{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,3]],"date-time":"2026-05-03T03:20:35Z","timestamp":1777778435669,"version":"3.51.4"},"reference-count":34,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2004,6,1]],"date-time":"2004-06-01T00:00:00Z","timestamp":1086048000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information Visualization"],"published-print":{"date-parts":[[2004,6]]},"abstract":"<jats:p>Data sets with a large numbers of nominal variables, including some with large number of distinct values, are becoming increasingly common and need to be explored. Unfortunately, most existing visual exploration tools are designed to handle numeric variables only. When importing data sets with nominal values into such visualization tools, most solutions to date are rather simplistic. Often, techniques that map nominal values to numbers do not assign order or spacing among the values in a manner that conveys semantic relationships. Moreover, displays designed for nominal variables usually cannot handle high cardinality variables well. This paper addresses the problem of how to display nominal variables in general-purpose visual exploration tools designed for numeric variables. Specifically, we investigate (1) how to assign order and spacing among the nominal values, and (2) how to reduce the number of distinct values to display. We propose a new technique, called the Distance-Quantification-Classing (DQC) approach, to preprocess nominal variables before being imported into a visual exploration tool. In the Distance Step, we identify a set of independent dimensions that can be used to calculate the distance between nominal values. In the Quantification Step, we use the independent dimensions and the distance information to assign order and spacing among the nominal values. In the Classing Step, we use results from the previous steps to determine which values within the domain of a variable are similar to each other and thus can be grouped together. Each step in the DQC approach can be accomplished by a variety of techniques. We extended the XmdvTool package to incorporate this approach. We evaluated our approach on several data sets using a variety of measures.<\/jats:p>","DOI":"10.1057\/palgrave.ivs.9500072","type":"journal-article","created":{"date-parts":[[2004,7,2]],"date-time":"2004-07-02T05:36:46Z","timestamp":1088746606000},"page":"80-95","source":"Crossref","is-referenced-by-count":52,"title":["Mapping Nominal Values to Numbers for Effective Visualization"],"prefix":"10.1177","volume":"3","author":[{"given":"Geraldine E","family":"Rosario","sequence":"first","affiliation":[{"name":"Computer Science Department, Worcester Polytechnic Institute, Worcester, U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elke A","family":"Rundensteiner","sequence":"additional","affiliation":[{"name":"Computer Science Department, Worcester Polytechnic Institute, Worcester, U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David C","family":"Brown","sequence":"additional","affiliation":[{"name":"Computer Science Department, Worcester Polytechnic Institute, Worcester, U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew O","family":"Ward","sequence":"additional","affiliation":[{"name":"Computer Science Department, Worcester Polytechnic Institute, Worcester, U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiping","family":"Huang","sequence":"additional","affiliation":[{"name":"Computer Science Department, Worcester Polytechnic Institute, Worcester, U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2004,6,1]]},"reference":[{"key":"bibr1-palgrave.ivs.9500072","doi-asserted-by":"crossref","unstructured":"LeBlanc J, Ward M, Wittels N. Exploring n-dimensional database. Proceeding of Visualization1990; 1990; 230\u2013237.","DOI":"10.1109\/VISUAL.1990.146386"},{"key":"bibr2-palgrave.ivs.9500072","first-page":"319","volume-title":"Cognition and Survey Research","author":"Friendly M.","year":"1999"},{"key":"bibr3-palgrave.ivs.9500072","doi-asserted-by":"crossref","unstructured":"Inselberg A, Dimsdale B. Parallel coordinates: a tool for visualizing multidimensional geometry. Proceedings of Visualization 1990, 1990; 361\u2013378.","DOI":"10.1109\/VISUAL.1990.146402"},{"key":"bibr4-palgrave.ivs.9500072","unstructured":"Ma S, Hellerstein JL. Ordering categorical data to improve visualization. In IEEE Information Visualization Symposium Late Breaking Hot Topics, 1999; 15\u201318."},{"key":"bibr5-palgrave.ivs.9500072","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1080\/10618600.1996.10474701","volume":"5","author":"Becker A","year":"1996","journal-title":"Journal of Computational and Statistical Graphics"},{"key":"bibr6-palgrave.ivs.9500072","unstructured":"Xmdv Tool Home Page. 2003. http:\/\/davis.wpi.edu\/\u223cxmdv."},{"key":"bibr7-palgrave.ivs.9500072","volume-title":"Correspondence Analysis in Practice","author":"Greenacre MJ","year":"1993"},{"key":"bibr8-palgrave.ivs.9500072","volume-title":"Applied Multivariate Statistical Analysis","author":"Johnson RA","year":"1988","edition":"2"},{"key":"bibr9-palgrave.ivs.9500072","doi-asserted-by":"crossref","unstructured":"Rosario GE, Rundensteiner EA, Brown DC, Ward MO. Mapping nominal values to numbers for effective visualization. Proceeding of information Visualization, October 2003; 113\u2013120.","DOI":"10.1109\/INFVIS.2003.1249016"},{"key":"bibr10-palgrave.ivs.9500072","first-page":"293","volume-title":"Softstat 1993: Advances in Statistical Software","author":"Riedwyl H","year":"1994"},{"key":"bibr11-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(02)00289-X"},{"key":"bibr12-palgrave.ivs.9500072","unstructured":"Johnson B, Shneiderman B. Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: Proceeding of the Second Conference on Visualization1991. IEEE Computer Society Press: Sliver Spring, MD, 1991; 284\u2013291."},{"key":"bibr13-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1145\/102377.115768"},{"key":"bibr14-palgrave.ivs.9500072","unstructured":"Kolatch E, Weinstein B. Cattrees: dynamic visualization of categorical data using treemaps, 2001. http:\/\/www.cs.umd.edu\/class\/spring2001\/cmsc838\/Project\/Kolatch_Weinstein."},{"key":"bibr15-palgrave.ivs.9500072","first-page":"113","volume":"4","author":"Hofmann UARHG","year":"1996","journal-title":"Journal of Computational and Graphical Statistics"},{"key":"bibr16-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1145\/948449.948460"},{"key":"bibr17-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(02)00290-6"},{"key":"bibr18-palgrave.ivs.9500072","volume-title":"Graphics and Graphic Information-Processing","author":"Bertin J","year":"1982"},{"key":"bibr19-palgrave.ivs.9500072","volume-title":"Semiology of Graphics","author":"Bertin J.","year":"1983"},{"key":"bibr20-palgrave.ivs.9500072","doi-asserted-by":"crossref","unstructured":"Rao R, Card SK. The table lens: merging graphical and symbolic representations in an interactive focus+context visualization for tabular information. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM Press: New York, 1994; 318\u2013322.","DOI":"10.1145\/191666.191776"},{"key":"bibr21-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1145\/502512.502545"},{"key":"bibr22-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1007\/BF02294151"},{"key":"bibr23-palgrave.ivs.9500072","unstructured":"Friendly M. Mosaic displays for loglinear model. Proceedings of the Statistical Graphics Section, ASA, August, 1992; 61\u201368."},{"key":"bibr24-palgrave.ivs.9500072","volume-title":"SPSS Categories 10.0","author":"Meulman J","year":"2000"},{"key":"bibr25-palgrave.ivs.9500072","doi-asserted-by":"crossref","unstructured":"Milanese R, Squire D, Pun T. Correspondence analysis and hierarchical indexing for content-based image retrieval. In: Proceeding of the Third IEEE International Conference on Image Processing, ICIP1996, 1996; 859\u2013862.","DOI":"10.1109\/ICIP.1996.560891"},{"key":"bibr26-palgrave.ivs.9500072","doi-asserted-by":"publisher","DOI":"10.1145\/507533.507538"},{"key":"bibr27-palgrave.ivs.9500072","volume-title":"Data Mining: Concepts and Techniques","author":"Han J","year":"2001"},{"key":"bibr28-palgrave.ivs.9500072","unstructured":"SAS Institute Inc. SAS OnlineDoc Version 8 with PDF Files, 2000."},{"key":"bibr29-palgrave.ivs.9500072","unstructured":"StatSoft Inc. Electronic statistics text book: correspondence analysis, 2002. http:\/\/www.statsoftinc.com\/textbook\/stcoran.html."},{"key":"bibr30-palgrave.ivs.9500072","volume-title":"Theory and Applications of Correspondence Analysis","author":"Greenacre MJ","year":"1984"},{"key":"bibr31-palgrave.ivs.9500072","volume-title":"Categorical Data Analysis","author":"Agresti A.","year":"1990"},{"key":"bibr32-palgrave.ivs.9500072","doi-asserted-by":"crossref","unstructured":"Ankersti M, Berchtold S, Keim DA. Similarity clustering of dimensions for an enhanced visualization of multidimensional data. Proceedings of the IEEE Symposium on Information Visualization, InfoVis1998, 1998; 52\u201360.","DOI":"10.1109\/INFVIS.1998.729559"},{"key":"bibr33-palgrave.ivs.9500072","unstructured":"Blake C, Merz C. UCI repository of machine learning database, 1998. http:\/\/www.ics.uci.edu\/\u223cmlearn\/MLRepository.html."},{"key":"bibr34-palgrave.ivs.9500072","unstructured":"United States Department of Health. Centers for disease control and prevention homepage, 2001. http:\/\/www.cdc.gov\/."}],"container-title":["Information Visualization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1057\/palgrave.ivs.9500072","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1057\/palgrave.ivs.9500072","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:19:30Z","timestamp":1777490370000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1057\/palgrave.ivs.9500072"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,6]]},"references-count":34,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2004,6]]}},"alternative-id":["10.1057\/palgrave.ivs.9500072"],"URL":"https:\/\/doi.org\/10.1057\/palgrave.ivs.9500072","relation":{},"ISSN":["1473-8716","1473-8724"],"issn-type":[{"value":"1473-8716","type":"print"},{"value":"1473-8724","type":"electronic"}],"subject":[],"published":{"date-parts":[[2004,6]]}}}