LEADER 01867oam 2200433zu 450 001 9910141206003321 005 20241212220159.0 010 $a9781467301558 010 $a1467301558 035 $a(CKB)2670000000131670 035 $a(SSID)ssj0000669886 035 $a(PQKBManifestationID)12241835 035 $a(PQKBTitleCode)TC0000669886 035 $a(PQKBWorkID)10715834 035 $a(PQKB)10050846 035 $a(NjHacI)992670000000131670 035 $a(EXLCZ)992670000000131670 100 $a20160829d2011 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$a2011 IEEE Symposium on Large Data Analysis and Visualization 210 31$a[Place of publication not identified]$cIEEE$d2011 215 $a1 online resource (viii, 142 pages) 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9781467301565 311 08$a1467301566 330 $aVisualization of massively large datasets presents two significant problems. First, the dataset must be prepared for visualization, and traditional dataset manipulation methods fail due to lack of temporary storage or memory. The second problem is the presentation of the data in the visual media, particularly real-time visualization of streaming time series data. An ongoing research project addresses both these problems, using data from two national repositories. This work is presented here, with the results of the current effort summarized and future plans, including 3D visualization, outlined. 606 $aInformation visualization 615 0$aInformation visualization. 676 $a001.4226 702 $aIEEE Staff 801 0$bPQKB 906 $aPROCEEDING 912 $a9910141206003321 996 $a2011 IEEE Symposium on Large Data Analysis and Visualization$92529489 997 $aUNINA