2014 in review – visualizations to summarize my blog on data visualization

The WordPress.com stats helper monkeys prepared a 2014 annual report for this blog.

Here’s an excerpt:

A San Francisco cable car holds 60 people. This blog was viewed about 300 times in 2014. If it were a cable car, it would take about 5 trips to carry that many people.

Click here to see the complete report.

Assignment 4 – Processing

Though I haven’t made it so a user can select a file, I did make:

-a bar chart


-a scatterplot


-a scatterplot matrix


-parallel coordinates


I am pretty proud of what I was able to accomplish and feel like with a given data set I can create a visualization that I want to. I was able to add some interactive highlighting visualizations and provided a tooltip with the actual data values (to all except splom and parallel). I was not able to figure out filters with sliders yet, unless you count the filter in the parallel coordinates. I used the iris flower data set. Plan to add cars! I emailed Prof. Alark the zip (GitHub still thinks I am a robot…)

Lightning Visualizations

I am currently co-enrolled in an environmental ethics class where we have weekly journals based on articles we read from the web. This week I read this article and took an interest in the animation of the lightning data and couldn’t help but wish I could fix it up. It doesn’t seem like I have access to the Science journal to see the physical data (if its in the report at all). Ideas for the lightning data: make light colored dot at the spot of lightning and then as that spot gets hit again (could represent with a larger circle area) color the dot darker. It would result in a heat map of sorts for lightning. Theres always the 3D histogram, which depending on what the data looks like, it could be interesting, but as 3D isn’t the most palatable for the masses its not the best end goal visualization.

GraphDice: A System for Exploring Multivariate Social Networks

Original Paper: http://www.aviz.fr/old/graphdice/graphdice.pdf

This paper was very organized and included well planned research. They did a good job at laying down the ground work with the background information like the 3 categories of social network analysis software tools (confirmatory analysis, exploratory analysis and network visualization) and previous paper’s task and/or challenges with social network analysis. They concluded this section of the paper by stating that “visualizing multivariate networks is recognized as an important but difficult challenge,” and “[their] challenge is to provide a simple visualization tool supporting a more complete set of the SNA tasks”. The rest of the paper followed in its clarity. The preliminary user feedback section was particularly interesting to me. I thought it was good that they acknowledged that their full day workshop did not suffice as a user study and that they still plan to do one. The way they utilized the preliminary user feedback was pretty cool.

Force-Directed Edge Bundling for Graph Visualization

original paper: http://www.jessefagan.com/linksviz/forcebundles_eurovis.pdf

This paper described how edge bundling removes clutter and shows edge patterns and how they did it without hierarchy or control mesh. The edges were flexible springs, and the nodes were fixed positions. The self organization technique using physics is very intuitive. They presented both inverse linear and inverse quadratic models in the paper. They also described how bundled edges can differ greatly in length. I liked the section on smoothing using a Gaussian kernel. Figures 7-9 were very clear and effective in expressing the results of their work and without these I may have been a little lost.

Tree visualization with Tree-maps: A 2-d space-filling approach

Original paper: http://drum.lib.umd.edu/bitstream/1903/367/2/CS-TR-2645.pdf

This paper presented a very clean over view of the space-filling approach to tree maps. I thought it was very clear and the inclusion of pseudo code was very effective. It felt like a final project report for cs 245 or something with the definitions, but that made it seem accessible, which in a paper can be very effective. Midway through the paper I preemptively wrote down that there was not limits of this tree map algorithm included. I knew that this function had a finite number of nodes that it could effectively show on the screen. However, the display resolution section addressed my concern and included the idea of possible zooming, which was cool. Overall, I liked this paper because it felt like something I could easily write about my own work in the future.