My Plan for the final project in Information Visualization Class. Exercise for #Flow_Diagram

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My Plan for the final project in Information Visualization Class. Exercise for #Flow_Diagram

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My Information Visualization Homework this week. Good practise for graphic design skills. :)
Researchers at Baylor compared a normal human genome with that of the MCF-7 breast cancer cell line to analyze the genetic differences. This infographic summarizes the results quite well. Around the outside are the normal chromosomes, each individually colored. The inner ring depicts the breast cancer chromosomes.
Blue lines show DNA rearrangements within a chromosome, while red lines show transpositions between one chromosome to another. Overall, 157 rearrangements were found between the two genomes.
Comparative Genome Hybridization data, which I don't entirely understand, is plotted in the grey bars immediately inside the normal chromosomes, and I think shows differential expression between the normal and breast cancer cell lines; gains are represented in lime green, while losses are in red.
I think this is a very effective visualization which simplifies a vast amount of genetic data into one consolidated graphic. The hybridization data could have been left out and represented in another instance of the graphic in order to simplify it further.
The visualization can be viewed at the following sites:
http://www.nytimes.com/2008/12/25/science/25visual.html
http://www.genboree.org/java-bin/MCF7/index.jsp?isPublic=Yes
http://genome.cshlp.org/content/19/2/167.long
*This third link includes even more fascinating representations of the team's data.
this map shows the geolocation of selected galleries from the Metropolitan Museum of Art collection
displays the total number of objects in the Metropolitan Museum of Art digital collection

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In conjunction with MoMA's Inventing Abstraction exhibition the network visualization displayed and linked above was created. The interactive nature of the visualization allows users to easily navigate the web of interaction that took place between the years of 1910 and 1925, illustrating various relationships between influential and marginal figures of the Abstraction Movement. The visualization differentiates between the highly influential and networked and more liminal denizens by color coding the nodes. If the artist was highly influential, as indicated by the number of relations, then the node is in orange, lesser artists are black nodes. Individual artists can be clicked on and the network rearranges itself specific to that query so that the specific relationships can be examined and extra information is provided to enhance the user-experience and further aspects of the informal learning environment.
The visualization also serves to illustrate the reasoning for including particular artists in the exhibition and excluding others. Presumably, the movement of Abstraction and its creation including more individuals than the ones lauded at the show, but these were the most influential in terms of interaction and creating the necessary support for the movement.
http://www.emissionsglobe.com/
Designed by Robbie Tilton, this interactive graph, displaying total global emissions per country per year (up until 2010), is essentially a part-to-whole visualization with some extra use of color and graphics for added emphasis and affect. Users can switch between a bar graph and what amounts to a traditional pie chart (though only the outer surface area is displayed, leaving the smokey globe to think about). The visualization shows individual country (parts) effects upon the globe (whole) and uses varying color hues of red in order to show who pollutes the most (most opaque red) and the least (white). However, the bar graph and the pie chart are not quite perfectly representative across their respective mediums and might be a little misleading, depending on which graphic the user examines. Specifically, the pie chart creates to overlapping geographic sectors labeled "Asia & Oceania" (AO) and "Eurasia" (EA). The problem here is that there is the possibility for statistical overlap depending on which countries in Asia were considered closer (how? culturally? geographically?) to Oceania and which were closer to that of Eurasia. Typically, Eurasia is one continent that stretches from the "Atlantic in the west to the Pacific in the east...In the north Russia and Scandinavia abut [sic] the Arctic Ocean...Its southern borders are Africa, the Mediterranean Sea and the Indian Ocean" (http://en.wikipedia.org/wiki/Eurasia). Whereas Oceania controversially consists of "coral atolls and volcanic islands of the South Pacific to the entire insular region between Asia and the Americas...or used more specifically to denote Australia and proximate islands" (http://en.wikipedia.org/wiki/Oceania). SInce there is no legend or key to denote which countries are included in which geographic location, the user may be left with a sense of confusion. Likewise, when examining the bar chart, the geographic names change to specific countries such as China, Taiwan, India, Russia, Japan, Indonesia, and Australia, all of which might be considered part of one of the two geographic categories mentioned above. The whole visualization would certainly benefit from maintaining naming conventions between both manifestations and it seems that the information from the bar chart could have been easily applied to the pie chart
A visualization of US Military strategy in Afghanistan, first seen in a NYT article "Enemy Lurks in Briefings on Afghanistan" by Elizabeth Bumiller, 4/27/2010.
While the original article focuses on overuse of Power Point (which is a valid point) I think this graphic also demonstrates the ways in which data visualization itself can go awry.
Info visualization is based on data. This seems like a simple "duh" statement, but I think can easily get lost in the race to make a super impressive, overly complicated visualization. Moreover, data, whether gathered by computer or by person, still has the potential to be overwhelming, uninteresting, or irrelevant which can easily carry over into any visualization. The underlying message, whatever the purpose of the visualization is, can be lost if the choice of data (and ultimately the choice of message) is bad or if the method of execution is bad. Thinking about the different types of data and the various ways a visualization can go wrong (and it seems to me, it can go wrong at many points along the way from faulty data initially to poor visual element choice at the end) I decided to dig this gem out of my archives because I think it represents multiple poor choices, including data selection and representation. I know I don't understand what this is based on, what it means, and why it was presented, but I am not alone. When the then leader of the US Military in Afghanistan saw it, he said "When we understand that slide, we'll have won the war."
I saved this in my archives when I read the article nearly three years ago and I like to break it out occasionally as a cautionary tale when I am training people, or actually just giving a presentation myself. There is so much wrong with it - the data its based on is not apparent so its purpose and message is lost (although the unintentional message here must be that this war is a mess). the incomprehensible structure of the viz including the seemingly orderless use of color, the sheer number of arrows (nightmarish!), the fact that taxpayer money probably funded the exorbitant fee to the consulting firm who vomited this thing, the overuse of jargon in any situation, it's overall offense to the eye and on and on. I love this one so so much.
Too often, visualizations are done for the visualization's sake. The mess above just underscores to me the importance of data selection, data integrity, overall messaging, and final presentation when creating info visualization,.