week 4

week1.md

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+This first reflection concerns a piece of work that I did during a summer internship at Northwoods Software Corporation. My task for this internship was to use the GoJS library (https://gojs.net) to make a diagramming layout for genograms, or advanced family trees. 
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+![Genogram](genogram.PNG)
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+Above is an example of the type of genogram that would be generated from this. The main issue in this project was scaling the visualization and visualizing trees that might consist of hundreds or thousands of nodes/people. This is a very difficult task, since visualizing large trees in the general case can get incredibly complicated incredibly fast.
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+I think this is a very interesting piece of work to showcase for the purposes of this class because it involves visualizing a fairly uncommon and unique type of data. Family trees aren't actually just trees all the time - they can become directed acyclic graphs in general, and this makes the visualization process even harder.
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+The layout is, of course, only one part of making a good genogram. Colors and shapes are also very important to the visualization, and luckily this is a much easier part of the project. This sample uses high-contrast colors and shapes to distinguish between genders and properties of people. Because genograms are often used to trace traits through a genaeology, this is an important part of the visualization as well.

week2.md

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+For my visualization for week 2, I wanted to look at the most commonly used websites on the internet in 2021. I found a visualization on visualcapitalist.com that had this information along with various categories for the websites. It is shown below:
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+![image](https://github.com/IanCoolidge0/reflections/blob/master/Top_50_Websites_V4-2-2048x2048.jpg)
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+Websites are roughly grouped according to their category. Color in the diagram represents the owning company, which allows the user to see how few overall companies control a large portion of the internet. The color scheme appears to be one of the Tableau color schemes and uses significant contrast between the colors to differentiate the companies.
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+In addition to this, this visualization is an example of using multiple methods to convey the same data. A bar chart in the top left corner shows the breakdown of websites by category which allows the user to see which kinds of websites are in general the most popular. Various blurbs throughout the diagram also present the user with additional information about the websites. Overall, after a short time looking at this graph a user can get a good sense of which websites are most popular at this time.

week4.md

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+![Picture of the netflix visualization](netflix-insights-2017-eclipse.png)

week5.md

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+My visualization for today is a representation of the 2013 budget that was posted in the New York Times. This shows the $3.7 trillion budget in several different views, showing various spending proportionally. The use of colored bubbles makes it very easy to see which parts of the budget are largest and have increased the most in this budget. The deficit is also shown.
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+Another useful view compares mandatory to discretionary spending. This shows that mandatory spending significantly outpaced discretionary spending in this year, and also that discretionary spending was significantly related to the military. Various uses of color, hue, and brightness also show various characteristics of the data. The breakdown by department also shows the relative spending between various departments.

week6.md

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+https://public.tableau.com/app/profile/nandinipundir/viz/The100Most-SpokenLanguagesintheWorld/TotalSpeaker
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+This visualization shows an area based map of some of the most spoken languages in the world today. This is a particularly interesting visualization to me since despite the fact that it still shows that English is the most spoken langauge in the world, the dominance is less than expected as Mandarin Chinese is spoken almost as much.
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+This visualiztino has several strong representations that make it easy to look at and read. The colors group languages into areas of origin such as Indo-European and Sino, while a mouseover allows the user to view the actual number of speakers of that language in the world. My one critique of this visualization is that the color scheme seems somewhat arbitrary. A color scheme with more similar or complementing colors might go a long way in making the visualization easier to look at overall.

week7.md

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+https://www.visualcapitalist.com/history-of-pandemics-deadliest/
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+This visualization demonstrates the history of the deadliest pandemics in human history. When initially looking at this graph, it is particularly interesting to note the unique visuals of the graph. Each pandemic is represented by a three-dimensional virus-looking objects which makes the visualization fun to look at. On the other hand this can make it somewhat difficult to easily compare sizes of the data points (representing death toll of that pandemic). This is because volume is one of the more difficult visualization methods to perform comparisons on, particularly for sphere-like objects.
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+Other aspects of the visualization provide more interesting data. Some text gives additional information on some of the deadliest pandemics, while a sorted list at the bottom allows readers to compare death tolls more accurately. In particularly it is interesting to note that there are many pandemics that have been significantly deadlier in the past compared to COVID-19, showing the enormous impact of those pandemics. Overall the color scheme and visualization makes this interesting to look at, but focuses less on utility of visualization than it could. It is particularly appropriate for a lay audience.