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The Journal of Supercomputing

, Volume 61, Issue 3, pp 1089–1115 | Cite as

Serviceable visualizations

  • Brian J. d’Auriol
Article

Abstract

Serviceable Visualizations describe a new paradigm of service-oriented visualizations that are suitable for cloud and other distributed or remote service-oriented architectures. Serviceable Visualizations address current-day visualization infrastructure limitations. This paper describes Serviceable Visualizations together with its two supporting models for visualization and service packaging. Application examples are given. A brief description of a middleware-based architecture to support Serviceable Visualizations is also described.

Keywords

Visualization Service-oriented architecture 

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References

  1. 1.
    (2002) Mpeg-21 overview v.5. http://mpeg.chiariglione.org/standards/mpeg-21/mpeg-21.htm. Accessed 04 August 2011
  2. 2.
    (2002) Remote and distributed visualization at Berkeley lab. http://www-vis.lbl.gov/Research/AMRvis/LBNLVisResearchOvervie_w-MICS-July2002.pdf. Accessed 04 August 2011, poster presented at July 2002 MICS PI meeting at ANL
  3. 3.
    (2004) Mpeg-7 overview (version 10). http://mpeg.chiariglione.org/standards/mpeg-21/mpeg-21.htm. Accessed 04 August 2011
  4. 4.
    Arafa Y, Mamdani A (2001) Building multi-modal personal sales agents as interfaces to e-commerce applications. In: Proceedings of the 2001 active media technology, AMT2001, Hong Kong, China. LNCS, vol 2252, pp 113–133 CrossRefGoogle Scholar
  5. 5.
    AVS Advanced Visual Systems http://www.avs.com. Accessed 04 August 2011
  6. 6.
    AVS Advanced Visual Systems AVS/Express 7.3 documentation. http://help.avs.com/Express/doc/ExpressDoc.asp. Accessed 04 August 2011
  7. 7.
    Becker L, Bernard L, Döllner J, Hammelbeck S, Hinrichs KH, Krüger T, Schmidt B, Streit U (2000) Integration of dynamic atmospheric modeling and object-oriented GIS. Geoinformationssysteme 13(2):19–23 Google Scholar
  8. 8.
    Belaton B, Brodlie K (2002) Model centred approach to scientific visualization. Journal of WSCG 10(1):63–70 Google Scholar
  9. 9.
    Bethel W (2004) Science-driven visualization research challenges. http://crd.lbl.gov/DOEresources/SC04/Bethel_Viz_SC04.pps#257, 1. Presentation at Supercomputing 2004 (SC2004), available from http://vis.lbl.gov
  10. 10.
    Brodlie K, Carpenter LA, Earnshaw RA, Gallop R, Hubbolt R, Mumford AM, Osland CD, Quarendon P (eds) (1992) Scientific visualization: techniques and applications. Springer, Berlin MATHGoogle Scholar
  11. 11.
    Brodlie K, Wood J, Wright H (1996) Scientific visualization—some novel approaches to learning. SIGCSE Bull 28:28–32. doi: 10.1145/237477.237516 CrossRefGoogle Scholar
  12. 12.
    Bull RI (2006) Integrating dynamic views using model driven development. In: Proceedings of the 2006 conference of the Center for Advanced Studies on Collaborative. ACM, New York, pp 1–14 Google Scholar
  13. 13.
    Bull RI (2008) Model driven visualization: towards a model driven engineering approach of information visualization, PhD thesis, Department of Computer Science, University of Victoria, Victoria, BC, Canada Google Scholar
  14. 14.
    Charters SM (2008) Visualization for eResearch: past, present and future. In: Wyborn L, McMillan P (eds) Proceedings of eResearch Australasia, Melbourne, Australia Google Scholar
  15. 15.
    Chengzhi Q, Chenghu Z, Tao P (2003) Taxonomy of visualization techniques and systems—concerns between users and developers are different. In: Proceedings of the Asia GIS conference. IEEE Computer Society, Wuhan. http://www0.hku.hk/dupad/asiagis/fall03/Full_Paper/Qin_Chengzhi.pdf. Available from: http://www0.hku.hk/dupad/asiagis/ Google Scholar
  16. 16.
    Chi EHH, Riedl JT (1998) An operator interaction framework for visualization systems. In: Proceedings of the IEEE symposium on information visualization, Research Triangle, CA, USA, pp 63–70 Google Scholar
  17. 17.
    Chuah MC, Roth SF (1996) On the semantics of interactive visualizations. In: Proceedings of the 1996 IEEE symposium on information visualization (INFOVIS’96). IEEE Computer Society, Washington, pp 29–36 CrossRefGoogle Scholar
  18. 18.
    d’Auriol BJ (2009) Serviceable visualizations. In: Proceedings of the 2009 international conference on modeling, simulation and visualization methods (MSV’09), pp 378–382. CSREA Press, Monte Carlo Resort Google Scholar
  19. 19.
    d’Auriol BJ (2010) Aerospace mobile sensor network visualization requirements. In: Proceedings of the international conference on advanced aircraft technologies (ICAAT 2010) Google Scholar
  20. 20.
    d’Auriol BJ (2010) Effective new visualization approaches for emerging databases. In: Proceedings of the second international conference on emerging databases (EDB 2010) Google Scholar
  21. 21.
    d’Auriol BJ, Hung LX, Lee S, Lee YK (2009) Visualizations of human activities in sensor-enabled ubiquitous environments. In: International workshop on sensing and acting in ubiquitous environments (SEACUBE’09), St.-Petersburg, Russia Google Scholar
  22. 22.
    d’Auriol BJ, Nguyen T, Pham T, Lee S, Lee YK (2008) Viewer perception of superellipsoid-based accelerometer visualization techniques. In: Proceedings of the international conference on modeling, simulation and visualization methods (MSV’08). CSREA Press, Monte Carlo Resort, pp 129–135 Google Scholar
  23. 23.
    Gobel M (2004) visualization in scientific computing. In: Proceedings of the international workshops on visualization in scientific computing Google Scholar
  24. 24.
    Gong B, Singh R, Jain R (2004) Research explorer: gaining insights through exploration in multimedia scientific data. In: Proceedings of the 6th ACM SIGMM international workshop on multimedia information retrieval (MIR’04). ACM Press, New York, pp 7–14 CrossRefGoogle Scholar
  25. 25.
    Haber R, McNabb D (1990) Visualization idioms: a conceptual model for scientific visualization systems. In: Nielson G, Shriver B, Rosenblum L (eds) Visualization in scientific computing. IEEE Press, New York, pp 74–93 Google Scholar
  26. 26.
    Jeong B (2010) Remote visualization systems and software. http://cms.tacc.utexas.edu/fileadmin/class_materials/03-29Visualization_Systems_and_Software.pdf, Presentation file
  27. 27.
    Johnson GP, Mock SA, Westing BM, Johnson GS (2009) EnVision: a web-based tool for scientific visualization. In: Proceedings of the 2009 9th IEEE/ACM international symposium on cluster computing and the grid, CCGRID’09. IEEE Computer Society, Washington, pp 603–608. doi: 10.1109/CCGRID.2009.80 CrossRefGoogle Scholar
  28. 28.
    Joshi A (2009) In: Papademetris X, Joshi A (eds) An introduction to programming for medical image analysis with the visualization toolkit, 2nd edn Google Scholar
  29. 29.
    Kalawsky R (2006) A visualization service for the national grid service: a workshop to derive user needs. http://syseng.lboro.ac.uk/Visualization_Service_for_the_Natio_nal_Grid_Grid_Service%20. Accessed 04 August 2011 Report of Workshop
  30. 30.
    Kongkanen P, Lahtinen J, Myllymäki P, Silander T, Tirri H (2000) Supervised model-based visualization of high-dimensional data. Intell Data Anal 4(3, 4):213–227 Google Scholar
  31. 31.
    Lamberti F, Sanna A (2007) A streaming-based solution for remote visualization of 3d graphics on mobile devices. IEEE Trans Vis Comput Graph 13(2):247–260 CrossRefGoogle Scholar
  32. 32.
    Library, OG. http://www.opengl.org/. Accessed 04 August 2011
  33. 33.
    Lienhard A, Kuhn A, Greevy O (2007) Rapid prototyping of visualizations using Mondrian. In: Proceedings of the 4th IEEE international workshop on visualizing software for understanding and analysis (VISSOFT 2007), pp 67–70 CrossRefGoogle Scholar
  34. 34.
    Lietsch S, Marquardt O (2007) A cuda-supported approach to remote rendering. In: Proceedings of the 3rd international conference on advances in visual computing (ISVC’07)—Volume Part I. LNCS, vol 4841, pp 724–733 Google Scholar
  35. 35.
    Liu Y, Gao S (2009) Wsrf-based distributed visualization. In: Proceedings of the 9th IEEE/ACM international symposium on cluster computing and the grid. IEEE Computer Society, Los Alamitos, pp 615–619 CrossRefGoogle Scholar
  36. 36.
    LongJump, Longjump, a relational networks company. http://longjump.com/. Accessed 04 August 2011
  37. 37.
    Map, O.S.S.I. www.ossim.org/. Accessed 04 August 2011
  38. 38.
    Maya. http://usa.autodesk.com/maya/. Accessed 04 August 2011
  39. 39.
    Meyer M, Girba T, Lungu M (2006) Mondrian: an agile information visualization framework. In: Proceedings of ACM symposium on software visualization (SoftVis 2006) Google Scholar
  40. 40.
    Microsoft (2011) List view. http://msdn.microsoft.com/en-us/library/aa511485.aspx. Accessed 04 August 2011
  41. 41.
    Microsoft (2011) Tree views. http://msdn.microsoft.com/en-us/library/aa511496.aspx. Accessed 04 August 2011
  42. 42.
    NICE. http://www.nice-italy.com/web/nice/home. Accessed 04 August 2011
  43. 43.
    Peng W, Ward MO, Rundensteiner EA (2004) Clutter reduction in multi-dimensional data visualization using dimension reordering. In: INFOVIS’04: Proceedings of the IEEE symposium on information visualization. IEEE Computer Society, Washington, DC, pp 89–96. doi: 10.1109/INFOVIS.2004.15 CrossRefGoogle Scholar
  44. 44.
    Preim B (2005) Model-based visualization for intervention planning. In: Meinzer H, Kim M (eds) Proceedings of 8th Korea-Germany joint workshop on advanced medical image processing. Berlin, Germany, pp 33–43 Google Scholar
  45. 45.
    Preim B, Oeltze S (2008) 3d visualization of vasculature: an overview. In: Linsen L, Hagen H, Hamann B (eds) Visualization in medicine and life sciences, mathematics and visualization. Springer, Berlin, pp 39–59. doi: 10.1007/978-3-540-72630-2_3 CrossRefGoogle Scholar
  46. 46.
    Radoiu D, Enachescu C, Adjei O (2006) A systematic approach to scientific visualization. Eng Comput 23(8):898–906 MATHCrossRefGoogle Scholar
  47. 47.
    Rosenholtz R, Li Y, Nakano L (2007) Measuring visual clutter. J Vis 7(2):1–22 CrossRefGoogle Scholar
  48. 48.
    Rossignac J, Novak M (1994) Research issues in model-based visualization of complex data sets. Comput Graph Appl 14(2):83–85. doi: 10.1109/38.267479 CrossRefGoogle Scholar
  49. 49.
    Ruffino F (2009) Remote visualization and cloud computing for e-infrastructures. Presentation at ESA 4rd GRID & e-Collaboration Workshop, Frascati, Italy Google Scholar
  50. 50.
    Sanglard H (2001) Towards an easy-to-learn and extensible platform for scientific visualization, PhD thesis, University of Neuchatel Google Scholar
  51. 51.
    Shalf J, Bethel EW (2003) The grid and future visualization system architectures. IEEE Comput Graph Appl 23(2):6–9. doi: 10.1109/MCG.2003.1185573 CrossRefGoogle Scholar
  52. 52.
    Shelestov A, Kravchenko O, Ilin M (2008) Distributed visualization systems in remote sensing data processing grid. Int J Inf Technol Knowl 2:76–82 Google Scholar
  53. 53.
    Singh R, Pinzón JC (2007) Study and analysis of user behavior and usage patterns in a unified personal multimedia information environment. In: Proceedings of the 2007 IEEE international conference on multimedia and expo, Beijing, China, pp. 1031–1034. doi: 10.1109/ICME.2007.4284829 CrossRefGoogle Scholar
  54. 54.
    Stasko JT, Domingue J, Brown MH, Price BA (eds) (1998) Software visualization: programming as a multimedia experience. MIT Press, Cambridge Google Scholar
  55. 55.
    Texas Advanced Computing Center Longhorn visualization portal. https://portal.longhorn.tacc.utexas.edu/. Accessed 04 August 2011
  56. 56.
    Toolkit V. http://www.vtk.org/. Accessed 04 August 2011
  57. 57.
    Tory M, Möller T (2004) Rethinking visualization: a high-level taxonomy. In: Proceedings of the IEEE symposium on information visualization, Austin, TX, USA, pp 151–158 CrossRefGoogle Scholar
  58. 58.
    Tufte ER (1990) Envisioning Information, Graphics Press LLC Google Scholar
  59. 59.
    Upson C, Faulhaber T Jr, Laidlaw DK, Schlegel D, Vroom J, Gurwitz R, van Dam A (1989) The application visualization system: a computational environment for scientific visualization. IEEE Comput Graph Appl 9(4):30–42 CrossRefGoogle Scholar
  60. 60.
    Ware C (2004) Information visualization perception for design, 2nd edn. Morgan Kaufmann, San Mateo Google Scholar
  61. 61.
    Zudilova-Seinstra E, Yang N (2005) Towards service-based interactive visualization. In: Proceedings of the international symposium on ambient intelligence and life, pp 15–25 Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Computer EngineeringKyung Hee UniversityGlobal CampusKorea

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