Methods<\/h2>\n
This presentation uses three visualizations. \u00a0The first is a line graph representing the number of publications made by City Hall over time. \u00a0The second is a bar graph showing how many publications were produced by the top ten most active agencies. \u00a0The third is a packed bubble chart showing what types of reports were made for the different topics.<\/p>\n
User testing was conducted both face-to-face\u00a0and through social media. \u00a0The tests included one interview, two observations, and a Likart scale. \u00a0All of the testers come from different backgrounds and have varying degrees of experience with regard\u00a0to data visualization, local government, and library publications. \u00a0For example, one tester is a journalist who has covered events at City Hall before, but otherwise has no experience with the institution. \u00a0Another tester is a grant writer for non-profit organizations with a background in law. \u00a0The third tester is knowledgeable about statistics\u00a0and has experience in creating information visualization. \u00a0The Likart scale was sent to an educator who had experience with colorblind people.<\/p>\n
Design Choice Rational<\/h2>\n
The line graph was chosen for the first chart because it is the easiest way to showcase the number of publications filed over time. \u00a0It’s simple, easy to read, and provides context for the two graphs below it. \u00a0The only difficulty was that one user felt the title of the presentation was the title of that first graph alone. \u00a0Because of this, he didn’t realize\u00a0that the other two graphs were connected. \u00a0To rectify this, the main title was bolded and centered to clarify the information for the reader.<\/p>\n
Due to the vast number of agencies who published their works to the New York City Hall library, the number of agencies on the second graph was reduced to the top ten. \u00a0Initially, the graph was created through vertical bars, but one user felt that horizontal bars were easier to understand because they could be read. Color-coding was also provided in the first draft of the graph to show the range of topics. \u00a0However, one user who didn’t have a strong affinity for color found it confusing that two graphs were color-coded. \u00a0Because of this, the color-coding was removed from the second graph. \u00a0It was also moved above to make more room for the third graph.<\/p>\n
The packed bubble graph was perhaps the most complicated to work with, but in turn, it became the most interesting. \u00a0Initially, several visualizations were examined to determine which would best represent the information. \u00a0The packed bubble graph was chosen because it was the easiest to interpret. \u00a0The size of the bubbles related to the number of publications regarding specific topics, and they were also color-coded by the types of reports published under each topic. \u00a0One user felt that sharp contrast between colors would be better than a standard pallet. \u00a0As such, a gradient between green and gold was used for the color-coding.<\/p>\n
One tester suggested a certain degree of interactivity to better read the information provided by the graphs. \u00a0Since TableauPublic has an inherent interactivity function, more direct action did not appear to be necessary. \u00a0However, another tester who was unfamiliar with the software was unaware that one could hover over different points on the graph and gain specific insight on each point, bar, and bubble. \u00a0For the purposes of further clarification, clickable filters and instructions were added.<\/p>\n
Results<\/h2>\n
The final presentation has some rather intriguing results, as shown below:<\/p>\n
![\"\"](\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2017\/06\/Dashboard-1-1-620x725.png?resize=620%2C725\")
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