W. Aigner, S. Miksch, W. Müller, H. Schumann, and C. Tominski, Visual Methods for Analyzing Time-Oriented Data, IEEE Transactions on Visualization and Computer Graphics, vol.14, issue.1, pp.47-60, 2008.
DOI : 10.1109/TVCG.2007.70415

R. A. Amar, J. Eagan, and J. Stasko, Low-level components of analytic activity in information visualization, p.15, 2005.

M. Amiel, G. Melançon, and C. Rozenblat, Réseaux multi-niveaux: l'exemple deséchanges deséchanges aériens mondiaux, M@ppemonde, vol.79, issue.3, 2005.

G. Andrienko, N. Andrienko, P. Jankowski, D. Keim, M. Kraak et al., Geovisual analytics for spatial decision support: Setting the research agenda, International Journal of Geographical Information Science, vol.21, issue.8, pp.839-857, 2007.
DOI : 10.1080/00207540500247495

G. Andrienko, N. Andrienko, and S. Wrobel, Visual analytics tools for analysis of movement data, ACM SIGKDD Explorations Newsletter, vol.9, issue.2, 2007.
DOI : 10.1145/1345448.1345455

N. Andrienko and G. Andrienko, Exploratory Analysis of Spatial and Temporal Data, 2005.

D. Auber, Y. Chiricota, F. Jourdan, and G. Melançon, Multiscale visualization of small world networks, IEEE Symposium on Information Visualization 2003 (IEEE Cat. No.03TH8714), p.INFOVIS, 2003.
DOI : 10.1109/INFVIS.2003.1249011

URL : https://hal.archives-ouvertes.fr/lirmm-00269770

S. K. Card, J. Mackinlay, and B. Shneiderman, Readings in Information Visualization: Using Vision to Think, 1999.

A. Ceglar, J. F. Roddick, and P. Calder, Guiding Knowledge Discovery Through Interactive Data Mining, pp.45-87, 2003.
DOI : 10.4018/978-1-59140-057-8.ch004

Y. Chiricota and G. Melançon, Visually mining relational data, International Review on Computers and Software, 2005.
URL : https://hal.archives-ouvertes.fr/lirmm-00153838

A. Das, Semantic approximation of data stream joins, Member-Johannes Gehrke and Member-Mirek Riedewald, pp.44-59, 2005.
DOI : 10.1109/TKDE.2005.17

R. Duda, P. Hart, and D. Stock, Pattern Classification, 2000.

J. Dykes, A. Maceachren, and M. Kraak, Exploring geovisualization, 2005.
DOI : 10.1016/b978-008044531-1/50419-x

K. Engel, M. Hadwiger, J. M. Kniss, C. Rezk-salama, and D. Weiskopf, Real-time Volume Graphics, 2006.
DOI : 10.1201/b10629

M. Ester and J. Sander, Knowledge Discovery in Databases -Techniken und Anwendungen, 2000.

C. Forsell, S. Seipel, and M. Lind, Simple 3D Glyphs for Spatial Multivariate Data, Proceedings of the 2005 IEEE Symposium on Information Visualization (INFOVIS'05), p.16, 2005.
DOI : 10.1109/INFOVIS.2005.31

J. Han and M. Kamber, Data Mining, 2000.
DOI : 10.1007/978-1-4899-7993-3_104-2

D. Hand, H. Mannila, and P. Smyth, Principles of Data Mining, Drug Safety, vol.15, issue.2, 2001.
DOI : 10.2165/00002018-200730070-00010

A. Inselberg and B. Dimsdale, Parallel Coordinates: A Tool for Visualizing Multivariate Relations (chapter, pp.199-233, 1991.

J. A. Jacko and A. Sears, The Handbook for Human Computer Interaction, Lawrence Erlbaum & Associates, vol.20126252, 2003.
DOI : 10.1201/b11963

D. Keim and T. Ertl, Scientific visualization (in german), Information Technology, vol.46, issue.3, pp.148-153, 2004.

D. Keim and M. Ward, Visual Data Mining Techniques, 2003.

D. A. Keim, M. Ankerst, and H. Kriegel, Recursive pattern: a technique for visualizing very large amounts of data, Proceedings Visualization '95, p.279, 1995.
DOI : 10.1109/VISUAL.1995.485140

D. A. Keim, C. Panse, M. Sips, and S. C. North, Pixel based visual data mining of geo-spatial data, Computers & Graphics, vol.28, issue.3, pp.327-344, 2004.
DOI : 10.1016/j.cag.2004.03.022

J. Krúger, J. Schneider, and R. Westermann, ClearView: An Interactive Context Preserving Hotspot Visualization Technique, IEEE Transactions on Visualization and Computer Graphics, vol.12, issue.5, pp.941-948, 2006.
DOI : 10.1109/TVCG.2006.124

O. Maimon and L. Rokach, The Data Mining and Knowledge Discovery Handbook, 2005.

A. Meliou, D. Chu, C. Guestrin, J. Hellerstein, and W. Hong, Data gathering tours in sensor networks, Proceedings of the fifth international conference on Information processing in sensor networks , IPSN '06, p.IPSN, 2006.
DOI : 10.1145/1127777.1127788

T. M. Mitchell, Machine Learning, 1997.

F. Naumann, A. Bilke, J. Bleiholder, and M. Weis, Data fusion in three steps: Resolving schema, tuple, and value inconsistencies, IEEE Data Eng. Bull, vol.29, issue.2, pp.21-31, 2006.

C. North, Toward measuring visualization insight, IEEE Computer Graphics and Applications, vol.26, issue.3, pp.6-9, 2006.
DOI : 10.1109/MCG.2006.70

H. Schumann and W. Müller, Visualisierung -Grundlagen und allgemeine Methoden, 2000.

B. Shneiderman, Tree visualization with tree-maps: 2-d space-filling approach, ACM Transactions on Graphics, vol.11, issue.1, pp.92-99, 1992.
DOI : 10.1145/102377.115768

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.1549

B. Shneiderman and C. Plaisant, Designing the User Interface, 2004.

R. Spence, Information Visualization, 2001.
DOI : 10.1007/978-3-319-07341-5

URL : https://hal.archives-ouvertes.fr/hal-01414610

J. J. Thomas and K. A. Cook, Illuminating the Path, 2005.

X. Tricoche, G. Scheuermann, and H. Hagen, Tensor Topology Tracking: A Visualization Method for Time-Dependent 2D Symmetric Tensor Fields, Computer Graphics Forum, vol.20, issue.3, 2001.
DOI : 10.1111/1467-8659.00539

A. Unwin, M. Theus, and H. Hofmann, Graphics of a Large Dataset, Statistics and Computing, 2006.
DOI : 10.1007/0-387-37977-0_11

J. J. Van-wijk, The Value of Visualization, VIS 05. IEEE Visualization, 2005., p.11, 2005.
DOI : 10.1109/VISUAL.2005.1532781

URL : https://hal.archives-ouvertes.fr/hal-00701741

J. Widom, Trio: A system for integrated management of data, accuracy, and lineage, pp.262-276, 2005.

J. S. Yi, Y. Kang, J. T. Stasko, and J. A. Jacko, Toward a Deeper Understanding of the Role of Interaction in Information Visualization, IEEE Transactions on Visualization and Computer Graphics, vol.13, issue.6, pp.1224-1231, 2007.
DOI : 10.1109/TVCG.2007.70515