submitting assignment 3

02_activities/assignments/participation/viz1_assignment3_markdown.md

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+## dataset link: 
+
+https://open.toronto.ca/dataset/daily-shelter-overnight-service-occupancy-capacity/
+
+## What software did you use to create your data visualization?
+graphpad - prism
+
+## Who is your intended audience? 
+the general public of the GTA
+
+## What information or message are you trying to convey with your visualization? 
+I would like to show the rates of occupancy per sector, driving home the message that regardless of sector most shelters are at 100% occupancy right now (can see this with the concentration of points at the upper limit). There is thankfully fewer families needing shelters (fewer dots) and lower occupancy rates. However youth, women and men are usually shelters relatively equally.
+
+## What aspects of design did you consider when making your visualization? How did you apply them? With what elements of your plots? 
+I wanted to make sure that each shelter is represented so I chose a scatter plot, and I wanted to emphasize that most shelters are at occupancy therefore I made the dots semi-transparent so a concentration of colour would draw the viewers attention.
+I wanted to reduce visual anxiety so labels and titles are as minimal as possible. 
+I also used the viridis colour package to accomodate colour blind viewers.
+additionally, I used flat graphics vs 3D to reduce visual load and included the bars along with the individual dots to help the viewers see that women, men, and youth are relatively equal ( = everyone needs help)
+
+## How did you ensure that your data visualizations are reproducible? If the tool you used to make your data visualization is not reproducible, how will this impact your data visualization? 
+While my visualization was created on prism, I provide the excel workbook with the data I used and sheets to show how I manipulated the data to be processed for the graphs as well as a data_info sheet to explain
+## How did you ensure that your data visualization is accessible?  
+1. I used viridis colour package
+2. texts are all at least 12 pt font
+3. I used a dyslexia friendly font type (verdana)
+
+## Who are the individuals and communities who might be impacted by your visualization?
+I hope to impact the unhoused community with this visualization as the visualization is made to influence some positive change in the shelter situation in the GTA.  
+
+## How did you choose which features of your chosen dataset to include or exclude from your visualization? 
+I did not want the graph to be too busy and I wanted to drive home a clear message so I only included 2 variables and did not include any excess information. I chose to include shelters with bed occupancy instead of rooms because this data type shows exactly how many individuals are impacted as one bed = one person. With rooms you cannot grasp how many people are impacted from a glance.
+
+## What ‘underwater labour’ contributed to your final data visualization product?
+- work by the shelter staff to report these numbers
+- work by city analysts to coalesce and clean the data

02_activities/assignments/participation/viz2_assignment3_markdown.md

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+## dataset link: 
+
+https://open.toronto.ca/dataset/daily-shelter-overnight-service-occupancy-capacity/
+
+## What software did you use to create your data visualization?
+prism - graphpad
+
+## Who is your intended audience? 
+the public of the GTA, city councillors, government officials
+
+## What information or message are you trying to convey with your visualization? 
+message: the majority of shelters have less than 100 beds available, and only a few ~300. etobicoke falls behind the other locations by a great amount with both fewer shelters (fewer dots) with fewer number of beds (the max number of funded beds per location sits around 30-40)
+## What aspects of design did you consider when making your visualization? How did you apply them? With what elements of your plots?
+considering visual load/visual exhaustion: I chose soft, complementary colours as to not overwhelm the viewer. Graphics are flat vs. 3D for that same reason, making the visual easy to digest and not too busy.
+using the violin plot, I am able to show the range in availability between the different locations: Toronto and North York have a higher range of # of beds while Etobicoke has a very limited range of funded bed and their upper limit is much lower than the rest.
+accessibility: font sizes are all atleast 12, using a dyslexia friendly font and I bolded certain areas to make them more striking and eye catching.
+
+## How did you ensure that your data visualizations are reproducible? If the tool you used to make your data visualization is not reproducible, how will this impact your data visualization? 
+While my visualization was created on prism, I provide the excel workbook with the data I used and sheets to show how I manipulated the data to be processed for the graphs as well as a data_info sheet to explain 
+
+## How did you ensure that your data visualization is accessible?  
+1. I used font bolding to help draw attention and create priority in viewing certain aspects to make this viz more understandable
+2. texts are all at least 12 pt font
+3. I used a dyslexia friendly font type (verdana)    
+
+## Who are the individuals and communities who might be impacted by your visualization?  
+shelter users: hoping this visual will allow them to see the how many beds are funded in the GTA as well hoping that this will encourage more funding for more beds especially for those living in etobicoke.
+policy makers/government officials: hoping this visual will push for impact on the number of beds funding = more funding and budget to increase the number of beds. With the 2 visuals together I hope the message is clear that certain locations are not receiving as many funded beds as other and the majority are at capacity = we need to increase availability of beds and try to have more in locations like etobicoke.  
+
+## How did you choose which features of your chosen dataset to include or exclude from your visualization? 
+I did not want the graph to be too busy and I wanted to drive home a clear message so I only included 2 variables and did not include any excess information. I felt that it was important to categorize by the different locations in the GTA to highlight how different availability of # of beds are and I showed each facility as a dot to also show the differences in number of facilities per location.
+
+## What ‘underwater labour’ contributed to your final data visualization product?
+- work by shelter staff to gather data
+- work by city analysts to clean and organize data
+- work by city IT staff to maintain the website to make this data available to the public