{"id":3015,"date":"2010-02-22T07:35:53","date_gmt":"2010-02-22T15:35:53","guid":{"rendered":"http:\/\/palblog.fxpal.com\/?p=3015"},"modified":"2010-02-21T21:59:14","modified_gmt":"2010-02-22T05:59:14","slug":"glossy-pictures-and-diagrams","status":"publish","type":"post","link":"https:\/\/blog.fxpal.net\/?p=3015","title":{"rendered":"Glossy pictures and diagrams"},"content":{"rendered":"<p><a href=\"http:\/\/www.neoformix.com\/Projects\/TwitterVenn\/view.php?q=valentine,love,hate\"><img decoding=\"async\" loading=\"lazy\" class=\"alignright size-full wp-image-3017\" title=\"Valentine, love, hate: Twitter Venn\" src=\"http:\/\/palblog.fxpal.com\/wp-content\/uploads\/2010\/02\/twitter-venn1.bmp\" alt=\"Valentine, love, hate: Twitter Venn\" width=\"138\" height=\"120\" \/><\/a>In the spirit of <a title=\"Many Eyes | IBM\" href=\"http:\/\/manyeyes.alphaworks.ibm.com\/manyeyes\/\" target=\"_blank\">Many  Eyes<\/a>, <a title=\"Welcome to by Weblog | Neoformix\" href=\"http:\/\/neoformix.com\/2006\/WelcomeToMyWeblog.html\" target=\"_blank\">Jeff Clark<\/a> has been developing <a title=\"Discovering and Illustrating Patterns in Data | neoformix.com\" href=\"http:\/\/neoformix.com\/\" target=\"_blank\">visualizations<\/a> of various kinds, including those of various Twitter collections. For example, his <a title=\"Twitter Venn | Neoformix\" href=\"http:\/\/www.neoformix.com\/Projects\/TwitterVenn\/view.php\" target=\"_blank\">Twitter Venn<\/a> diagram looks at intersections of tweets with three user-specified terms to help understand something about the way different concepts co-occur. Other visualizations look at word distributions associated with pairs of terms, and term use timlines.<\/p>\n<p>The graphs are pretty and, perhaps, informative. His goal is to visualize complex data that don&#8217;t lend themselves to standard bar and pie charts. When these visualizations are effective, they can reveal insight that textual representations fail to convey, but the trick is to understand what is effective when. <a title=\"The Work of Edward Tufte and Graphics Press\" href=\"http:\/\/www.edwardtufte.com\/tufte\/index\" target=\"_blank\">Tufte<\/a>&#8216;s design guidelines are a start, but one based on a rather static notion of data visualization. Apparently <a title=\"Jacques Bertin | Wikipedia\" href=\"http:\/\/en.wikipedia.org\/wiki\/Jacques_Bertin\" target=\"_blank\">Bertin<\/a> was more attuned to <a title=\"Can Edward Tufte Do Business Charts? | ExcelCharts.com\" href=\"http:\/\/www.excelcharts.com\/blog\/can-edward-tufte-do-business-charts\/\" target=\"_blank\">interaction<\/a>, but was still trapped in a static medium.<\/p>\n<p><!--more--><\/p>\n<p>There are two basic challenges to applying these techniques: deciding which data to visualize, and deciding how to visualize them. The twitter examples suggest to me the possibility of using these kinds of visualizations to support exploratory search, but that shouldn&#8217;t surprise those familiar with <a title=\"Golovchinsky, G. (1997) What the query told the link: the integration of hypertext and information retrieval. In Proc. HYPERTEXT '97. ACM, New York, NY, 67-74. \" href=\"http:\/\/doi.acm.org\/10.1145\/267437.267445\" target=\"_blank\">VOIR<\/a>. If we give up the notion of treating a search engine as a black box that transmogrifies bags of words into ranked lists of documents, but insist on having it &#8220;show its work,&#8221; we then gain access to lots of fodder for visual exploration. The includes content such as related terms, facets, etc., and behavioral information that reflects what the searcher (or searchers) have done recently in pursuit of the evolving information needs.<\/p>\n<p>How to display such data is a much more open-ended challenge. We can certainly start with some canned visualizations, but it would be interesting to think about more data-driven approaches to reveal hidden patterns. We (see <a title=\"K. Reichenberger, T. Kamps, G. Golovchinsky,  &quot;Towards a generative theory of diagram design,&quot; ieee_infovis,  pp.11, 1995 IEEE Symposium on Information Visualization (InfoVis '95),  1995\" href=\"http:\/\/www.computer.org\/portal\/web\/csdl\/doi\/10.1109\/INFVIS.1995.528681\" target=\"_blank\">here<\/a> and\u00a0 <a title=\" Golovchinsky, G., Kamps, T., and Reichenberger, K. (1995)  Subverting Structure: Data-driven Diagram Generation. Visualization '95  (Atlanta GA, Oct-Nov 1995), IEEE Computer Society Press, 217-223.\" href=\"http:\/\/portal.acm.org\/citation.cfm?id=833874\">here<\/a>) and others (e.g., <a title=\"Chuah, M. C. and Roth, S. F. (1996) On the semantics of interactive visualizations. In Proc. INFOVIS '96\" href=\"http:\/\/portal.acm.org\/citation.cfm?id=857187.857620\" target=\"_blank\">here<\/a> and <a title=\"Roth, S. F., Chuah, M. C., Kerpedjiev, S., Kolojejchick, J. A., and Lucas, P. (1997) Toward an information visualization workspace: combining multiple=\">here<\/a>) tried this in the mid-90s on a small scale, but it would be interesting to revisit this topic in the context of modern data sets and computational capabilities. The goal I have in mind is not just graphic representations of single quantities related to information seeking (e.g.,\u00a0 <a title=\"The Health Tweeder | Pixels&amp;Pills\" href=\"http:\/\/www.pixelsandpills.com\/tweeder\/\" target=\"_blank\">Tweeder<\/a>) or overviews of collections (e.g., <a title=\"InfoCrystal by Anselm Spoerri | Rutgers University\" href=\"http:\/\/comminfo.rutgers.edu\/%7Easpoerri\/InfoCrystal\/InfoCrystal.htm\" target=\"_blank\">InfoCrystal<\/a>) but actually synthesizing interactive visualizations of rich, multi-dimensional data that was either retrieved in an information exploration session, or that characterizes users&#8217; behavior while engaged in such activity. Both kinds of visualizations should help users understand and reflect on the complex activities characteristic of HCIR.<\/p>\n<p>We&#8217;ve got a long way to go toward being as facile with graphical means of conveying complex information as we are with textual means, but it is heartening to see efforts such as Jeff Clark&#8217;s in this direction.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the spirit of Many Eyes, Jeff Clark has been developing visualizations of various kinds, including those of various Twitter collections. For example, his Twitter Venn diagram looks at intersections of tweets with three user-specified terms to help understand something about the way different concepts co-occur. Other visualizations look at word distributions associated with pairs [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[24,61],"tags":[94],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=\/wp\/v2\/posts\/3015"}],"collection":[{"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3015"}],"version-history":[{"count":10,"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=\/wp\/v2\/posts\/3015\/revisions"}],"predecessor-version":[{"id":3027,"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=\/wp\/v2\/posts\/3015\/revisions\/3027"}],"wp:attachment":[{"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3015"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3015"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.fxpal.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3015"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}