Bibliography & Reading

Below is the VISTAS’ reading list/bibliography, relating to Scientific Visualization or work relevant to the environmental science we are ‘visualizing’ for our collaborators.  Each item is annotated with when and by whom the reading was posted, and if and when the item was included in the VISTAS reading group:

  1. Abdullah, Kulsoon, Chris Lee, Gergory Conti, John A. Copeland.  Visualizing Network Data for Intrusion Detection, June 16, 2005.
  2. Mike Bailey.  2013. Using GPU Shaders for Visualization Part I, Part 2, Part 3.   Visualization Viewpoints,  IEEE  Computer Graphics and Applications. #1: xxx, #2: March/April 2011 (vol. 31 no. 2), pp. 67-73,#3: May-June 2013.  Posted by Judy March 11, for Reading Group Friday, March 15, 2013.  See alsoTeaching a Shader-Based Introduction to Computer Graphics, www.computer.org/csdl/mags/cg/2011/02/mcg2011020009.pdf, by S Owen, Feb 10, 2011.
  3. Becker, Richard A., Stephen G. Eick (eick@research.bell-labs.com), Allan R. Wilks,  Visualizing Network Data, IEEE Transactions on Visualizationand Computer Graphics, Vol. 1, No. 1,pages 16-21,March 1995.
  4. Ecological Reflections:  A network of sites dedicated to long-term, collaborative science and art inquiry into particular sites of great ecological or cultural importance.
  5. Michael Dubakov, Targetprocess Founder, Visual Encoding, September 2012.  A useful description of the concept.
  6. Jean-Daniel Fekete, “Visual Analytics Infrastructures: From Data Management to Exploration,” IEEE Computer, vol. 46, no. 7, pp. 22-29, July, 2013
  7. Jon D. Genetti, M.Bailey, D. Laidlaw, R. Moorhead, R. Whitaker.  What Should We Teach in a Scientific Visualization Class? IEEE Visualization 2004, Austin, Texas, USA. 0-7803-8788-0/04, IEEE.
  8. Grey, Jim, and Alex Szakay (2004).  Where the Rubber Meets the Sky:  Bridging the Gap between Databases and Science.  Microsoft Technical Report (MSR-TR-2004-110).
  9. Guzy,Michael R. ,  Courtland L. Smith, John P. Bolte, David W. Hulse, and Stanley V. Gregory (2008)Policy Research Using Agent-Based Modeling to Assess Future Impacts of Urban Expansion into Farmlands and ForestsEcology and Society 13(1): 37.  Posted by Judy Cushing January 17, 2013, for January 2013 Reading Group.
  10. HANA Immersive Visualization Environment (HIVE), Stanford University, June 5, 2014.  accessed 6/6/2014.
  11. Hinsen, Konrad. Daydreaming about Scientific Programming, IEEE Computing Today, Sept./Oct. 2013 (Vol. 15, No. 5) pp. 77-79. 1521-9615/13/$31.00 © 2013 IEEE Published by the IEEE Computer Society.
  12. Petra Isenberg, Danyel Fisher, Meredith Ringel Morris, Kori Inkpen, and Mary Czerwinski. An Exploratory Study of Co-located Collaborative Visual Analytics around a Tabletop Display. In Proceedings of Visual Analytics Science and Technology (VAST), pages 179–186, Los Alamitos, CA, USA, 2010. IEEE. Received a best paper honorable mention. (doi) (PDF, 8 pages, 3.51 MB)
  13. Longo, João S. C., and Claudia Bauzer Medeiros. 2013.  Providing multi-scale consistency for multi-scale
    geospatial data.  SSDBM 2013, p. 60-71.
  14. John Lukasiewicz, Scientific Visualization Using Pixar’s RenderMan, Computer Science M.S. Thesis, Rochester Institute of Technology, June 29, 2011.
  15. Kosara, Robert. Storytelling: The Next Step for Visualization, IEEE Computer, May 2013 (Vol. 46, No. 5) pp. 44-50 0018-9162/13/$31.00 © 2013 IEEE.
  16. Rhyne, Theresa-Marie and Min Chen.  A Snapshot of Current Trends in Visualization – “5 articles that exemplify current trends in computer-generated visualization” – Computing Now, vol. 7, no. 1, Jan. 2014, IEEE Computer Society [online]; http://www.computer.org/portal/web/computingnow/archive/january2014.
  17. Bernice Rogowitz and Lloyd Treinish, Why Should Engineers and Scientists Be Worried About Color?
  18. Schultz, Nick, and Michael Bailey (2012). Using Extruded Volumes to Visualize Time-series Datasets. In Expanding the Frontiers of Visual Analytics and Visualization, J. Dill et al (eds), Springer-Verlag, Berlin, 127–148.  Posted by Judy Cushing October 11, 2011.
  19. Jared M. Spool, C. Perfetti, and D.Brittan.  2004.  Designing for the Scent of Information.  User Interface Engineering.   copyright held by www.uie.com.
  20. Michael Sedlmair, Petra Isenberg, Dominikus Baur, and Andreas Butz. Evaluating Information Visualization in Large Companies: Challenges, Experiences and Recommendations. In Proceedings of the CHI Workshop Beyond Time and Errors: Novel Evaluation Methods for Information Visualization (BELIV), pages 79–86, New York, NY, USA, 2010. ACM Press. Received the best paper award at BELIV 2010
  21. Thomas CK, Smoot AR.  2012.   An effective, economic, aspirated radiation shield for air temperature observations and its spatial gradients, J. Atmos. Ocean. Technol. inpress.
  22.  L. Treinish. Task-Specific Visualization Design:  A Case Study in Operational Weather Forecasting.
  23. P. Skraba, Bei Wang, G. Chen, P. Rosen. “2D Vector Field Simplification Based on Robustness,” In Proceedings of the 2014 IEEE Pacific Visualization Symposium. (“Best Paper” at PacificVis 2014)
  24. Matt Williams and Tamara Munzner. Steerable, Progressive Multidimensional Scaling. Proc. InfoVis 2004, pp 57-64.
  25. Sherry Yang, M. M. Burnett, E. DeKoven, MosheZloof.  1997. Representation Design Benchmarks: A Design-Time Aid for VPL Navigable Static Representations. Journal of Visual Languages and Computing 8, 563-599.