Month: November 2014

Johanna Drucker’s article Humanities Approaches to Graphical Display discusses the prevalent challenges and approaches to visualizing and understanding data. First, she calls attention to the distinction between ‘data’ and ‘capta’. Acknowledging the difference between the two is of key importance – as they delineate “constructivist and realist approaches” (Drucker). Data is the information that surrounds us – existing independently and without human interpretation. Capta is the data that we interpret – “taken and constructed” (Drucker). The distinction between data and capta acts as the basis for a more comprehensive construction of data visualization. Instead of viewing bar charts and maps as absolute truth, we take capta as a caveat – this information is mediated.

Drucker discusses the huge impact this challenge offers. She writes, “If we don’t engage with this challenge, we give the game away in advance, ceding the territory of interpretation to the ruling authority of certainty established on false claims of observer-independent objectivity in the ‘visual display of quantitative information’” (Drucker). As we move into this stage of a digital world where scholars contribute work, we have to confront this issue head on. Drucker suggests that capta display “ambiguity and complexity”. This is an important step towards greater clarity in data presentation. Drucker explains, “Nothing in intellectual life is self-evident or self-identical, nothing in cultural life is mere fact, and nothing in the phenomenal world gives rise to a record or representation except through constructed expressions” (Drucker). This is all to say that any information we view must be mediated through humanistic approach.

A keen example of Drucker’s argument is Julia Belluz’s infographic for an online article The Truth about the Ice Bucket Challenge. The data visualization is titled Where We Donate vs. Diseases That Kill Us, which illustrates color coordinated circles that correspond to the amount of money donated to causes compared to the highest death causing diseases in the country. However, a blog post on Cool Infographics by Randy Krum points out that the size of the circles do not accurately depict the proportional values. Krum warns, “Designers make the mistake of adjusting the diameter of circles to match the data instead of area, which incorrectly sizes the circles dramatically. It takes some geometry calculations in a spreadsheet to find the areas and then calculate the appropriate diameters for each circle” (Krum). Krum proves his point by actually correcting the infographic. The result is much less impactful, as the size of the circles in each table level out considerably.

Bullez’s article has since been corrected by the website it was run on, Vox Media, but its mistake offers an insight into Drucker’s argument. In her “polemic call to humanists to think differently about the graphical expression in use in digital humanities” (Drucker), Drucker asks that capta shifts its terms from “certainty” to “interpretive complexity” For example, who donates to these causes and why? Who are the people who die of these leading-causes diseases and what are their stories? Although this is daunting, Drucker argues that it is all the more enlightening to the humanist approach to knowledge and understanding.

Krum, Randy. “False Visualizations: Sizing Circles in Infographics.” Web log post. Cool Infographics. N.p., 29 Aug. 2014. Web. 2 Nov. 2014.

Johanna Drucker in Humanities Approaches to Graphical Display talks about how digital visualization tools act as an “intellectual Trojan Horse,” or a “vehicle which assumptions about what makes up information swarms with form.” As I was reading this I realized that graphical displays are not the only forms that act as Trojan Horses. Advertisements have become just as sneaky, playing on consumer assumptions.

The advertisement that came to mind was the one below:

 

I saw this post float around Tumblr for a bit with the caption, “Who’s Alex? Billboard demonstrating gender stereotypes as most people automatically assume that Alex is the boy.”

I sure as hell did. I’m even sure the people reading this blog post even assumed that Alex was the boy. I even thought it was a clever advertisement, a company riding on the strongly rising movement of gender equality. It was clever that they were forcing people to face their stereotypes and their assumptions. It’s clever because we think that it’s doing exactly what Drucker has been saying. The advertisement is saying “Look, you assumed! That’s okay though. You can change. Buy our products.” Or something to that extent.

This is where it kind of gets Inception-like.

We’ve been fooled. We’ve made the assumption that this ad played off of our gender assumptions and stereotype, when in fact the advertisement actually just used advertising and design trick. Tumblr user, Urulokid demonstrates that Body Shop is catching us red-handed but because the little boy is the focal point, we immediately assume he’s Alex. Furthermore, Urulokid proves that the ad is fallacious because English readers’ eyesight scans from left to right. The first thing we read is “MEET ALEX” and then our eyes go immediate right of the words to the boy.

 

 

 

 

http://www.cubancouncil.com/work/project/moodstats

Moodstats is a program made by Toke Nygaard and Per Jørgensen in 2000. It’s a personal diary where you can record notes on the day’s events and the changes in your mood, creativity, stress, and three more customizable variables. The data can be displayed either as a line graph or a stacked column chart.

The data visualizations that this application produces are good examples of what Johanna Drucker would characterize as an observer-independent, realist visualization of qualitative experiences. It is analogous to her example of a “standard map with a nuanced symbol set,” except the symbol set isn’t even nuanced. The programmers did not see data as capta when they made this program, and the structure of the visualizations is not based on interpretive, co-dependent relations of observer and phenomena. Each variable is rated on a scale from 1-10, a reductivist approach that eliminates uncertainty and ambiguity, and the axis for time is linear and homogenous. The parametrization of data is scientific, and the graphic design reinforces the cuteness of how silly it is to represent your mood with such precision and certainty. Still, the rhetoric of objectivity is attractive when considering the possibility of finding patterns in your mood and identifying triggers to mood swings. Sometimes you want a detached observer or method of observation to get a more authoritative perspective on emotional matters.

Looking at the experimental graphical expressions of interpretation in Drucker’s article, it is clear that they would be much more effective at representing a person’s daily mood changes. Crises and their self-conscious interpretation would be more apparent and revealing if they were shown “as a factor of X.” The subjective experience of time could also be represented by expanding, contracting, and warping the timeline. However, maybe it would be hard for a computer program to make graphical expressions automatically. It seems like producing graphical expressions involves a lot more thought and work than regular graphs and charts (which isn’t to say that data visualizations are easy to make). The word “expression” implies human subjectivity, and the visualizations in the article look sophisticated and for lack of another term, artistic. Can graphical expressions be made in about as practical a manner as realist data visualizations?

At the end of her article, Drucker refers to Edward Tufte’s book “The Visual Display of Quantitative Information.” She contrasts that model of information design against the humanities approach to graphical expression that she proposes. Just to put this program into context, Tufte’s book was originally published in 1983, and it become popular at the turn of the century. Maybe the design of Moodstats would have been different if it was made after Drucker’s article was published.

 

Although relatively short, I found the “With Criminal Intent” article to still reveal significant information.  Put briefly, the article discusses a way of datamining through the use of three online resources: the Old Bailey Online, Zotero and TAPoR.  Together, the narration uses the programs to research various data pertaining to criminal cases to uncover particular information.  I did not find the overall process to be all that intriguing but I did find the combination of several programs to reach a goal to be very fascinating.  Using the three resources in conjunction not only allowed for a denser and more thorough research, but expanded the capabilities that one could do alone.

Often, there are various items or programs that ultimately serve the same purpose but vary in their strengths and weaknesses.  We have to then weigh the pros and cons of each product and commit to the one we find best suited.  In the case provided from the article, there is unification between the programs that allows for cohabitation and a process that efficiently goes beyond the scope of each individually.

Similarly, this example is very similar to the Digital Audio Workstations (DAWs) used for audio engineering.  As mentioned, certain programs may have aspects that the others do not offer or allow for secondary purposes that are not capable through another program.  In the case of DAWs, a method known as Rewire allows there to be communication between different software. For example, by using Rewire, an audio engineer can use Logic Pro X with Live (both DAWs) and increase functionality.  Through this process, a wide array of musical instruments and mixing capabilities become available along with an efficient workflow.

While others may not find my example to be relatable or significant, the mere fact that two separate programs can be bridged together to increase efficiency and expand upon their individual capabilities should be.  Furthermore, allowing for a proficient linkage between programs may lead to greater and speedier developments.  As we continue to gravitate towards a technology-rich world, cohesion between programs will become even more important to promote a sense of seamlessness.

 

Sources:

1. http://criminalintent.org/%20%20getting-started/

http://www.sodahead.com/living/what-race-are-you/question-1919271/?link=ibaf&q=&esrc=s

Race is a classification system that has affected many people simply because of their skin color or country of decent. “Invisible Australians” states that early twentieth century Australia identified itself as a white man’s country and enacted discriminatory laws and policies against the non-European people that lived there. These people were basically denied their place as Australians.

“The Real Faces of White Australia” shows faces of men of non-European decent, people who lived in Australia but faced discrimination because of their skin color. A link is provided below and if you click on one of the portraits, you will find a record stating that that individual was forced to leave Australia for a certain number of years (most said three) and if they returned before that time finished, they would face consequences. Could you imagine being forced to leave the country you call home just because of the way you look or your decent? Even in recent years, people here face forms of discrimination based on race.

I intern at a psychiatrist’s office and one of the young ladies that works there is mixed Black and Guatemalan so as a child, she hated answering what gender she was when it came to school forms because of one time when she marked herself as Hispanic, resulting in the school placing her in a class for children who spoke English as a second language. She ended up having to take a test to prove that she could speak English fluently. Her school functioned with the notion that race defined whether she spoke English fluently or not.

People of mixed decent are not as uncommon as they were ten years ago making it seem like the notion of race is outdated, and for the most part, it is except for when it comes to a person’s health. Categorization of Humans in Biomedical Research: Gene, Race, and Disease says that “The human population is not homogeneous in terms of risk of disease. Indeed, it is probably the case that every human being has a uniquely defined risk, based on his/her inherited (genetic) constitution…” In this sense, it is important to categorize people based on their decent because of health risks that may have been passed down by an allele. Categorization does have its negatives because of the social impacts that it can have on a group of individuals, but it does have its use and purpose for protecting them as well.

Work Cited

http://invisibleaustralians.org/

http://invisibleaustralians.org/faces/

http://www.biomedcentral.com/content/pdf/gb-2002-3-7-comment2007.pdfThat

Reading through “Humanities Approaches to Graphical Display” I was slightly taken aback by the thought that humanities should develop their own methods of display and analyzing graphics. While it would be great to have designs built with digital humanities in mind, the role of a researcher is not to design technology but to research. The presence of the technology is a bonus that allows us to further explore information we already have and present it in a fashion the public is already familiar with. An example I thought of would be methods of survey in archaeology. Almost every method was developed for another purpose be it geology, military, or geography. GIS, metal detectors, GPR (Ground Penetrating Radar) and others were never meant to be used for archaeology and yet they are adaptable to our field (https://www.utexas.edu/courses/denbow/labs/survey2.htm.) Archaeologists use these technologies but do not spend time inventing materials of their own; that is the job of computer scientists and statisticians.
Another possible problem with creating digital visualizations of our own is that the public user may not be as familiar with the format as they are with others. The current designs in existence take marketing and public interest into account more often than do researchers designing tools for themselves. The point is, any visualization tool designed for digital humanities scholars will never be truly meant for everyday users.
Academia is essentially nothing but borrowed ideas manipulated to fit our study and improved upon. I would argue that current methods of visualization are still valuable as they present a basis from which to work off of and possibly improve.
“Humanistic methods are counter to the idea of reliably repeatable experiments or standard metrics that assume observer independent phenomena.” This definition of the humanities struck me as rather odd. While the author is arguing that the humanities are not the sciences and should be kept as human as possible, I would like to point out the irony of putting these human concepts in computers. What is digital humanities but the combination of the humanities and science? Experimental science also lends validity to concepts brought up through theories. Visualization and data analysis are scientific approaches to understanding humanistic data. It would seem rather possessive for the humanities to remain only with the social scientists. We have to admit that there is a possibility of realizing new ideas through the application of scientific methods. Research should not be limited to one area or department but can be combined with other disciplines entirely different from our own.

Johanna Drucker, “Humanities Approaches to Graphical Display,” Digital Humanities Quarterly5, no. 1 (2011)

http://structuralarchaeology.blogspot.com/2011/11/archaeo-toons-secrets-of-stonehenge.html

 

Johanna Drucker’s article focuses on the concept of data as capta. She argues that because all data is taken through observation and then interpreted, none of it is “given as a natural representation of pre-existing fact.” In other words, that knowledge is by default constructed, simply based on our interactions with it. She argues effectively that the traditional data visualization is a tricky and often murky issue. The traditional charts and graphs which present information so clearly and succinctly are often taken at face value as knowledge, when in fact so many decisions and assumptions are included in the visualization. She gives the example of amounts of men and women in certain countries at a certain time. The resultant bar chart is clear, and one can easily make the snap judgement that these are the final statistics pertaining to this question. However, as Drucker delves deeper into the prior assumptions and decisions made by the visualizer, the picture becomes much less clear. She begins with a discussion of the non-binary nature of gender, as well as how socio-cultural norms can effect these statistics – such as when a woman is only socially considered to be (and therefore recorded statistically as) a woman once she is of reproductive age. She goes on to consider how the interpreters have dealt with (or not dealt with) populations crossing national boundaries, skewing the entity of the “nation” represented on the graph, or transient populations which could skew the temporal component. She notes that while the traditional graphs are extremely useful, especially in the case of determining the location of a cholera outbreak, we have to be careful with the information we assume to be knowledge. It may be more useful to humanists to create more complex, messy visualizations that treat our prior assumptions and interpretations of the data up front.

A very similar debate can be found in the field of archaeological theory. In the 1960s, the processual school rose to dominance. This type of theory stresses scientific methods of hypothesis to create general, systems-based explanations for important cross-cultural themes such as the emergence of the state. These incredibly systematic solutions were meant to be diagnostic regardless of the context, and generally removed any focus on the specific culture or human agency. In the late 70’s and 80’s, a reactionary school called postprocessualism arose which was focused much more acutely on individual agency and were incredibly context specific in their analysis. These scholars, in much the same tone as all data being capta, believed that the material record could not be treated outside of its specific context and social interpretation.