cs4804-24c · nadavk2002 · Jan 23, 2024 · Jan 23, 2024 · Jan 30, 2024 · Feb 26, 2024
diff --git a/week1.md b/week1.md
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+https://pudding.cool/2017/03/film-dialogue/
+
+This link contains the visualization breakdown of popular Disney/Pixar films and the percentage of dialogue voiced by male-identifying characters versus female characters. I am the prime example of a Disney adult, primarily due to my raising my younger siblings through the magic and nostalgia of these films. It is interesting and impactful to note the evolution of the scripts written for many of these Disney movies because as the release dates become more and more recent, the balance of the male-to-female dialogue also meets more of an equilibrium. I chose this visualization because it felt important for me to understand the growth of feminism in films targeted toward a younger audience, so my younger siblings (both male and female) can better understand the social dynamics needed for success and equality. An interesting contrast among the movies in the visualization is that there are several outliers for movies with more prominent female dialogue, as well as those with female lead characters and still a dialogue imbalance. The visualization is a simple one, without color gradients or fancy geometry overlays. However, the significance of its quality is the shadows and shading with a few lines and font choices that are subtle but change how the viewer interprets the data. When scrolling through the website, the visualization drastically and dramatically transitions to much more complex and even beautifully overlaps the article beneath it. Finally, the visualization scroll ends with a gradient where upon cursor hovering there will display a movie name and the male-female split percentage of dialogue in a certain movie--depending on where the cursor is hovering on the bar. The transition from simple to more complicated visualizations on this page were very interesting and caught my attention as data that I had never thought about before viewing this page.
diff --git a/week2.md b/week2.md
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+![image](https://github.com/nadavk2002/reflections/assets/34312348/b94223cf-d5fc-42bc-b441-164f5a5a85bc)
+
+This simple data visualization is a line graph of the streaming service's monthly cost timeline from 2011 to the present. This visualization aims to portray the inflation and increase in the cost of the streaming industry. In a booming industry such as the streaming service industry, this visualization provides clarity to services that have drastically increased their prices in recent years. The colors used for each streaming company are well chosen, granted the services used in the visualization are the eight most popular on the market today. It is interesting how the designer chose for the layout to be on a dark background, and each color appears to glow or have a brighter saturation than the usual colors found in the color libraries I am familiar with. What seems even more difficult, however, is uploading the streaming service logo onto a certain coordinate in the plane and then surrounding the image with the same color its line represents. Given my current skillset, I don't know if I would be able to precisely round the corners of these images as well as round the corners of the lines when they are on a bend in the coordinate plane. This visualization was found on the dataIsBeautiful Reddit page at this user link: https://www.reddit.com/r/dataisbeautiful/comments/19cz93q/oc_streaming_service_price_increases_since_2011/
+While the visualization is simple and definitely more simple than last week's reflection, I did what I could to find a visualization that was closer to my skillset (while still a reach), a similar topic to my last reflection (movie-related), and one that is relevant to life today. There isn't anyone in my life who has not heard of or paid for at least one streaming service represented in the visualization I found, and the rise in cost is significant for many who may not have as much financial freedom as others. 
diff --git a/week3.md b/week3.md
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+https://youtu.be/Z_1Q0XB4X0Y?si=QgONLGj0ThqyvAGG
+https://flowingdata.com/2023/12/21/scale-of-all-the-things-compared-to-you/
+
+My reflection for this week may be slightly unorthodox given the usual requirements, my submission is a video animation of the visualization of size comparisons for things in the universe. I found this YouTube visualization by Kurzgesagt fascinating, not only due to my bias as a subscriber to their YouTube channel. For as long as I have been a Kurzgesagt viewer, the informative video stories have vivid and richly saturated coloring with complex animation that fills numerous different video lengths. Attached in the reflection is the link for this week's FlowingData blog, where the blog post is titled "The Scale of all the Things Compared to You," and the Kurzgesagt video is titled "You Are The Center of The Universe (Literally)." The twelve-minute-thirty-second-long video discusses the concept of size scaling on two fronts: big and small things. Kurzgesagt is a well-known channel with 21.7 million subscribers. Their objective in this video is to scale everything in the universe in comparison to their average viewer. The visualization of the measurements of things measured is beautifully animated to exponentially grow with the concept of the power of 10 in the positive or negative direction depending on the thing talked about. Kurzgesagt focuses on a stark shadowing method of color theory to portray their graphics, and their range of animation goes from linear motion to the facade of three-dimensional movement. I find the flow, bounce, and precision of the visualization are at a level that I cannot achieve and therefore cannot give much more critique for. The image below is an example of what I attempt to describe in terms of scaling, and the placement of lines, numbers, images, image movement, and color are all captivating and I truly am swept into continuing to intake the data being presented to me.
+
+![image](https://github.com/nadavk2002/reflections/assets/34312348/bb697298-45f0-4562-b24b-a861ef7c0d2f)
diff --git a/week4.md b/week4.md
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+![image](https://github.com/nadavk2002/reflections/assets/34312348/c0b7386d-1e7c-451c-a8ae-56acd31548c9)
+Source: https://www.reddit.com/r/dataisbeautiful/comments/1aj3x1d/adults_across_the_us_are_reporting_higher_rates/ 
+
+  This visualization, titled "Adults across the US are reporting higher rates of mental unwellness," is a line graph that effectively presents a decade's worth of data (2011-2021) on the increase in reported mental unwellness among adults in the US. I chose this visualization, because today is my 22nd birthday, and I have unfortunately had to deal with a loss due to mental health exactly a decade ago today. The significance for me and for the world today behind this visualization is to bring to light the seemingly never-ending mental health crisis. I think this visualization is difficult to read; the use of thin lines to represent individual states or territories and thicker lines for the overall US average provides both micro and macro perspectives, which is commendable but needs around ten seconds to understand. The color-coded distinction between women (in pink) and men (in blue) aids in quick visual interpretation. However, the overlapping thin lines can make the data appear more complex and harder to dissect at a glance. 
+  An interactive feature allowing viewers to isolate specific data sets might enhance readability, however, and better explain how adults' mental health is on a global decline. Despite being outdated, this graph remains significant as it underscores a concerning upward trend in mental unwellness reports, an issue likely exacerbated by recent global events like the COVID-19 pandemic, however, it is unclear what sample size this dataset is covering. It serves as a reminder of the ongoing need for accessible mental health resources and societal support systems. The style is aesthetically pleasing but could benefit from a better axis heading description or a distinct legend describing line elevation and trend. The small text at the bottom indicating the source and creation tool ("Source: CDC; Created with Datawrapper") adds credibility to the data presented. However, it could be made more prominent to ensure viewers can easily verify the information. This visualization is a powerful tool for raising awareness about mental health issues, despite its minor shortcomings. I look forward to reevaluating this visualization in class as it may be created in a similar manner to our recent A2, the subject is important to me, and I believe this visualization is within my skill capacity, and I would make lines bolder or touch up the aesthetics of the Y axis.
diff --git a/week5.md b/week5.md
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+![image](https://github.com/nadavk2002/reflections/assets/34312348/86b03d72-4693-4d96-a779-89d51fb370f3)
+![image](https://github.com/nadavk2002/reflections/assets/34312348/f4c7db13-2b5e-4d3e-94a5-fc20d161d10b)
+![image](https://github.com/nadavk2002/reflections/assets/34312348/10318518-dc68-4b31-963c-240cf05d21b7)
+https://public.tableau.com/app/profile/xinran.peng/viz/DataPlusMoviesStarterDashboard_17016561962340/Dashboard1
+This visualization found on tableau.com by Xinran Peng titled "Data+Movie: Into the Spider-Verse | Iron Viz: Student Edition 2024" is an extremely impressive multilayered visualization discussing everything regarding the Spider-Man superhero cinematic universe. The screenshots attached display how large the visualization is, and almost every element of this visualization is interactive with content. Multiple shapes, graphics, types of graphs, tables, etc, this visualization is the perfect final exam for this course, as it covers every aspect of lecture content that we have covered so far. I find it impressive that the creator was able to integrate so many viz strategies and methodologies into their work and to include animations as well as real-world data (which may be slightly outdated) and images that were easy to understand where placed. My critiques would be many points of redundant data, to many viewers I can see where many would disconnect the Spider-Man media and general animated movie data. Also, there is a lot of information in this visualization, and as I write this reflection I am still uncovering all bits and pieces, which would be too much to even write here. There are times when there can be too much going on, and while I think this visualization is extremely impressive, beyond my abilities, the modern average attention span unfortunately would not comprehend what is being discussed throughout this visualization. The theme and color schema for the layout are beautiful and are in respect with the films they adhere to, and I find the statistics for both the actors and animated films directory to be interesting. As mentioned several times, all non-text and non-background features are interactive, and I am curious as to which library or libraries the creator could have used to create this visualization, and, is it all credited at the source? What about when it needs to be updated? There is a huge influx of information one needs to intake for this visualization, and as time goes on the amount of information will only grow, how can this visualization be more simple? I would say split it up into different sheets, an interactive tab or menu at the top for one to navigate to like its own webpage, as opposed to one long infographic. 
diff --git a/week6.md b/week6.md
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+![image](https://github.com/nadavk2002/reflections/assets/34312348/89fd92b8-20a8-4a7a-9002-e0f7ee2c3db7)
+
+This visualization titled "The World's Top 50 Science and Technology Hubs" uses a combination of a world map and a bar graph to visualize the tech hotspots worldwide, and as repetitive as that sounds, effectively completes this task. The use of larger "zoom" circles on the map to represent the denser clusters in a region is a good design choice as it allows for quick visual comparison and understanding of the geographical distribution of the world's leading tech hubs. The addition of country labels in the bar graph is a nice touch, providing a visual cue that enhances understanding without needing to read and understand a graph with an X and Y axis. I also find the top 50 city list interesting as well. However, the size, font, and color of the circles on the map could potentially be confusing as it's not immediately clear what they represent and a legend or key explaining these features could be beneficial. The dark theme, while a nice aesthetic, might be difficult to read or see for some viewers, especially if viewed on a device with a smaller screen or in bright light conditions. I am noticing as I write this though I notice that there are interesting shadowed underlays for a few continents as well as text boxes that add historical meaning. This visualization, found on the Visual Capitalist website, is compelling because it provides a lot of information in a compact and visually appealing format. If I were to make changes, I would add a clear legend or key for the map, explaining what the different colors and sizes of the circles represent. I would also consider using a lighter theme or providing a toggle between light and dark modes to cater to different viewing preferences. Additionally, I would consider adding interactive elements, such as tooltips or pop-ups that provide more information about each plot point when hovered over or clicked on, to make the visualization more engaging and informative. This would allow users to delve deeper into the data if they wish, without overwhelming those who prefer a more high-level view.
diff --git a/week7.md b/week7.md
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+![image](https://github.com/nadavk2002/reflections/assets/34312348/eaab241a-bbe4-45cc-a5d7-774749ff2ade)
+
+![image](https://github.com/nadavk2002/reflections/assets/34312348/0a56403e-5f79-4f7b-b48e-8164ce6e6322)
+
+https://nathenry.com/writing/2023-02-07-seattle-walkability.html
+
+For the final visualization reflection, it would be interesting to apply my knowledge of GIS and geospatial visualization to this GPS map of Seattle, WA, which analyzes public locations and their relative distances according to time. I find this to be a very well-designed visualization, the article attached is a description of the design and technical features a user can interact with, with clearly labeled interactive list items and a nice fixed legend on the map. It may be an issue on my computer's end, but the map zoom and toggle features may have a little latency. The math that goes behind calculations of the distances I'm sure is extremely complex and impressive, I don't think I would change anything about that. If my MQP has taught me anything, then it is possible to improve the rendering speed of updated visualizations, and I would apply that knowledge by implementing a caching strategy or other optimization method where applicable to improve the refresh time and map rendering time when zooming or reconfiguring the toggle options. In a future edition of this work, I would hope to link the data to a worldwide or at least national set of data to then apply to the entire state or the entire country--what are the limits of this? What other public locations are not shown on this list that can be visited within 30 minutes? I would be curious to see the extent to which the 15-minute city concept is limited as well as expanded. Antique stores? Pharmacies? Shopping centers? If there are none in the city then how far away is it? I think this visualization has the potential to be at the level of a new generation of GPS when asking the right questions and growing it further. It would also be cool for each city block when highlighted or clicked on--which is a feature already well-made in this visualization--to show the streets that they are part of, say, 4th and Main to 5th and Broadway in New York, for example. This visualization is important and significant for the world's carbon footprint as well, and if it were a map-like software for the general public to use it would easily show the eager and busy population the nearest convenient locations to reach within their preferred distance; encouraging them to partake in either a walk or public transportation. This would work best in larger urban areas of course, which is why it is tested through this viz in Seattle.
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		https://pudding.cool/2017/03/film-dialogue/

		This link contains the visualization breakdown of popular Disney/Pixar films and the percentage of dialogue voiced by male-identifying characters versus female characters. I am the prime example of a Disney adult, primarily due to my raising my younger siblings through the magic and nostalgia of these films. It is interesting and impactful to note the evolution of the scripts written for many of these Disney movies because as the release dates become more and more recent, the balance of the male-to-female dialogue also meets more of an equilibrium. I chose this visualization because it felt important for me to understand the growth of feminism in films targeted toward a younger audience, so my younger siblings (both male and female) can better understand the social dynamics needed for success and equality. An interesting contrast among the movies in the visualization is that there are several outliers for movies with more prominent female dialogue, as well as those with female lead characters and still a dialogue imbalance. The visualization is a simple one, without color gradients or fancy geometry overlays. However, the significance of its quality is the shadows and shading with a few lines and font choices that are subtle but change how the viewer interprets the data. When scrolling through the website, the visualization drastically and dramatically transitions to much more complex and even beautifully overlaps the article beneath it. Finally, the visualization scroll ends with a gradient where upon cursor hovering there will display a movie name and the male-female split percentage of dialogue in a certain movie--depending on where the cursor is hovering on the bar. The transition from simple to more complicated visualizations on this page were very interesting and caught my attention as data that I had never thought about before viewing this page.
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		@@ -0,0 +1,3 @@
		![image](https://github.com/nadavk2002/reflections/assets/34312348/89fd92b8-20a8-4a7a-9002-e0f7ee2c3db7)

		This visualization titled "The World's Top 50 Science and Technology Hubs" uses a combination of a world map and a bar graph to visualize the tech hotspots worldwide, and as repetitive as that sounds, effectively completes this task. The use of larger "zoom" circles on the map to represent the denser clusters in a region is a good design choice as it allows for quick visual comparison and understanding of the geographical distribution of the world's leading tech hubs. The addition of country labels in the bar graph is a nice touch, providing a visual cue that enhances understanding without needing to read and understand a graph with an X and Y axis. I also find the top 50 city list interesting as well. However, the size, font, and color of the circles on the map could potentially be confusing as it's not immediately clear what they represent and a legend or key explaining these features could be beneficial. The dark theme, while a nice aesthetic, might be difficult to read or see for some viewers, especially if viewed on a device with a smaller screen or in bright light conditions. I am noticing as I write this though I notice that there are interesting shadowed underlays for a few continents as well as text boxes that add historical meaning. This visualization, found on the Visual Capitalist website, is compelling because it provides a lot of information in a compact and visually appealing format. If I were to make changes, I would add a clear legend or key for the map, explaining what the different colors and sizes of the circles represent. I would also consider using a lighter theme or providing a toggle between light and dark modes to cater to different viewing preferences. Additionally, I would consider adding interactive elements, such as tooltips or pop-ups that provide more information about each plot point when hovered over or clicked on, to make the visualization more engaging and informative. This would allow users to delve deeper into the data if they wish, without overwhelming those who prefer a more high-level view.