Global Homicide

Melisa Dougherty

Using Data gathered from the World Health Organization (WHO), I hoped to analyze global homicide not only from a geographical standpoint, but also from a gender perspective, comparing the rates of homicide of both genders in each country. From this, I not only hoed to discover information regarding different regions but also about how homicide affects either gender and what this information says.

Data

Download file "INFOGRAPHData.xls"

First Visualization

My initial visualization served as a means of portraying the ray data and none of the information that I extracted from it. In this visualization, I compare the homicide rates in twenty-five countries (the countries with the highest rates of homicide). The numbers are based on statistics that state the number of man and women murdered out of 100,000 people. This was the format of the original data.

In this visualization, I chose an extremely basic bar graph design, portraying that data regarding men in blue (a hegemonic masculine color) and the data from women in a red (a hegemonic feminine color). Both colors are not only basic colors but they are contrasting, making the data more visually separated. In addition, the colors chosen are extremely symbolic in that blue is traditionally associated with men and red is a darker version of pink, a traditional color for females. By setting the bars on a dark background and adding a three diminutional visual effect, I hoped the bars and the data itself would jump out, making not only the data self-explanatory but also making it visually accesible to an audience. Through this information, I gathered clearly, that South Africa and Columbia had the highest rates of homicide, which made me wonder why. It is important that I point out that this data was taken from 2004, and upon further research, i found the significance of this. In this year columbia ffaced great strife with drug wars. In addition, in South Africa, there was genocide. Therefore, the significance of this visualization is that not only does it show the difference in homicide rates between genders, but it also highlights the countries with the highest homicide rates, bringing awareness to these regions. This is important specifically in this case in the push to save lives and end genocide. If no one is aware, then no one can help.

Second Visualization

After this initial graph, I was even further interested in attempting to draw attention to the countries with particularly high rates. I wanted to see if it was possible for me to create a visualization that highlighted this information even further. Sparing further research, I wanted to stick with the same data information, seeing if I could use it to show the information that I specifically wanted to.

IN this map, I used some basic math to find total homicide rates per country. I think exported this data to create a map highlighting the countries of both high and low homicide rates, provided by the color spectrum. I wanted to make this map more interactive as to make the audience further involved in the information, which was my initial intent. I then chose these specific colors to reflect the content of the map– red of course symbolizing blood and death, meaning the regions with the highest cases of homicide where darkest in shade. I think I accomplished my goal. If I ever have to do an assignment like this again, I think I will make it even more interactive by providing historical information within the visualization. When the viewer clicks on each country a window will come up showing the data and potential reasons for this rate. I think this graph was particularly significant for me because it was the first step into making this particular type of data interactive. This experience will be crucial as I continue on in this class

Third Visualization

At this point in the process, I wanted to turn back to the gender aspect of my data. I specifically wanted to focus on gender because of my experience in gender studies. The data sets I found provided little information regarding the differences in gender. This was good though because it allowed me the opportunity to delve far into the information, finding connections on my own rather than have them spelled out for me in the data.

Fourth VisualizationIn this particular visualization, I wanted to use a visual theme of homicide, so I knew I would be using violent images. By using a gun and bullets, I knew my visualization would contain some level of shock value, but I wanted to control this by not having any blood references present. By doing this I hope my visual was shocking but not so much so that it overpowers the information and makes it not accessible to viewers. Through this visual I attempted to demonstrate what percentage of the total homicide rate per country was from each gender. I demonstrated this even further through my use of different colors (in reference to the different colored bullets). It is subtle but clear enough to keep the data being demonstrated separate. While I think I did accomplish this visually, I do know I made one huge mistake which I hope to alleviate in future projects. That mistake was in the text. Underneath each bar, I wrote “Percent of Men Murdered Worldwide” and “Percent of Women Murdered Worldwide.” This makes it seem like the percent of the male and female population murdered, which was not my intent and not true of the information shown. I only realized this as I was beginning my writing, so I decided to keep this and I thought it would be important to discuss this mistake.

While the above graph did show the difference in homicide rates between each gender, I do not think it was effective enough in showing just how drastically different the rates are. Through my final visualization, I really wanted to make it extremely clear to any viewer the drastic difference in homicide rates of each gender. I also wanted it to be clear to those unfamiliar with the data.

By using extremely minimal design, I hoped to do just that. I used few colors and as few data sets as possible, making the information simplified and clear. I stuck with the idea of using visuals with violent connotations. In this case, that was bullet holes and targets- this not only served to the reflect the material being discussed but it also helped to get my ideas across regarding the material. I find that this data truly dehumanized what is happening in the world. In stead of making it clear what sad things are happening to people in the world by showing why these people are killed, it only shows numbers. By showing that view by quite literally taking away the human aspect and replacing it with a target, I hope to show the extremity of holding this view. By doing this, I hope that it does get people emotionally involved by showing them just how terrible it is not to be emotionally involved with this data. This way of demonstrating the data also allows for a wide range of interpretation. By being as simple as possible, the viewer really has control over how they choose to interpret the data and how the choose to associate significance with it

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Conclusion

Overall, I think this was an extremely valuable assignment for me not only as a new student in the realm of global health but also in applying my knowledge of IML. It allowed me to apply several design theories to a very important data set. Through trial an error I was able to explore what makes an information visualization effective and what does not. In addition, I had the opportunity to use the design of my visualizations as a means for communicating with a viewer, manipulation their scope of view to what I desired for them to see and how I wanted them to interact with the data. This is a key part of what design is and I learned that in the case of global health, it is extremely important because it is designs like this that determine whether or not a viewer gets exposed to information regarding health. Through these designs, awareness is spread, and if there is no awareness then change is not possible.
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