Visualization Critique (2023)

[venkatrajam]

For the first assignment, find a simple, stand-alone, static visualization and write a short critique on: How effective is it at what it aims to do? What works well and what doesn't? What could be better?

You comment should contain:

Title of the example with one image (add url reference if it is online)
Short critique (could be in paragraphs or bullet points)
You can edit or update your comment anytime after you post, but do not make multiple comments. If your github username is not your actual name, include it in the comment/comment title.

Check out past works 2022 & 2021 for reference, but select new examples.

[AhmadThahaHussain]

Critique on the graph "The changing nature of middle class jobs"
https://www.nytimes.com/interactive/2015/02/23/business/economy/the-changing-nature-of-middle-class-jobs.html
• It takes time to understand the graph with the graph alone. The second image (below) is required to understand what is happening in the graph.
• It doesn’t show what happened in the time gap between 1980 and 2014.
• The lines should be curves and not straight lines which could be misleading.
• The gradient in between the lines doesn’t explain anything.
• It is hard to deduce how the shares lean towards the jobs that are more open to women.
• We don’t know which line represents which job and even if we do, it is hard to hover since the bottom part of the graph is particularly crowded.

[kashyapine]

Anmol Kashyap
22M2241

Source: Thomson Reuters, Turkey Earthquake Visualization, March 2023

Positives:

• The data is represented with form. A big circle indicates a larger magnitude of earthquake making it easier to understand at a glance.
• The larger circles are overlapping smaller ones which creates an impact i.e., the high-magnitude earthquakes are more deadly than low-magnitude ones as they seem to be very small (visually represented by fitting inside the larger ones).
• The circles, also in a way represent the area it is being affected as the bigger the earthquake, the more damage it does thus impacting a larger land mass.
• The visualization also includes the previous 30 days' data to provide more information rather than counting from day 0.
• Some circles are tagged with numerical values to induce scale in viewers' minds and to accurately understand the chart.

Negatives:

• The overlapping circles make it a bit difficult to understand the chart in technical terms.
• The chart seems only to be targeted towards layman viewers, it is not very distinct and informative when it comes to a more detailed perspective.
• The linear timeline from left to right is not clear. One cannot draw out an accurate number of aftershocks as the data is very cluttered and clubbed together. It shows an impact of how deadly the earthquake was but fails to provide proper information as to how many aftershocks occurred.
• Even though horizontally it follows a timeline (time duration; number of days) but it doesn't follow a timeline vertically up (year-wise). This may create confusion in viewers' minds unless they look up to the title mentioned (country and year).
• For the Turkey earthquake with 7.8 magnitude, it seems there were multiple quakes at the same time due to the overlapping visuals of the circles. This is physically not possible because, at a point in time, there can be only one earthquake. The distance between the centres of the circles could be increased to create a distinct representation.
• Few of the larger magnitude earthquakes are tagged with their numerical value to create a perception of scale but it is only done for the larger ones. Whereas, if the scale is not mentioned for any of the smaller ones, how can the viewer assume the entire range?
• For the earthquakes; 'Turkey 2011', 'Phillipines 2013', 'Mexico 2017', all have a magnitude of 7.1. Then how is the placement of these events on the graph plotted? Is it according to a hierarchy of the names of the country (first letter basis) or is it according to the time the earthquake occurred? Is it according to how deadly the earthquakes were or is it according to how many aftershocks they had? The placement of these event data on the chart is not very clear as to what basis.
• The colour fill for the circles is a pro as well as a con. It helps in distinguishing one earthquake from another when there are a lesser number of quakes or if one quake is very high in magnitude and another very less comparatively. If the quakes are of similar magnitude, the same colour fill fails to distinguish the earthquakes creating a smudgy-looking graphic. Maybe an option without the fill could have been explored.
  Eg: Can be observed from the Japan 2011 earthquake where the timeline seems like a smudge of purple.

[AnujsAmbhore1]

Title ; The companies Disney owns.

Anuj Ambhore, 21u130031, B.des 3rd year

Link ; https://9gag.com/gag/a9E8n6o

Critique ;

• If it weren't so big and complicated, this data visualization would  have been quite useful and instructive.
• There is a lot of information to add, and the designer's selection of font size, line weight, circle sizes, etc. didn't turn out so well.
• The shape of Mickey Mouse is highlighted, resulting in three different circle sizes. The wider circle of companies appears to be the most significant to viewers, although this isn't necessarily the case.
• Additionally, it gives the impression that businesses in smaller circles outside of the Mickey Mouse frame are less significant. Also, it is never a good idea to use the yellow and white color combination.
• There were much excessive other forms used inside the large rings. Smaller circles, rounded rectangles, and squares with sharp corners are also seen.
• Finally, reading the small texts in such a large representation of data must be done at the best resolution possible.

[lakshrajpal1803]

Laksh Rajpal (21u130028), BDes 3rd year

URL: https://public.tableau.com/app/profile/healthdataviz/viz/EatingDisorderAwarenessWeekInfographics2023/PrevalenceTileMap

Strengths:

• The data is presented in a simple and easy-to-understand manner.
• The chart's identity is relevant to health, making it suitable for its purpose.
• The organized grid arrangement of tiles enhances clarity and ease of interpretation.
• The chart effectively condenses a large dataset, simplifying complex information for better comprehension.

Weaknesses:

• The representation of the chart does not resemble the world map clearly, which might lead to confusion.
• The seventh circle's color is visually confusing as it appears closer to the last circle.
• Instead of aligning the countries so close to each other, it would be more user-friendly to spread them out accurately across the page, making it easier to locate specific countries quickly.
• The highlighted countries lack a clear purpose, such as indicating the highest prevalence rates or higher population rates.
• Geographical location is irrelevant to the data, so more focus could be given to other factors like quality of life index, average weight or incidences of various diseases.
• To better convey population data or the number of diagnosed cases, consider using the circle size as an additional visual cue.
• Generally the color green represents better health, the color scheme should lean more towards the positive side of the prevalence rate.

[Ketaki007]

Who grossed the most ?

This visualisation explores the performance of the top 6 film distributors from 1995-2020 - Walt Disney, 20th Century Fox, Paramount Pictures, Sony Pictures, Warner Bros and Universal.

It aims at understanding the effect of factors such as quality over quantity and audience perception on the success of a film distributor

https://i0.wp.com/www.printmag.com/wp-content/uploads/2021/03/16b8f0_48616fb7c55e47dcb3f84c787bc15631mv2-scaled.jpg?resize=1000%2C1321&ssl=1

The information encoded here is :

Time (on the main axis)
Total released films (on the radial axis)
Annual gross of all films (size of the circle)
Film distributors (colour codes)
Market share (on horizontal bar chart)
Audience perception (IMDB star ratings)

What works :

• The chart combines a wide range of factors with systemic coding of information through colour and proportions. A good balance in use of text, colour, shapes/sizes and images.
• The exploratory visualisation conveys important insights - one of them being - the shift in Warner Bros. quality/quantity strategy. We can see that Walt Disney too, followed the same (quality over quantity) strategy to become the leading distributor over the past 8 years.
• The sizes of the circles enveloping the details highest grossing movie of the year - when viewed across years, gives a complete understanding of the performance of a movie that year and across other years.
• Radar chart fits the 25-year data in a more compact manner than a linear chart.
• The designer neatly presents a “key” / “how do I read this” instruction.

Gaps/ drawbacks :

• The visualisation misses interesting information like - events/ evolution of movie screenings/ technology/booking methods over the years which may have an effect on the gross earnings. For eg : there is a sudden drop in the number of films made and the annual gross made by all the distributors in 2020 (which clearly would be an effect of Covid 19 on the industry). Highlighting such events on the chart would add more meaning and reasoning to the chart.
• The distributors with the same gross earnings might lie away from one another on the vertical axis. One might earn huge profits from a small amount of movies and other from larger number of movies. In this case, the reader might confuse the circle on the farther end to be higher in value
• The horizontal bar chart may clarify the confusion mentioned above, but it goes almost unnoticed
• Audience perception is encoded as the IMDB rating which is shown in the form of star ratings. This format does not add to the comparative power of the chart. The annual gross of the movie in relation to the audience rating could’ve been shown as a secondary (outer) radar chart

[Vaish0204]

Pabboju Vaishnavi | 22m2249

Source: https://www.behance.net/gallery/169039001/Objects-launched-into-space?tracking_source=search_projects|data+visualization

Data Visualization project: "Objects launched into space" by Federica Fragapane

What worked -

• The form looks visually pleasing and unique to look at.
• The color palette is not jarring or highly contrasting. The minimum number of colors being used made the data easier to look at.
• A large amount of data here is shown with reduced complexity.
• The abstractness of the visual made me curious about the data hidden within.

What didn't work-

• The number of lines in each band (representing the number of objects launched in each year) is almost illegible.
• The intention behind the chosen form is not clearly conveyed.
• The shape of the form does not add any value to any parameter of the chosen data. It's highly abstract and not metaphorical in nature.
• Without the legend, the visual itself is completely incomprehensible.
• It presents the number of launches from each country but does not clarify whether they were successful.
• Reasoning behind choosing each line in the band (year) to represent 50 objects was not specified. If 1 line = 50 objects,
  cumulative launches with totals other than multiples of 5 cannot be displayed in the visual.
• Even though each year's data is supposed to be considered band width-wise, the length of each band, which has no data parameter attached to it, makes the visual quite misleading at first glance.

[Mukul3110]

Economic Exodus in the Americas - Data Visualization

Mukul Mahajan
21u130029
Bdes, 3rd Year

URL: https://nicolasrapp.com/studio/portfolio/economic-exodus-in-the-americas/

Pros :

• Given a data of how much someone could theoretically boost his or her standard of living (as measured by per capita GDP) by crossing borders.
• The data is clearly labeled and easy to read, hence it is easy to note the amount of migrant encounters from various countries.
• Varied width of the arrows representing the amount of migrant encounters helps us to compare the data, for eg: we can easily tell that Mexico has the highest number of migrants.
• The color scheme is quite subtle, it adds contrast and allows for easier visual comparison. The use of different shades of orange to represent GDP of the country makes it evident and easy to interpret.
• Monthly encounters in the U.S have also been given for further analysis.

Cons :

• The data is not very accurate. The data is based on the number of migrant encounters by the U.S. Border Patrol, which does not necessarily reflect the number of immigrants who have actually entered the country.
• The visualization does not distinguish between different types of migrants as stated in the description (But economics are only one factor in the hemisphere’s immigration dilemma: Political conflict in Nicaragua and Peru; gangs in Honduras, Guatemala, and El Salvador; and systemic breakdown in Cuba and Venezuela are also driving people to leave their homes behind.)
• The monthly encounter has been given but we cannot state the accurate number of immigrants.

[SamarthDhanuka]

Comparison between the caffeine and calorie contents of various food items.

Samarth Dhanuka
21U130001
B.Des, 3rd Year

Pros-

• The data consists of a vast variety of items that people generally consume for their caffeine requirements.
• The chart draws parallels between some famous food items as well as activities related to the amount of calories they contain which makes it easy to relate to the number of calories being consumed.
• The chart can help one find a suitable food based on their caffeine and calorie requirements/restrictions.

Cons/Improvements-

• The X and Y axis are not placed on the sides. They are placed in between such that their intersection is not the origin (0,0) which creates a massive confusion.
• The quantity of any of the items is not specified so it is impossible to know how much of the item contains the mentioned quantity of caffeine and calories. Using average as data points for this is very risky and doesn’t help the user in any way.
• The chart does not give any information on the type of food. It would be helpful to differentiate between solid food, coffee related items, tea items etc.
• The size of the items varies and it is impossible to tell which part of the item should be considered for extracting the quantity. Large objects like the 1ltr Coke bottle have an enhanced effect of this problem.
• The chart could outline some threshold for safe consumption and health issues that can be caused by excessive intake.
• The items in blue used as relation points are placed outside the plotting area of the axes and hence it is hard to tell if they contain 0 caffeine or if they are not to be considered for checking caffeine content.
• Various symbols have been used but there is no legend and it is hard to find a relation between items with the symbols and how the variation in their sizes corelate.

[Anshika1105]

Anshika -21u130027

Url: https://www.visualcapitalist.com/sp/mapped-the-colossal-cost-of-plastic-pollution-by-country/

The data visualization shows the "colossal cost of plastic pollution" by country. The poster is well-done in terms of its design and use of color, and it is easy to understand the main message. However there are both pros and cons to this visualization.

Pros:

• Data Labels and Scales: all relevant data points are properly labeled, and the scales on the axes are indicated to prevent misinterpretation.
• Accessibility: all the countries are arranged in alphabetical order and continent wise which makes data easier to read (suggestion: the countries with high statistics could have bigger font sizes to create a hierarchy & better segregation ).
• Visual elements : the visualization honestly represents the underlying data without distorting or misrepresenting it. Does not contain visual elements that mislead the audience such as exaggerated scales. Another point, the use of coordinates eases the visualization of data especially when it comes to ranges.
• Aesthetics: Circular (radial axis) representation makes it look more interesting, is more compact for huge data.
• Graph: good thing that they made the graph more like a donut instead of a circle and did not start from the center which avoided clutter.

Cons:

• Colour & design: the contrast between the adjacent sectors of the circle could have been more for a better understanding.
• Accuracy and clarity: the circle could have been divided into more concentric circles for better accuracy & precision.
• Time frame: The data doesn't clearly mention the time frame of the information and doesn't talk about the relevance of the data or when it was recorded.
• The data doesn't provide the relationship between costs and population or the degree of pollution or the number of water bodies or areas covered by water that a country owns.
• Simplicity: The map in the center turns out to be a little cluttered. The zoomed-in view was unnecessary.
• Comparability: it may become difficult to compare data especially if it's on the other side of the graph .Bar graph could have been more effective in this case.

[ANOOF-PK]

Champions Of UEFA Champions League History.

Anoof P K - 21U130023

Link - https://www.behance.net/gallery/145712955/SPORT-UEFA-Champions-League-History?tracking_source=search_projects_comments|data+visualization+sport

Pros:

1. Every single point has been thoroughly reviewed every single year.
2. By looking at every year, you can easily understand the visually.
3. The colors of each team name are simple to recognize as a team in any European country.
4. The number of continuous champions can clearly be observed.

**Cons / Improvement: **

1. Understanding the information of lines will take time.
2. Some countries' colors appear to be nearly the same.
3. Should put the team's logo close to the team name so that it is easier to see without looking at the team name.
4. Continuous Champions Numbers should be placed on Team Information where they can clearly be observed.
5. Instead of a single graph, numerous graphs of every ten-year gap should have been created.
6. Adding the top three manager word colors to the graph. Also in the Top 5 Team too.

[AditiChintey]

Escher's Gallery

Pros :

1. A very interesting graphic way of presentation, integrating Escher’s art into it.
2. The data is color encoded based on the styles of art created by Escher in his lifetime.
3. Not only does it manage to give a timeline to the works of art produced by him, but it also segregates their styles.
4. There is specifications for the pieces of art that were famous, when they were made, and his popularity timeline.
5. Visualizes his most created art styles and their popularity.
6. It is interactive, which makes it easier to understand the style of art.

Cons :

1. Though information is Quantitative, it's tough to understand the numbers without reading the legend.
2. The data brings area into play instead of number, which misleads in comparing the art works produced in one age to another.
3. Difficulty in understanding what the style of art means or represents for anyone without prior knowledge.
4. Non-distinct seperation between his his age timeline.

[SarthakRao]

Sarthak Sridhar Rao, 19u130012

"The Night a Train Destroyed a Town", published by National Post in 2013, describing the events leading up to a deadly derailment of 72 tankers carrying crude oil in Lac Megantic, Canada.

Positives:

• Details. One can study every aspect of the tragedy –causes, series of events, geography, time, speed, elevation, scale, etc.– and the more technical aspects like braking systems and mechanical features are explained using annotated diagrams separately.

• Illustrating the entire mile long train, and coding the tankers that exploded/derailed, puts into perspective the severity, especially along with the human for scale illustration.

• Parallel coordinate chart shows the acceleration of the train as it rolled down the hill. Theoretical calculations show it should've reached much higher speeds (~170 as opposed to 100kph), providing insight into the braking activity.

• Geospatial plots show sequence of events at the sight of derailment and firsthand affected areas around it.

• The infographic goes beyond stating the series of events unfolding, also touching upon statistics such as crude oil movement by pipeline vs trains in Canada, and known safety measures which if implemented may have prevented the mishap.

Limitations:

• For those looking for a quick summary of the incident, the graphic feels too cluttered–your attention is pulled towards different places, sequence is scattered.

• Parts of the information are still very text heavy, which need to be read first for context.

• For a graphic titled "...destroyed a town", it only barely touches upon the statistics related to deaths, injuries, ecological impact, etc.

• While time of events are mentioned in text, no temporal plots are made (the data could've been added to existing maps/charts)

[yashbhrani]

Too late to start?
Visualization Critique by: Yash H Bharani (22M2244)

Artist: Anna Vital
Source: https://www.google.com/url?sa=i&url=https%3A%2F%2Fblog.adioma.com%2Ftoo-late-to-start-life-crisis-infographic%2F&psig=AOvVaw0qARt8_6nypQUHpBqCwaJD&ust=1690882067159000&source=images&cd=vfe&opi=89978449&ved=0CBEQjRxqFwoTCJiGoOLQuIADFQAAAAAdAAAAABAI
Year of issue: 2014

About: This infographic depicts the ages of the founders when they started the company. It wants to cut across the point that most companies are founded around a specific age group when people undergo a quarter-life crisis or mid-life crisis.

Pros:
-> I found it as a novel mode of showing the information.
-> The design of the information is minimal and aesthetically good.

Cons:
-> The information representation is misleading because of the following aspects:
1. It has arbitrarily taken 100 among the top 2000 companies in the world, and it also doesn’t claim to have randomly
selected them. So the conformational bias might be at play here.
2. The line originated from the specific number in the multiple of 5 and not from a range of numbers.
3. It claims causality for a phenomenon that could easily be correlational, as many confounding variables are at play here. Eg.
4. The startup starts at 25 because that’s when people finish college and are full of energy. And same is seen around 35
because that’s when they usually marry, get settled, and have enough savings to take on the risk. And it reduces because
people grow old and find it difficult to catch up with the new generation.
-> The graph data is not readable on smaller screens.

[Rajdeep115]

Where does data visualization come from?
by Fabrice Sabatier (Source)

What it aims to do?
Collates the information of contributors in the field of data visualization.
The diagram encodes the contribution, their authors, links denote their discipline/s, dotted links denote the no. of contributors in two connected discipline/s, and a chronological distribution of contributors within the span of 250 years (1765-2015)

What works?
It consolidates a wide range of data (250 yrs.) into a simple temporal chart.
One can very well stay with the chart for quite a long time as they study/ practice data visualization.
Linkages also reveal when people contributed the most and the least.
A gap between every 5 bars of contributors makes it really easy to count.
The stroke width of linkages at the bottom between two disciplines encodes the no. of contributors, hence we can notice which link has contributed the most.

What could have been better?
Connection of the authors to the respective profession/ disciplines are encoded twice, once by direct linkages and by color coding them.
Instead of drawing linkages between authors and their feilds it would have been interesting to see a rough analysis of the contributions (maybe through categorization like "maps", "grids", "pictograms", etc.) and how authors are connected to one another (someone has cited someone/ developed on someone's work)
Some of the colors (like shades of green and yellow) are too similar to be distinguished in a quick look.
Although the X- axis encode time (years), the Y- axis seem to be arbitary and left only to cater to the logistics of making the linkages.
The markers of years in the radial charts at the bottom are curved, which has no semantic relevance. and some disciplines which has less contributors are omitted from representation.
The gridlines for years do not encompass the entire map, hence it's difficult to locate some authors on the time scale.

[MansiKhedekar]

Mansi Khedekar (22M2253)

Unstoppable network

Source - https://multimedia.scmp.com/culture/article/SCMP-printed-graphics-memory/lonelyGraphics/202211A312.html

What works?

• The infographic has presented the data simply and minimally with pastel colours.
• The way they have chosen to visualize the data brings emphasis to their achievement. They did this by encoding the year on the horizontal axis and the length of the tracks on the vertical axis and chose triangles (Peaks) to connect the two data points.
• The data displayed in the centre of the infographic (in red) is conveyed well as against the year-wise progress data as mentioned below.

What doesn't?

• The triangles make it slightly unclear if the vertical axis has an origin or if the values written at the vertex of the triangle are the lengths of that particular triangle.
• The progress of railway tracks across the years at first glance looks like constellations.
• It is also difficult to immediately understand if tracks were essentially expanded or if they are distinct new tracks.
• There is no context to the location of the tracks (no borders, no identifiable landmarks)
• The first few clusters of tracks (2008 to 2011) are not separated well.

[Rajdeep115]

Name: Vinay Kumar (22m2250)

Source: https://www.srijan.net/how-we-do/innovation/data-visualization-crop-production-in-india

A scatter plot of area vs. production talks about the key trends in crop production in India Over the 12 years (1998 - 2010)

What Works
It is capable of taking into account upcoming data as well as the expected horizon for prediction.
Colors are contrasting to distinguece between the various data types.
The data is associated with the bubble area, so the hierarchy of data values is visually displayed.
Growth/Decline in crop production over the years are possible to visualize.
This is an interactive graph.

Possibilities of Improvements
It's a visually messy graph.
The graph has very small data points and random places to select.
Randomization in the visualizing the state vise crop production, makes impossible to select or guese the state.
Left side graph, so much data is stored in the 0m + 10m range that it wouldn't make sense to come up with a conclusion.
The name of a state is not shown on the graph, so it's difficult to figure out which states are there.
The rice, sugarcane and wheat selected constitute the 3 layers, but they do not appear to be connected in hierarchy.

[sparshGupta24]

Field of Commemoration

by Valentina D'Efilippo

https://www.informationisbeautifulawards.com/showcase/375-field-of-commemoration

About:
The visualization documents countless deaths in wars across the 20th century. The visualization and the data provided make clear that war was a near-constant characteristic – allowing just two years of peace – in the last century.

What went right:

1. The poppy holds significant symbolism as the emblem of remembrance in Commonwealth states, providing a powerful foundation for the creator's narrative.

2. Through this visualization, one can easily deduce how the frequency of wars escalated after World War II. The aftermath of WWII saw the establishment of the United Nations, an essential event aimed at resolving conflicts and promoting global peace. However, this period also witnessed the granting of independence to many countries, leading to border issues, and was marked by the tensions of the Cold War. The noticeable increase in the density of poppies after WWII raises thought-provoking questions about the UN's success in curbing wars and fostering lasting harmony.

3. The creator follows a set of guidelines established by her religiously throughout the visualization. She creates an exception for the events of both world wars, which is intentional I feel. It adds impact to the narrative and made it easy for me as a viewer to traverse through the visualization.

4. She also adds cues which instruct the user on how to go about reading the visualization.

What could have gone better:

1. Time on 2 axis: I am not sure if it is a good approach. I understand the intent of the creator in doing this, which is to add an extra dimension to what would otherwise be a normal timeline. It was only effective for certain edge cases.

2. It is not made clear if there is an existing denotation for regions through colors on the basis of which these guidelines were formed.

3. It is not made clear if the change in the design for the stem in some cases has any meaning or not.

4. The creator chose to label certain conflicts, the rationale behind choosing these conflicts is not clear.

Additional Comments:

• Since every data point is not accompanied with details, we cannot deduce exact data from the visualisation. But I feel that the creators intent was to show a trend, rather that specific data.

[princeagarwa]

How Gender Affects Pay
URL: https://www.washingtonpost.com/graphics/2017/business/women-pay-gap/

Prince Agarwal
22M2247
Interaction Design

The visualization shows the pay gap between men and women across different jobs.
Data Type:
Gender: Binary, Independent variable
Jobs: Categorical Data, Independent variable
Number of people (gender-wise): Interval Data, Dependent Variable
Salary: Interval Data, Dependent Variable

What works:

1. Clear visualization of the pay gap between genders across different professions.
2. Clear visualization of the proportion of gender across different professions.
3. We can also see the difference in the number of jobs in different professions.
4. Hovering on an individual data point tells details.
   
5. Jobs are ordered from the women concentric to the male concentric.
6. Slope Chart to show the salary median change between 1960 and 2015.
   
7. Clear visualization of the profession in which women outearn men and by how much.
   

What Doesn't work and suggestions:

1. Clustered and chaotic visualization.
2. Some sorting mechanisms can also help.

The Daily Routines of famous creative people
URL: https://podio.com/site/creative-routines

Prince Agarwal
22M2247
Interaction Design

The Visualization titled “The Daily Routines” is the daily routine representation of some famous creative people in History. The data represented here is not the average or represents the whole life of that person but a specific period of time as recorded in diaries, letters, and other documentation.

Critique:

What Works:

1. It is interesting to see and compare how famous personalities spend their time.
2. The content can capture the attention of audiences interested in habits and lifestyles and inspire them to optimize their own.
3. Bar representation method is justified since there is only one linear temporal data point.
4. High Contrast in the color makes it easier to differentiate between the sections.
5. Interactive elements like toggle make it easier to compare.


What Doesn’t works

1. The reliability and accuracy of the data sources may be questioned.
2. Daily routines involve subjective details that are challenging to quantify or verify so some information can be misleading.
3. There is a lack of context and no explanation about the data, like the rationale behind certain routines or how they contributed to an individual's success.
4. There is no mention of the time in which they lived and what part of their life they followed this routine.
5. It is difficult to understand whether the people are arranged in chronological order or if they are randomly arranged.
6. Calculating the hours spent on each activity is difficult and must be done manually.

Quick Suggestions

1. Adding a timeline and arranging the people in chronological order.
   

2. Adding a photograph of the person and giving the link for more information.
   

3. Total hours label on each bar to reduce the efforts in the calculation.
   

[abhishekshirsagar]

Abhishek Kshirsagar
21U130030, B.Des 3

On Their Way: the Journey of Foreign Fighters

https://www.informationisbeautifulawards.com/showcase/2323-on-their-way-the-journey-of-foreign-fighters

The visualisation is a Sankey diagram representing the flow of people referred to as 'foreign fighters' leaving a country and going to ISIS in Syria.

• The diagram accurately represents amount of flow of foreign fighters but lack of arrows make it difficult to understand the direction of the flow.
• Inconsistent scale on the vertical axis (representing the country's population) makes it difficult to compare and relate the populations of the countries.
• No key insights could be gained by looking at the visualisation at a glance. Using the layout of world map to position the rhombuses rather than a linear scale of distance from Syria could improve understanding due to familiarity with maps.
• The size of the rhombuses represent the Muslim population in the country, but the scale is split into discrete steps which does not accurately display the information. Using a continuous scale in the sizes of the rhombuses would be better.
• The colour value of the rectangles shows the ration of the leaving foreign fighters to the total Muslim population of the country which can be used to easily identify the most affected countries.
• The visualisation does not communicate the time period to which the data belongs.
• The title of the chart is missing.

[Yash2412kothari]

Yash Kothari
21U130033 B.Des 3rd year.

CO2 EMISSION VS. VULNERABILITY TO CLIMATE CHANGE

URL: https://mir-s3-cdn-cf.behance.net/project_modules/fs/38b1a228174005.560ac2601e048.jpg

What's working well:

• The visualization is clear and easy to understand. The different colours of the circles make it easy to see which countries are more or less vulnerable to climate change, and the size of the circles corresponds to the amount of CO2 emissions each country produces.
• The visualization is visually appealing. The use of colour and negative space is effective in drawing the viewer's attention to the important information.
• The analysis indicates that the regions most vulnerable to climate change primarily consist of non-human inhabited areas, such as Africa.
• The visualization is well-labeled. The text on the map provides clear and concise information about the data being presented.

What could be improved:

• The visualization could be more accurate. The data for this visualization is from 2010, so it may not be up-to-date.
• The data for vulnerability to climate change is based on a number of factors, so it is difficult to say definitively which countries are the most vulnerable.
• The data is visualized based on CO2 emissions, weighted, and expressed in geographical areas. The intensity of CO2 emissions is influenced by the area and population density of each nation.
• Unfortunately, there is no available data for Antarctica. Despite its susceptibility to climate change, the current visualization lacks information regarding this region.
• The arrangement of circles in descending order seems to serve the purpose of ranking nations based on their CO2 emissions and vulnerability to climate change. However, this ranking could be easily achieved through a simple tabular presentation as well.
• An alternative approach could involve using maps to represent the bubbles based on regions, which may reveal additional patterns related to the issue.
• The current focus of the visualization appears to prioritize aesthetics rather than facilitating the identification of patterns within the data. This approach could limit the opportunity for in-depth visual exploration.
• The geographical map merely categorizes nations based on their CO2 emissions or vulnerability without providing explicit rankings. An improved design could involve coding CO2-emitting nations according to the ND Gain Index, enabling a more informative representation of patterns.
• The visualization could be more detailed. The circles on the map are relatively small, so it can be difficult to see the differences in size between them. Additionally, the visualization does not provide any information about the specific countries that are most vulnerable to climate change.
• The visualization could be updated to use more recent data. This would help to ensure that the information being presented is as accurate as possible.

[anniketmohalik]

Anniket Mohalik
21U130008 | B.Des

[Data Visualization State of the Industry, 2022]
(https://flowingdata.com/2023/04/05/data-visualization-state-of-the-industry-2022/)

PROS

• It is a simple and easy to understand visualisation

CONS

• It is hard to compare to squares until it is adjacent
• No number is there in the square which makes it hard to compare
• Limited use of colour can make it confusing
• Aesthetically not appealing
• Size of each industry is not given to get an idea of percentages
• Due to small sample size some to spaces are missing

[Madhumithan333]

Madhumithan, 21u130002, 3rd yr b.des

which canine comes out as top data-dog?
https://informationisbeautiful.net/visualizations/best-in-show-whats-the-top-data-dog

Critique

1. The dogs are too clustered with lots of overlapping that it affects readability.
2. While the data is said to have used six different criteria we are not made to know how it was calculated.
3. It has prioritized data of a lesser importance thus causing visual chaos.
4. Most of the data regarding the size of the dogs are incorrect .
5. Too much information has been encoded in every single picture of a dog that it is very hard to get a basic sense of.
6. The same image has been used to represent different dogs while the font selection is bad leading to mis identification of certain dogs

[anniketmohalik]

Anniket Mohalik
21U130008 | B.Des

[Data Visualization State of the Industry, 2022]
(https://flowingdata.com/2023/04/05/data-visualization-state-of-the-industry-2022/)

PROS

• It is a simple and easy to understand visualisation

CONS

• It is hard to compare to square until it is adjacent
• No number is there in the square which makes it hard to compare
• Limited use of colour can make it confusing
• Aesthetically not appealing
• Size of each industry is not given to get an idea of percentages
• Due to small sample size some to spaces are missing

[avanibhagdi]

Avani Bhagdikar, 21u130032, B.Des Y3

Topic: The Top 5 Causes of Death in Every Country

Sources:
worldlifeexpectancy.com
ourworldindata.org
who.int
NYRequirements.com

• The chart aims to show the following information: country name, country life expectancy, and the top 5 causes of death in 183 countries.

• It lacks specificity and aims only to provide a general overview.

• In terms of intentionality, the chart does convey what the title suggests.

• The chart does not aim to provide statistics or numerical values for the causes of death: doing so would perhaps over-complicate the data and add clutter to an already complex-looking piece.

• In continuation of the earlier point, the chart is then misleading to the viewer, who may interpret the varying lengths of colour as being representative of absolute scale- seeing it in terms of length, not colour. The fact that a scale is not present should be made more obvious, since the viewer may attempt to impose a scale onto it otherwise.

• Since the form that has been chosen is extremely common, it is easy to understand to some degree even without the presence of a legend, since it is likely that the viewer already has prior context when it comes to understanding that type of data visualization: greater the length, higher the ranking.

• While the legend enables one to understand the chart in greater detail, even without it, it is possible to understand that most countries have the same disease ranked 1 on their list (coronary heart disease). Other such conclusions may also be drawn based on observation of the colours alone.

• Since colour is one of the focal points of this visualization, the contrast could perhaps be improved- as of now, several of the colours look very similar, further decreasing the readability of the chart.

• A pattern of concentric circles emerges from the coloured bars that are stacked next to each other, which looks aesthetically appealing.
  -Since the bars that represent the various ranks ( 1/ 2/ 3/ 4/ 5) are all aligned to each other, it is easy for the viewer’s eye to follow one particular rank along the circle that is formed by the close proximity of the bars.

• The semi-circular arrangement of the bars diminishes the overall strength of the visualization as it focuses on aesthetics first and function second.

• The information is difficult to process since the angle of the lines keeps changing with every occurrence since they are aligned to a circle.

• The font and typography also suffer due to this- it is difficult for the viewer to constantly have to adjust their eyes.

• This chart is difficult to read even at a large scale, and is not suitable for viewing on smaller screens.

• The ranking of countries and also of the causes for every country is done in an intuitive fashion: the countries are arranged by life expectancy, and the causes are arranged by their prevalence.

• While the order of the countries does make sense, that information is barely legible and the viewer may not be able to comprehend it at first: despite the logic being present, it is not presented well.

• Thus, despite having an underlying system of logic to it, the information fails to have the desired impact since it is not organized well enough.

• Should the creator wish to tell a story by means of this visual, they will have to improve its readability as a whole.

-An alternative method of organizing this data could perhaps be to have 2 donuts set within each other: one may depict the countries, and the other, the causes of death, and the same information could be conveyed by a series of linkages.
-Perhaps varying levels of opacity or stroke width could be used to communicate their ranking (1, 2, 3, 4, 5); the colours could convey the name of the disease, and the linkages could guide the viewers' eyes to the country.
-Another option could also be to use a modified version of the visualizations generated by Circos: some examples may be seen below: (explanation below)

-The redesigned version that I can imagine would have the following features: a layout that mimics the ones generated by Circos, better color contrast that the original chart, and one which is less misleading with respect to the meaning associated with the varying lengths of colour. The issue with this system is that it is not feasible to use with a large dataset. The number of countries/ conditions that can be represented with such a visualization is thus greatly limited.

Having reached the end of the course, and having explored many data visualizations, each with their strengths and weaknesses, I have a few more concepts that would perhaps result in a better visualization- classifying countries based on geographical location; representation of the disorders within the countries as point sources connected by lines across countries, rather than as bars- this runs the risk of becoming cluttered, but is worth a try? and lastly, perhaps a chloropleth would also help- with each country being coloured using concentric regions (as observed in heatmaps)- the most prevalent disorder by country being the focal point, and all else radiating outwards.

That's all from me!
Cheers,
Avani

[JuneSardar]

Source : https://iibawards-prod.s3.amazonaws.com/projects/images/000/004/231/large.png?1569257429

Data Exploration on the smallest countries in the world.

Pros :

1. Instead of using filled circles of varying sizes to make scores from 1 - 5, a mix of blank and filled circles ranging from -2.5 to 2.5 has been used. This reduces the load while reading as blank circle automatically gives that impression that the country is 'missing' the particular parameter.
2. Layering of the information in concentric circles definitely lets the viewer correlate between parameters and ask questions like -
   i. 'why countries that have lower Civil Liberties score also have lower Women in Parliament' and the exceptions to this.
   ii. 'why Bhutan ranks so far behind Bahrain, even though their World Governance Indicator scores aren't that different.'
   Cons:
3. Arrangement of the countries in a circle makes it difficult to compare two countries
4. The countries are arranged cyclically according to the distance from the equator but this doesn't give the viewer an estimation of where the country actually lies geographically on the map. Hence, we can miss out on correlational insights regarding geographic location, neighbouring countries etc. For example, in the top left part of the circle, European counties have better scores particularly but since countries like Mongolia, Moldova etc come in between, one might not come to that conclusion.
5. Size of the indicator score circles corresponding to the scores is very ambiguous as there is no specific diameter that marks a specific score.
6. Since along with the size of the circle, the colour fill is also a variable and defines a score, one can get confused about the scoring since a filled small circle means a higher score than a blank large circle.
7. Due to the indicators being in concentric circle, one gets baited by the illusion that circles in the innermost ring are larger and more prominent (since spacing is less), even though they might be of the same size as the circles on the outermost ring.

[AnjaneshIndranil]

Nuclear Slowdown

Pros:

1. Each country has been assigned a separate color.
2. Good legibility for the wide range of colors used.
3. Makes it easy to see changes in new reactor constructions and reactors connected to the grid.
4. The use of curved lines gives a sense of progression.
5. Includes the major events in the timeline that may have led to change in nature of the graph.

Cons:

1. The graphs are overlapping making it difficult to see data in many places.
2. Difficult to find the start or the end of graphs for some countries and hence hard to track along the timeline.
3. Difficult to compare data between the countries.
4. Hard to know the name of the country by the color of the graph as the country name is annotated at a random place on the graph itself.
5. The red background makes it difficult to see the design for a longer period of time.
6. Difficult to know exact numbers of reactors on the graph as y axis has only multiples of 10 noted there.
7. A part of the graph is out of frame making this design loose the data.

[manishverma612]

Manish Verma
21U130014, B,Des 3rd Year
Source : https://bm.ge/en/article/quotnabijebi-romlebic-gadadgmulia-ekonomikashi-adekvaturia---archil-koncelidze-mtavrobas-afasebs/75336

Top 50 websites in the world

Pros:

1. The stand-alone static visualization keeps things simple and easy to comprehend. It avoids clutter and presents the information in a straightforward manner.
2. The use of a circles is a suitable choice for showcasing rankings, and it is visually appealing with the contrasting colors for each circle.

Cons:

1. Contextual information regarding the parameters used to gauge each website's popularity appears to be missing from the visualisation. Users could have trouble understanding the meaning of the rankings or how the websites were evaluated without this information.
2. Site information is missing: The visualisation would benefit from including quick labels or comments for each circle that listed the URL and possibly gave a little explanation of the category or goal of the website. Users who are unfamiliar with some of the above websites would find it more useful with this extra information.
3. It would be fascinating to see how these websites' popularity rankings have evolved over time. A time series component in the visualisation might offer insightful information and give the display more depth.
4. There doesn't appear to be any logical order to the websites' display in the bar chart. Users could have trouble identifying any underlying patterns or trends among the top 50 websites without a defined sorting criterion.

[shivaniv25]

Transportation Cluster

Pros:

• Good usage of color to differentiate between longitudes, gradationally
• The variation in diameter of a circle, representing a city with multiple routes
• The area with the most favorable topography to construct an airport accessible is visible, also the demand of airports,
• A densely populated area of the world

Cons:

• Multiple cities in closer proximity will overlap the circle and also the route density
• No clear representation between continents, and countries is visible
• Data is visible in a cluster format, we can only analyze the area where airports are located on the map that too in spiderweb format on the world map
• Cannot quantify the number of routes seeing this data
• Route lines are so dense, the city with lesser routes are not visible
• Cannot conclude which airport is at what distance from each other

[PoojaKumari56]

The Hollywood Insider
This visualisation explores for every major film for 2016.
https://informationisbeautiful.net/visualizations/the-hollywood-insider/

Pooja Kumari
22M2256
M.Des 2nd Year
Interaction Design

Y-axis represents the budget recovered
X-axis represents the budget in $million
The size of circle represents the worldwide gross
Colours of the circle represents different film genres

The visualisations main goal is to provide insights into a film's overall success, taking into account many essential factors such as critical reaction, audience feedback, international gross revenues, production budget, and the proportion of the budget recovered through box office income. The visualisation seeks to provide a better picture of how different films performed in these categories in 2016.

Concept & Design: David McCandless v1.02
Research: Stephanie Smith, Pearl Doughty White, Ella Hollowood
Code: Tom Evans, Paul Barton, Neil Muralee

Pros:

1. The visualisation makes excellent use of colour, resulting in an easily legible and understandable presentation.
2. The size of the circles, which indicates each film's worldwide gross, has been built with an interactive element. When users hover over a circle, it displays a complete summary of the corresponding film, delivering detailed information for a more in-depth comprehension.
3. The colour palette chosen for the visualisation boosts its aesthetic appeal and contributes to a user-friendly experience, making it aesthetically appealing as well as easy to interpret.

Cons:

1. Some of the movie names are missing. When you hover over the circle, then it shows the detailed information.
2. It would have been interesting to include the variables responsible for certain films' considerable budget recoveries, even when they received negative reviews from both audiences and critics, for example ‘Meet the Blacks’. Understanding these contributing aspects could provide useful insights into the intricacies of box office success and shed light on the various factors that influence a film's financial performance.

[AmrutaBailke]

https://www.jotform.com/blog/wp-content/uploads/2023/05/image-history-of-life-1.png

What works…
Color coding of information
Covers multiple layers of information using the radial pattern that builds upon each previous layer
Hierarchy in the delivered information is maintained by the use of colors highlighting the central graphic whereas use of gray on the edges of the image
Easy to understand the time for which any particular area lasted
Complex graphics of animals are replaced by silhouettes, so it gets just enough attention and does not overshadow other information.
Blend of 3D graphics with the 2D radial timeline
Use of grid to mark out years
The gradual change in geography can be noticed

What does not work…
Earth formation graphic not very clearly indicative - can be read as organism formation

What could be better?
What caused or what changed over the change in each era can be added

[akashdas58]

Reference:
Wimbledon Champions Of The Open Era
by Simon Beaumont
www.informationisbeautifulawards.com

Pros:

• The infographic is kept simple and minimal for the viewers to help us accurately analyse the winners of the Wimbledon Singles Title since the start of the open era in 1968.

• The infographic also tells us about the winners by their nationality with radials representing each of the 6 decades.

• The colour code of the infographics matches with the Wimbledon tournament colour theme which makes it appealing.

• The infographic uses the accurate size of translucent circles to show the number times he has won in a decade on the radial.

• The white lines also separates each player and if he is from a different country the line extends more and joins with the center thus grouping by nations.

• Each player’s nationality flag and no. of winners are written with their name.

Cons:

• Takes time to understand the player and the number of times they have won.

• The white lines in the radial are not so contrasting so the separation is difficult between players. The white lines are not contrasting and mixes with the light background colour.

• The size of green translucent circles cannot be easily compared as they are not close to each other in the radials so the value cannot be analysed properly.

• The radials kind of give hierarchy and somehow decrease the value of winning in past decades as the past decades are of smaller circles.

• The innermost radial is of decade 1960s but the Wimbledon has begun from 1968 so it is wrong information.

• The years written are written in different orientations, so difficult to read.

• The title cannot be read properly and not the highlight as it has different orientation and low contrast.

[RaghavSamodia1]

source: https://www.behance.net/gallery/110024405/Stolen-paintings

The infographic shows how many famous paintings were stolen over time. It shows that the number of stolen paintings has increased in recent years. The infographic is visually appealing.

Pros:

1. Unconventional method used here to mark the year is visually appealing, and the increase in stroke size augments the increase in the frequency of thefts

2. The infographic also describes the painting well

3. legend is easily comprehended

Cons:

1. the weird shape of the marker makes it challenging to determine the exact year

2. the authors are arranged alphabetically and not in a specific manner. Authors could be arranged by their birth year, eliminating the need for the year-painted marker.

3. museums stolen from are connected by different dashed lines, which is hard to distinguish and understand.

4. distance of the final lines from the timeline is excellent, making it difficult to read.

[Dhairya0802]

Dhairyasheel Pawar
21U130037
B.Des Third Year

The data link:
https://in.pinterest.com/pin/358739926563776794/

Pros:

1. A circular distribution to show seasons divided into twelve parts seems like a smart idea for easy and logical understanding.
2. The visualization is successful in showing comparative distances of different locations from the airport.
3. Different style of points used for showing the duration of average time spent at the place is also shown which is good for intuitive understanding.
4. Usage of colorful lines gives it an attractive and noticeable quality.

Cons:

1. Due to the usage of harmonious colors, distinguishing the purpose of a visit to some tourist destinations is difficult.
2. The visualization shows the approximate distance and not the actual distance of every destination from the airport.
3. The line representation creates confusion and visual disturbance as a whole while identifying the purpose of the visit as a whole.
4. The name of the places labeled are creating congestion in the visual aesthetics of the data.
5. The time duration could be also misinterpreted as the lines stretched over a month can also be considered for the duration.
6. The places that are radially distributed aren’t essentially showing the direction at which they lie from the airport which can also be misinterpreted.

[karantanna-kt]

Karan Tanna
22M2246 | 2nd Year MDes Interaction Design

Title : Data Visualisation of Resume by Travis Tester
Souce : Behance : Data Visualisation of Resume by Travis Tester

Usually resumes are done in cliche listed format. I came across this very interesting way of visualising resume. It intrigued me and made me analyse it further, and seemed like it was inspired by London Underground map but by analysing I discovered that its a mix of timeline style visualisation.

The left side of the visualisation showcases some of his more prominent talents and skill sets he is most proud of. Moving to the right, you can see how these disparate skills have woven into a job he has held, or sometimes how that skill applies to multiple jobs. Then, those jobs weave into a timeline that begins in 2010 and runs to 2023, and shows his education and work history.

Pros : What works ?

1. Colour coding of various position and associating it with eachother was interesting and insightful.
2. Timeline shows chronological events of his educational and professional life.
3. Branching shows that there were overlaps in the role and that was interesting.
4. The connection helps to understand the overall sense of his work/educational progress.
5. Colourblind friendly colour scheme (from Tableu)

Cons : What can be improved ?

1. The visualisation style is very interesting and seems eye catching. However, it is not easy to understand on first glance.
2. The connections made with skills are interesting. However, it confuses the user while reading it.
3. The colour pallet & line thickness is very less and visual clutter on left is heavy.
4. Less emphasis was given to organisation worked. It was not noticable on the first glance.
5. Start and ends of roles are confusing and not very clear.
6. Legend could have been more elaborate.
7. Thicker lines ( from timeline ) are starting abruply in certain cases or not clear why it starts where it starts.
8. This resume might not be OCR friendly or might not be recruiting process friendly.

[jishnuthewalker]

Source: https://www.nytimes.com/interactive/2018/02/23/sports/olympics/fractions-of-a-second-composite-images.html?mtrref=undefined&gwh=7BEBFF8221428B8D48CD25A62BE03BA8&gwt=regi&assetType=REGIWALL

Jishnu Diwakar | 3rd Year Bdes

Pros:

• the visualisation shows the complexity of movements over time made by Olympic athletes.
• the speed of the movement is apparent.
• the visualisation is visually appealing.
• the path followed by the athelete is clear.

Cons

• at points the visuals data becomes complicated and harder to read.
• the different poses are difficult to look at individually.
• there is too much details because images are used instead of illustrations.
• there is no accurate sense of timing for the visuals, it's hard to tell how fast the movement was in real-time.

[devaharshareddy]

Deva Harsha Reddy, 22M2243
“Happy people, Happy Planet?”

Website - https://informationisbeautiful.net/2023/the-winners-of-the-world-dataviz-prize-2023/
https://d33wubrfki0l68.cloudfront.net/5ba77c29-f30f-4918-b909-ea47adae1795/Happy%20People,%20Happy%20Planet.png

Information visualized here -

• Map shows the happiness and ecological footprint of all countries.
• Happiness is calculated based on the money spent on tangible products (consumerism).
• The colors red, green and blue indicate the ecological footprint of countries.
• The smile types represent the happiness of various countries.
• Size of the smiley represents the size of the population.

Critique-

1. The world map with smileys is easy to understand the happiness but there is no specific value given to the smileys in terms of happiness index.
2. Same situation occurs with ecological footprints as both of the variables are defined to be low, medium and high which are represented through three colors and smileys.
3. The population can be easily related as the size of the smileys varies independently.
4. Overall, the map provides easy understanding of various countries across continents in terms of Ecological footprint to achieve consumerism.
5. Here we can observe that European and North American countries are having a large ecological footprint to achieve happiness unlike the Asian and African countries which have large populations but have lesser ecological footprint and happiness.
6. The attention mainly goes to the color of the smileys rather than the smile itself.
7. For example, India has a prominent green smiley due to its population and the amount of green is higher than the other countries. This at first glance shows a positive state but later we can notice that India is equally unhappy.
8. The area of figures is perceived higher in Channel's rankings than the color and curvature. So as per the smileys, the population can be identified first, followed by ecological footprint and then happiness.
9. As the smileys are enclosed by the map behind the background, it is easy to understand it across the continents by grouping up the smileys. (Gestalt Law - Enclosure)
10. The comparative X-Y charts indicate the happiness and ecological footprint among developed and developing countries across the time in 10 years.
11. This gives more detailed scaling of the happiness and footprint, but it would be more accurate if the actual values for extreme countries are given.
12. The graph clearly points out countries which (are happy with lesser ecological footprint) have sustainable development.