Encouraging coupled views for visualization exploration

Scientific visualization, especially visualization exploration, enables information to be investigated and better understood. Exploration enables hands-on experimentation with the displayed visualizations and the underlying data. Most exploration techniques, by their nature, generate multiple realizations and many data instances. Thus, to best understand the information in coincident views, the manipulation information within one view may be 'directed' to other related views. These multiple views may be described as being closely coupled. Within this paper we advocate the use of coupled views for scientific visualization exploration. We describe, some key concepts of coupled views for visualization exploration and present how to encourage their use. The key concepts include: the scope of the correlation (between two specific views or many realizations), who initiates the correlation (whether the user or the system) and issues about 'what is correlated' (objects with a view, or the whole viewport).

[1]  Michael Stonebraker,et al.  Tioga: A database-oriented visualization tool , 1993, Proceedings Visualization '93.

[2]  Allan S. Jacobson,et al.  LinkWinds: interactive scientific data analysis and visualization , 1994, CACM.

[3]  Wolfgang Felger,et al.  The Visualization Input Pipeline ‐ Enabling Semantic Interaction in Scientific Visualization , 1992, Comput. Graph. Forum.

[4]  Matthew O. Ward,et al.  High Dimensional Brushing for Interactive Exploration of Multivariate Data , 1995, Proceedings Visualization '95.

[5]  Marc Levoy,et al.  Spreadsheets for images , 1994, SIGGRAPH.

[6]  Josie Wernecke,et al.  The inventor mentor - programming object-oriented 3D graphics with Open Inventor, release 2 , 1993 .

[7]  Allan R. Wilks,et al.  Dynamic Graphics for Data Analysis , 1987 .

[8]  J. V. van Wijk,et al.  HyperSlice: visualization of scalar functions of many variables , 1993, VIS '93.

[9]  Andreas Buja,et al.  Interactive data visualization using focusing and linking , 1991, Proceeding Visualization '91.

[10]  Ken Brodlie,et al.  Collaborative visualization , 1997, Proceedings. Visualization '97 (Cat. No. 97CB36155).

[11]  Jeremy Walton.  Data Visualisation with IRIS Explorer — What ' s New ? , 1996 .

[12]  Lloyd Treinish,et al.  An extended data-flow architecture for data analysis and visualization , 1995, COMG.

[13]  Jarke J. van Wijk,et al.  HyperSlice - Visualization of Scalar Functions of Many Variables , 1993, IEEE Visualization.

[14]  Ben Shneiderman,et al.  Advanced graphic user interfaces: elastic and tightly coupled windows , 1996, CSUR.

[15]  Tom Davis,et al.  Opengl programming guide: the official guide to learning opengl , 1993 .

[16]  David H. Laidlaw,et al.  The application visualization system: a computational environment for scientific visualization , 1989, IEEE Computer Graphics and Applications.

[17]  Ken Brodlie,et al.  GRASPARC-A problem solving environment integrating computation and visualization , 1993, Proceedings Visualization '93.

[18]  Jonathan C. Roberts,et al.  On encouraging multiple views for visualization , 1998, Proceedings. 1998 IEEE Conference on Information Visualization. An International Conference on Computer Visualization and Graphics (Cat. No.98TB100246).

[19]  D. Scott Dyer,et al.  A dataflow toolkit for visualization , 1990, IEEE Computer Graphics and Applications.

[20]  Jonathan C. Roberts.  Waltz: an exploratory visualization tool for volume data using multiform abstract displays , 1998, Electronic Imaging.

[21]  Matthew O. Ward,et al.  XmdvTool: integrating multiple methods for visualizing multivariate data , 1994, Proceedings Visualization '94.

[22]  Steve Kubica,et al.  Cantata: visual programming environment for the Khoros system , 1995, COMG.

[23]  Gudrun Klinker.  An environment for telecollaborative data exploration , 1993, Proceedings Visualization '93.