Crafting the User Experience of an Educational Blockchain Data Visualization Tool.




Over the last semester, my team worked with MapD to create an interactive data visualization for the blockchain and cryptocurrency, allowing new users to learn about the space.

MapD is an extreme analytics platform focused on optimizing big data analytics by providing solutions that harness the power of GPU processing. It currently houses multiple in-house demos, covering topics such as tweets, shipping traffic, taxi rides in New York City, shots taken by basketball players in the NBA, domestic airline flights, political donations in the US, mobile network quality, and the US Census. We were tasked with the creation of their newest interactive demo: blockchain and cryptocurrency.

The Problem

There is a large scale buzz about cryptocurrencies and the blockchain, however end user understanding of this technology is quite scanty due to the overly technical information present regarding it online. The aforementioned makes it difficult for a non technical user to grasp the fundamentals of the blockchain and therebt attempt to understand it.

All this combined makes it difficult for the user to understand the blockchain and relate it to aspects of their life. This project attempted to create relations between commonplace indicators such as stockprices, disposable income and blockchain fundamental indicators in a user friendly educational tool thereby enabling the end user to relate the blockchain to concepts in their daily life, all through an interactive and user friendly educational too.

Opportunity Areas

The scope of the project was to explore the needs of a common end user when it came to curiosity about blockchain and devise the best user interactions to grasp concepts through data visualization

Areas we wanted to investigate: areas that users are curious about, commonplace/daily life parallels to those areas, and UI of the educational tool.

User Research

Discussion Guide

To begin our user research phase, we created a plan covering high-level goals, assumptions about the user, specific research methods, the project schedule, team members, responsibilities, and a discussion guide. Within the discussion guide itself, we asked questions about demographics, interest levels, public perception, and existing educational resources.


User Interviews


We conducted user interviews with approximately fifteen different people, covering a variety of interest, education, and experience levels. Some users were completely new to the space, while others were seasoned veterans.

Secondary Research

In conjunction with our user interviews, we researched twenty-one different already existing blockchain or cryptocurrency implementations of data visualizations. We took note of each of the tracked parameters, deciding on pros and cons of each.


Research Insights

Key Insights

  • Onboarding is a pivotal component in order to acquaint the user to the interface of the educational tool the methods to interact with it.

  • The public perception and current understanding about the fundamentals and usage of blockchain technology is extremely distorted due to imperfect and scanty information presence.

  • The topics covered in current educational tools are incredibly misunderstood by the common end user, yet terms and defenitions from those educational tools are frequently used and quoted by the end users with confidence.

User Pain Points

  • Current educational resources for blockchain require a high-level of technical knowledge in the subject and a simple search for those technical terms is also of no help as it sends the user in a loop of recursive technical terms and defenitions.

  • Technical knowledge is easier to comprehend when presented alongside visual aids, which is currently not being done in a majority of blockchain educational resources that are present.


Identifying Key User Needs

To consolidate all of our insights, we created an affinity map of the information we found during our user interviews and secondary research. In conjunction to this, we created a preliminary user flow and general personas for potential users of the interactive demo.


Lo Fi Prototyping

All our low-fidelity designs were moving towards incorporating an effective navigation layout wherein the user can go to the topic he/she desires to view and maneuver through the various topics with ease. After finding twenty public data sets that would help users understand complex topics, we generated various visualizations and incorporated them into our designs alongside helpful explanations of the related topics.


Mid Fi Prototyping

We identified certain key features from our low-fidelity iterations (such as search, indexing, menu collapsibility) that were required for efficient functioning. We centered our designs around those features such that there are minimal distortions in the application’s functioning.


Hi Fidelity Prototypes

We wanted our designs to resonate with MapD’s brand identity which attributed to the selection of the blue color palette. Additionally, the minimal user interface enables the user to focus on the material being highlighted thereby offering an unhindered learning experience. Several of our data sets were uploaded onto MapD’s platform to create stunning interactive visualizations, such as the Bitcoin cryptocurrency overlay map shown below.



Usability Testing

We conducted twelve usability tests through where we assessed the learning process through data visualizations. We had three primary user testing goals:

  • Ensure that the user is able to navigate to the desired topic he/she wants to learn more about.

  • Enable user independence regarding toggling between data visualizations.

  • Enabling user interaction with the various data visuzations present on the system.

We used this feedback to quickly pivot in the right direction and continued iterating on our designs.

Concluding Thoughts

At the end of our project, we created multiple final deliverables, including a clickable prototype, a style guide, and a journey map. This map details topics, potential datasets, and feelings that are covered along each of the stages of the interactive demo.


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