InterAxis : Steering Scatterplot Axes via Observation-Level Interaction

Scatterplots are effective visualization techniques for multidimensional data that use two (or three) axes to visualize data items as a point at its corresponding x and y Cartesian coordinates. Typically, each axis is bound to a single data attribute. Interactive exploration occurs by changing the d...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 22(2016), 1 vom: 10. Jan., Seite 131-40
1. Verfasser: Kim, Hannah (VerfasserIn)
Weitere Verfasser: Choo, Jaegul, Park, Haesun, Endert, Alex
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S.
LEADER 01000naa a22002652 4500
001 NLM252631404
003 DE-627
005 20231224164523.0
007 cr uuu---uuuuu
008 231224s2016 xx |||||o 00| ||eng c
024 7 |a 10.1109/TVCG.2015.2467615  |2 doi 
028 5 2 |a pubmed24n0842.xml 
035 |a (DE-627)NLM252631404 
035 |a (NLM)26357399 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Kim, Hannah  |e verfasserin  |4 aut 
245 1 0 |a InterAxis  |b Steering Scatterplot Axes via Observation-Level Interaction 
264 1 |c 2016 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 05.02.2016 
500 |a Date Revised 04.11.2015 
500 |a published: Print-Electronic 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a Scatterplots are effective visualization techniques for multidimensional data that use two (or three) axes to visualize data items as a point at its corresponding x and y Cartesian coordinates. Typically, each axis is bound to a single data attribute. Interactive exploration occurs by changing the data attributes bound to each of these axes. In the case of using scatterplots to visualize the outputs of dimension reduction techniques, the x and y axes are combinations of the true, high-dimensional data. For these spatializations, the axes present usability challenges in terms of interpretability and interactivity. That is, understanding the axes and interacting with them to make adjustments can be challenging. In this paper, we present InterAxis, a visual analytics technique to properly interpret, define, and change an axis in a user-driven manner. Users are given the ability to define and modify axes by dragging data items to either side of the x or y axes. from which the system computes a linear combination of data attributes and binds it to the axis. Further, users can directly tune the positive and negative contribution to these complex axes by using the visualization of data attributes that correspond to each axis. We describe the details of our technique and demonstrate the intended usage through two scenarios 
650 4 |a Journal Article 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
700 1 |a Choo, Jaegul  |e verfasserin  |4 aut 
700 1 |a Park, Haesun  |e verfasserin  |4 aut 
700 1 |a Endert, Alex  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on visualization and computer graphics  |d 1996  |g 22(2016), 1 vom: 10. Jan., Seite 131-40  |w (DE-627)NLM098269445  |x 1941-0506  |7 nnns 
773 1 8 |g volume:22  |g year:2016  |g number:1  |g day:10  |g month:01  |g pages:131-40 
856 4 0 |u http://dx.doi.org/10.1109/TVCG.2015.2467615  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 22  |j 2016  |e 1  |b 10  |c 01  |h 131-40