Live Page: https://alisarmustafa.github.io/Portfolio/
Hello everyone!! My name is Alisar Mustafa, my pronouns are she/her or they/them. I am in the MSPPM Flagship Program. I was born and raised in Syria and moved to Austria at the age of 14 where I lived for two years before moving to Berkeley, California at the age of 16. I went to San Francisco State University where I majored in Political Science and minored in Middle East and Islamic Studies. I am interested in learning how to bridge the policy and activism worlds since they are very disconnected from eachother. I believe learning data visualization is a helpful tool to make policy more accessible to people.
I come from a deep rooted advocacy and activism background that started with my grandfather running away from Syria to Lebanon then escaping Lebanon during the civil war and my father being a political prisoner for 14 years in Syria for defying the Syrian government. After leaving Syria and seeing the outstanding amount of Syrians escapign and living in Refugee Camps, I felt pretty helpless on how to help until I realized that educatin is the first and most powerful step and tool to give people in refugee camps since it was impossible to help anyone inside of Syria. That is where my passion for education policy originated. I worked on a successful bi-annual Hearts for Syria fundraiser event to raise awareness and funds for UNHCR. I also worked closely with UNHCR on the issue. I also taught at San Francisco International School which is a public school for children who have been in the United States for four years or less. Because there is a disconnect between Policy Makers and workers on the ground I wanted to teach in these schools and learn the struggles that they go through before making policies that affects them. After I graduate I hope to work on managing projects that affect education for children in refugee camps or Immigration Detention Centers.
I would like to use this class to learn how to make data accessible for people who are not aware of the issues. I would also like to use this class so I can learn how to accurately and critically create visualizations for Education Policy proposals and give updates on how the specific projects are affecting the population. I hope to learn creative ways to convey data beyond simple charts.
<iframe src="https://data.oecd.org/chart/65O1" width="860" height="645" style="border: 0" mozallowfullscreen="true" webkitallowfullscreen="true" allowfullscreen="true">OECD Chart: General government debt, Total, % of GDP, Annual, 2018</iframe>General government debt-to-GDP ratio measures the gross debt of the general government as a percentage of GDP. It is a key indicator for the sustainability of government finance. Debt is calculated as the sum of the following liability categories (as applicable): currency and deposits; debt securities, loans; insurance, pensions and standardised guarantee schemes, and other accounts payable. Changes in government debt over time primarily reflect the impact of past government deficits.
For this chart I chose the color scheme to be one color because according to the article What to consider when choosing colors for data visualization by Datawrapper we should not use more than 7 colors in a chart because the more color we use the harder it becomes to read the chart. I wanted to use the gradient color scheme like the ones we use in GIS maps but I couldn't find a way to do it in the circle layout. I also used one color because I wanted the reader's focus to go immediately to the changes in sizes rather than the color as highlighted in the Good Charts book "our eyes go first to the change and difference". I used the circle layout rather than the treemap layout because I asked some of my friends and all of them preferred the circle layout because it reminded them of the Apple Watch Layout that they are used to. This speaks to the difference in audience, I would like to know what different age groups or professional groups think about this circle layout. One of my colleagues who works in the engineering department in the army told me that her boss prefers them using bar charts because that's what people are used to, however, I wonder if we are changing our default into more visually appealing charts used by big software companies such as Apple. Furthermore, even though I used one color I disagree that using one color is better than using many colors because it truly depends on the audience. I would rather see a gradient color on my chart than one color. I wanted to use a heat map for my visualization but I couldn't find a way to have a drop down window with the different years.
Source: Pennsylvania Juvenile Court Judge Commission, 2017 Juvenile Court Annual Report
Link to original chart: https://www.jcjc.pa.gov/Research-Statistics/Disposition%20Reports/2017%20Juvenile%20Court%20Annual%20Report.pdf
I was trying to find data on police in schools and the effect they have on students. I was more specifically looking for data about police presence in Pittsburgh Public Schools but I couldn't find any data to work with. As I was looking through the sources of different ACLU reports I found this report on Pennsylvania Juvenile Court which was close enough to what I'm interested in. I enjoyed reading most of the report because it had very good data but I did find myself wanting to edit most of the charts in it to make it more accessible to the general public. I thought a lot of the charts in the report if put together would make a great comparison.
First thing I wanted to make sure I do is make the bars horizontal rather than vertical so the labels are aligned. In addition I took out "other" and "unknown because it was not relevant to the analysis. I also limited the rate to up to 60% since there are no higher values than 60%. I also only included % sign next to 0 because according to our book, it de-clutters the map and eradicates repetitiveness. I kept the grid lines for now to give me guidance
In my second wireframe I added the data from the same report on population that was transfered to criminal proceedings based on race and ethnicity. I thought that this would make the chart more informative and eye catching.
In my final wireframe, I changed teh title to eliminate repetitivness. I also erased teh gridlines to make it clearer.
Feedback #1: I think this graph is about the % of cases of juvenile delinquency cases (allegations versus moved to criminal court), broken down by race and ethnicity. Probably for general readers. key being that more cases move to criminal court when they involve a Black non-Hispanic youth, or a Hispanic youth. think the graph is very telling and the move to side by side is a really neat one. empty bars tend to be harder to see/track, would recommend filling in the colors. align the bars to the y-axis so no bar is sticking out or overlapping would make it look very good! maybe label the x-axis? I see the 0% that's how I knew the unit of measurement, could help make it clearer by labelling it "% of cases". Also, hard to read from here if % is from total cases across all races and ethnicities, or the %s are calculated for each racial and ethnic groupif you like, could add the number to the right side of each bar to help people read the %, not necessary though if it was getting busyentirely convention here: I often find the legend (which color for which condition/group) to the right side of the graphalso bottom two bars for Hispanic group: spacing between the two bars seems wider than spacing for those bars in the other two groups.
Feedback #2: It is a bar chart. It described delinquency allegations and juveniles transferred to criminal proceedings. It is confusing whether the numbers contained in the first bar also represented in the second bar?. Maybe fill in the bars rather than having them as outlines. I assume your point is to highlight the fact that white juveniles are less likely to get jailed, but at first glance all I see is black and white have a long bar and hispanic a short bar. To make the distinction a bit clearer I think it would help to do percentages of the group for each group, rather than percentage of the pop as a whole
It was interesting to see that in Feedback #1 the person actually preferred to have more information on the expense of having it be cluttered and repetitive because it makes it easier for them to read. I think adding the percentages to the end of the bar is a helpful feedback. I also liked teh feedback on filling the bars with color rather than just an outline. I am also learning as I get feedback from people on my visualizations is that different things work for different audience depending on the complexity of the topic. Sometimes repeating and having a more cluttered chart is beneficial if it means the reader who doens't know anything about a complex topic would be able to understand it more.
For my final chart I included the percentages at the end following the suggestion in feedback #1. I also colored in the chart following the suggestion of Feedback #2. I wanted to make this comparison because I wanted to show that although the white Non-Hispanic population has the biggest rate (43.6%) of delinquency allegations compared to 37.8% allegations for Black Non-Hispanics, White Non-Hispanics have a significantly lower rates (24%) of transfer to criminal proceedings than Black Non-Hispanics which their transfer to criminal proceedings is at 56.7%. It is also worthy to mention that White Non-Hispanics are the only group in the report where their delinquency allegations are significantly higher than their transfer rate to criminal proceedings. Both Black Non-Hispanics and Hispanics have a higher rate of transfering to criminal proceedings thatn their rate of delinquency allegations. For the final version of my chart I decided to place the labels on top of the designated bars because in feedback #2, the person stated that they couldn't figure out if the labels are for both bars or one of the bars. I wanted to improve on the perceptibility of the chart and that is why I included the percentages at the end of each bar and changed the bars to horizontal rather than vertical so the label is straight and easy to read. To improve the aesthetics of the chart I removed the background color and gridlines.