Abhinit Parelkar - UX/Interaction Designer

Infographic Design

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Work     >      Infographic Design (Print-based)


Infographic Design (print-based) 

Artboard 1.png

Storytelling through visualization.


Duration: Last two weeks of February 2018 | Role: Infographic Designer


Data visualizations allow people to readily explore and communicate knowledge drawn from data.
— Interactions Magazine
Human beings are visual creatures. Visualization works from a human perspective because we respond to and process visual data better than any other type of data. In fact, the human brain processes images 60,000 times faster than text, and 90 percent of information transmitted to the brain is visual.
— Persuasion and the Role of Visual Presentation Support: The UM/3M Study


The project had following objectives:

  • Utilize a real world data-set to visualize meaningful information.

  • To come up with a proposal document.

  • The visualizations must be aesthetic and adhere to Kosslyn's graph design principles.

  • Must utilize Few's taxonomy for plotting graph relationships.

  • The output must be in a standard print size (tabloid) 11 x 17" vector graphics.

  • A final design report.


The Open Sourcing Mental Health Survey was conducted in 2016. With over 1,400 responses, it aimed to examine the frequency of self-identified ‘mental health issues’ among tech workers by various responses (i.e. gender, occupation, location, company, etc). The data set can be found here.

For our infographic design, we were in search of the answers to the following research questions:

  1. How many survey respondents with a tech role currently claimed to have a mental health issue?

  2. Which US state has the most tech workers who identify a mental health issue?

  3. What types of tech roles had the most self-identified mental health issue?

  4. What type of mental health issues do tech employees self-identify?

Our challenge was to visualize the answers from 1,434 records in the data-set.


We had a time constraint of two weeks to perform research, design, and write an analysis report. Our output was in a standard print size document (PDF) 11 x 17 ".


Our infographic design proposal consisted of the following digital sketch:


We proposed to incorporate Few's taxonomy for plotting graphs:

  • Classification of multiple distribution - Describes and compares responses among work positions. Side-by-side bar graph suits best for comparison.

  • Parts to whole - Describes the aggregate quantitative value(s). We've used pie chart and stacked bar graph to demonstrate the relationship.

  • Nominal comparison - Describes the comparison of two quantitative value(s). We've used bar graphs to demonstrate the relationship.

  • Geospatial - Provides a visual comparison of quantitative values per US state. We've use the choropleth map to demonstrate the relationship.


Our main motive was to make the information/data visually accessible and aesthetically pleasing.

The aesthetic quality of a product is an integral aspect of its usability.
— Dieter Rams

 We upheld Kosslyn's three goals for graph design as follows:

  • Connecting with the audience - The intended audience is tech employees, companies, and anyone who wants to learn about the self-identified mental health issues in the tech. industry. Only relevant information is shown, and it is appropriate for its intended audience.

  • Direct and hold attention - The principle of distinguishability and principle of salience. The colors of primarily blue and mango-yellow are complementary and distinctive, and furthermore, we ran the graph through the Sim Daltonism, an open-source software that allows us to visualize colors as they are perceived with various types of color blindness. After testing 3 other color palettes, the blue and mango-yellow color palette appears to be the best choice because they remained distinctive throughout the test.

  • Promote understanding and memory - Readers are able to see the dramatic difference between the U.S. states with California accounting for 60% of tech workers with self-identified mental health issues compared to values ranging from 0% to 13% for the other countries.

Our journey until the 8th iteration of this infographic design project.

Through the analysis of multiple feedback (from peers and the instructor) and an unsettling feeling of the overall aesthetics, we decided to iterate further. We wanted to reduce visual clutter. It was time to keep it simple by removing unwanted/non-functional elements and to utilize the space for incorporating some useful elements.

Simplicity is the Key to Brilliance.
— Dieter Rams

Thus, we arrived at our final output:

PDF version


R graphics (R Studio), Adobe Illustrator, Swiss style color picker (http://swisscolors.net), and Microsoft Excel.


This project was a two-person based team effort.

The team had following contributions:

Carolyn Rojsutivat (Researcher & Writer): Carolyn performed all the research activities which included identifying (variables) & cleaning of the data set (using Microsoft Excel), Few's classification for plotting graphs, and writing analysis report.

Abhinit Parelkar (Designer): I performed all the design activities which ranged from R-programming (plotting of the graphs), testing color palettes (using Sim Daltonism), designing 17 iterations of infographic (using Adobe Illustrator), and uphelding to Kosslyn's three goals for effective graph design.

The infographic result (with 17 iterations) was possible due to a strong collaboration between a researcher (Carolyn) and a designer (Abhinit). 


The project was in itself unique. The ability to make a design decision along with a researcher was an exhilarating experience. I learned the following valuable lessons and would love to improve further:

The metrics I registered: 

  • The unintentional use of offending/judgemental language "Mental Disorder/Mental Illness" under the graph titles - We learnt that representing the dataset in a right and acceptable way is the key responsibility of a designer to deliver the values through design.

  • The lack of story in the infographic - We learnt that adding a story gives user a context about what the infographic is trying to convey.

  • We made the infographic more simple by removing the non-functional elements, for example, we removed the "red" colored texts which served no contextual meaning thus causing a visual clutter and imbalance.



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