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Social mobility

Objective 

Making data meaningful and accessible using various forms of visualization.

Solution

A physical data installation showing the social mobility comparison between parents and their children. This installation would live within a public building or policy office to encourage conversations and discussions around the topic. This exploration is only a prototype of what a full installation could look like.

Purpose/Mission

Encourage conversation around factors influencing social mobility.

 

Project

2018, Communication design + Data visualization

Client

Carnegie Mellon University, Communication Design

Team

Josh LeFevre

Duration:

5 weeks

Tools

After Effects, Illustrator, Photoshop, Physical prototyping, Laser cutter, Wood, Acrylic, U.S. Census data, Allegheny County data, and Excel

My role:

Design strategist, Data analyst, Creator,  

 
 
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Key features

 
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  • Puzzle in geographic/cartesian form.

  • Physical model that reflects the idea of Pittsburgh being hilly.

  • Parental social mobility hangs below the board as the “foundation.”

  • Student social mobility rises from eh board.

  • Comparison between neighborhoods

  • Each colored layer has meta data engraved to allow taking apart of the model and delving into the data.

 
 
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01

Understanding the problem

 

Social mobility is a complex issues that affects everyone but is difficult to explain and even more difficult to see in the world around us. So, how does making the invisible social mobility scores of 20.3, 80.5, etc influence decision making. This problem is so huge and usually boiled down to a single number, I wanted to make the data speak for itself and be intractable. The more layer for each neighborhood means a positive factor contributing to the overall social mobility score measured by the height of each stack.

 
 
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02

Exploratory Research

 

The exploratory research consisted mostly of digging through data bases and compiling them into one excel document to determine social mobility factors.

 
 
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03

research synthesis

 

In general, the social mobility scores between parents and students is within 1-2% difference. meaning that after adjusting for inflation (educational, economic, etc) student’s social mobility scores remain similar to their parents on the aggregate. However, the factors playing into each score do vary.

 
 
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04

Ideation

 

Here I began exploring the facets of data physicalization that would need to be considered and implemented. While also testing the ideas of physical data visualization with peers. Their brought me to realize that in order to layer the depth of information I wanted to show, that 2D aspects would not be enough nor leverage the completeness that a 3D model could provide.

 
 
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05

Concept development

 

I created small prototypes to test comprehension, feasibility, and form factor

 
Evaluating size, engraved meta data, and assembly

Evaluating size, engraved meta data, and assembly

Staked layers

Staked layers

 
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06

Early Cut prototypes

 

I created several early physical prototypes, including this one to inform the final form factor.

 
 
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07

Presentation

 

The final form inspired a lot of buzz around social mobility and peeling back the layers to better understand the differences and possible interventions. Overall, this was considered successful making the data clear and tangible.

 
 
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08

Reflection + Next Steps + My role

 

Reflection

I was initially focused on creating various heights based on social mobility. As I worked with the data, I realized I had to run some predictive models and that the small differences were too little meaningfully show physically without misrepresentation. So, I went back to making the invisible factors that make up social mobility visible.

I found the colors useful to discuss the weights or importance of different type of data that could be categorized and easily seen with a quick look.

Next steps

  1. Present model prototype to Allegheny county

  2. Re cut the data for clarity

  3. Add physical data key

  4. Complete the prototype after further feedback from the county and local citizens.

My role

  • Data collection

  • Data evaluation

  • Design implementation strategy

  • Form decisions

  • …basically everything