September 2012 Archives

Week 5 Readings

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This week focuses on strategies to support an analytical process, design of tools to support those strategies, and then on visual analytics methods to interrogate networks of data.

  • Radburn, R., Dykes, J. and Wood, J. 2010: vizLib: Using The Seven Stages of Visualization to Explore Population Trends and Processes in Local Authority Research. In Haklay, M., Morley, J. and Rahemtulla, H., editors, Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010, 409-416.  {short paper and focused on rough ideas about design to meet some overarching analytical needs -- it uses sketched mock ups - available from: http://www.soi.city.ac.uk/organisation/is/research/giCentre/publications.html . To understand the tools discussed, try: http://www.gicentre.org/houseprices/  and watch this video: http://www.gicentre.org/hierarchical_layouts/  (the focus is on visual analysis to explore data and generate hypotheses - without links to statistics in this implementation, thus not directly useable to text hypotheses) & if you want the open source software, it is available here: http://www.treemappa.com/  }
  • Slingsby, A., Beecham, R. and Wood, J. 2012: Visual analysis of social networks in space and time. Paper presented at the Nokia Data Challenge Workshop, Pervasive 2012 Newcastle, UK. {this paper is from the same group as above.  It, again, focuses on the visual side of analysis targeting social network data. This paper took 3rd place in a Nokia research center challenge (You can get the paper at this link): http://research.nokia.com/page/12362 For more on their work: http://www.soi.city.ac.uk/organisation/is/research/giCentre/  }
  • Thiemann, C., Theis, F., Grady, D., Brune, R. and Brockmann, D. 2010: The Structure of Borders in a Small World. PLoS ONE 5, e15422 (open access journal). {Brockmann and colleagues has done a range of interesting research on network science; they don't call their work "visual analytics", but it fits most definitions of the term. For more on their work: http://rocs.northwestern.edu/publications/   }

Week 4 readings

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This week focuses on dealing with messy data:

  • Weaver, C., Fyfe, D., Robinson, A., Holdsworth, D., Peuquet, D. and MacEachren, A.M. 2007: Visual exploration and analysis of historic hotel visits. Information Visualization 6, 89-103. {in the SAGE Journals database of the library}. This paper, from work done here, focuses on development of cross-linked view strategies to explore qualitative data that has place, time, person, and other components in support of historical geographical research. In addition to reading the paper, watch the video at: http://www.geovista.psu.edu/resources/movies/VASThotels.html }
  • Kandel, S., Heer, J., Plaisant, C., Kennedy, J., van Ham, F., Riche, N.H., Weaver, C., Lee, B., Brodbeck, D. and Buono, P. 2011: Research directions in data wrangling: Visualizations and transformations for usable and credible data. Information Visualization 10, 271-288. {This paper focuses on developing methods for "data wrangling", or data manipulation and cleaning. It is a good example of how new useful interactive visualization methods can be developed for familiar problems. The authors also usefully concentrate on the issue of the recording, sharing, and re-use of data transformations.}

Week 3 Readings

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  • Dörk, M., Gruen, D., Williamson, C. and Carpendale, S. 2010: A Visual Backchannel for Large-Scale Events. IEEE Transaction on Visualization & Computer Graphics 16, 1129-1138. {IEEE Xplore library through our library} This is a non-geographic paper focused on advanced information visualization strategies for making sense out of streaming microblog data. Thus, it is not really a visual analytics paper either. The primary thing to focus on here is the various methods to visually signify streaming social media data and to think about how these methods might be applied in a more analytics-oriented system to answer some social science questions. [see: http://mariandoerk.de/visualbackchannel/ ]
  • Hollenstein, L. and Purves, R. 2012: Exploring place through user-generated content: Using Flickr tags to describe city cores. Journal of Spatial Information Science, 21-48. {open source journal} This is an explicitly geographically focused analysis of social media data (Flickr, specifically). The goals are, in part, to demonstrate that it is possible to analyze such data effectively from a geographical perspective and, in part, to (partially) answer a human geographic question about defining vague place references. The methods used might be considered VA, but that the authors don't label that way. Consider potential application of other methods you are aware of to get more out of these data plus other social science questions that might be addressed.
  • Diakopoulos, N., Naaman, M. and Kivran-Swaine, F. 2010: Diamonds in the Rough: Social Media Visual Analytics for Journalistic Inquiry. IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2010), Salt Lake City, Utah, USA, 115-122. {IEEE Xplore library - through our library} This is a visual analytics approach to supporting journalistic inquiry using microblog data about political elections. I'm guessing that the political scientists among us will not be satisfied (since the target is supporting journalists not scientists); but focus on what would be needed to apply to questions you are interested in. [http://sm.rutgers.edu/vox]
  • Vieweg, S., Hughes, A., Starbird, K. and Palen, L. 2010: Microblogging during two natural hazards events: what twitter may contribute to situational awareness. Proc. of the 28th Inter. Conference on Human Factors in Computing Systems: ACM, 1079-1088. {ACM Digital Linrary through our library} This paper is only marginally visual analytics (they don't use that term or draw on the literature).  But, it is a representative example of a set of work done by Leysia Palen's research group at Colorado on strategies to leverage twitter for understanding crisis events (and for responding during such events). When reading it, consider whether any of the more sophisticated visual analytics methods you have started to learn about would be applicable and how and/or what new methods would be needed. For the social scientists in the group, think of what social science theories and questions might be relevant. [look up the "tweek-the-tweet" site that Kate Starbird from this group created]

 

Week 1-2 Readings

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Week 1: Intro

  • Chapters 1-2 in Keim, D., Kohlhammer, J., Ellis, G. and Mansmann, F., editors 2010: Mastering the Information Age: Solving Problems with Visual Analytics. Goslar, Germany: Eurographics Association.

Week 2: VA & place-linked 'data'

  • Andrienko, G. and Andrienko, N. 2009: Visual Analytics for Geographic Analysis, Exemplified by Different Types of Movement Data. In Cartwright, W., Gartner, G., Meng, L. and Peterson, M.P., editors, Information Fusion and Geographic Information Systems: Springer Berlin Heidelberg, 3-17. {in SpringerLink database through our library}
  • Maciejewski, R., Rudolph, S., Hafen, R., Abusalah, A., Yakout, M., Ouzzani, M., S.Cleveland, W., Grannis, S.J. and Ebert, D.S. 2010: A Visual Analytics Approach to Understanding Spatiotemporal Hotspots. IEEE Transactions on Visualization and Computer Graphics 16, 205-220. {in IEEE database through our library}
  • Guo, D. and Jin, H. 2011: iRedistrict: Geovisual analytics for redistricting optimization. Journal of Visual Languages & Computing 22, 279-289. {via the ScienceDirect database in our library}
  • Kinnaird, P., Romero, M. and Abowd, G. 2010: Connect 2 congress: visual analytics for civic oversight. Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems, Atlanta, Georgia, USA: ACM. { in ACM database through our library}

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