - methods KW - preception KW - representation KW - system KW - techniques KW - terms-theory KW - visualization AU - Amar, RA AU - Stasko, JT PY - 2005/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1432689 ER -