Dangerous Scooter Data Presentation

I recently saw a data presentation about electric scooter injuries. It shows data on what types of injuries occur, what type of accidents occur, and the helmet wearing percentage of riders. The data is from two emergency departments in Southern California. The target audience is people who ride or may consider riding electric scooters. The goal of the presentation is to convince people that electric scooters are more dangerous than one might initially think and that they should take precautions such as wearing a helmet. It is mostly effective at doing this but could have a clearer message. I think they could make the helmet wearing message more prominent. It is small and at the bottom. The percentage is strikingly low and they don’t do much to draw attention to it. A visualization of the 4.4% would really help it out. The title sort of implies a message of “scooters are dangerous and should be avoided “rather than “riders need to take the risks of scooters more seriously and wear helmets”. They could also strengthen their message by highlighting how common serious injuries and accidents are by using the color code in the donut chart to indicate severity rather than commonness (which is already being shown by the donut chart). The graphics do a good job of emphasizing the danger aspect and drawing the readers attention.

Link to graphic

Colorful, Emotional, Interactive Sound Cloud

Interactive map of sounds organizes nonverbal “vocal bursts” into categories like surprise, contentment, awe, and pain.

In a study released on February 5th, UC Berkeley scientists presented their statistical analysis of “vocal bursts”— wordless exclamations — in a cloud of colorful points organized by their emotional connotation. The webpage is interactive, so a viewer can hover the mouse over a point and the sound will play automatically. The scientists were able to group the exclamations into 24 different kinds of emotions, whereas earlier studies capped the emotional variety to 13.

The data in this sound map are the over-2,000 vocal bursts, recorded by the researchers, by 56 male and female participants from the U.S., Kenya, India, and Singapore. The participants included both professional actors and non-actors, and the vocal bursts were responses to “emotionally evocative scenarios.”

The audience of this data visualization is primarily other experts in psychology and human behavior, although it is accessible for any user. As to its goals, according to the press release, “the map could theoretically guide medical professionals and researchers working with people with dementia, autism, and other emotional processing disorders,” to practice recognizing the different nonverbal cues. It also provides insight into human behavior.

It’s unclear what the ‘click and drag’ function of the webpage is supposed to accomplish. Otherwise, the webpage is effective at displaying the data because the sections are clearly labeled and colored as the vocalizations blend from one emotion into the adjacent ones.

Welcome to the 2019 Data Storytelling Studio

We are swimming in data – “Big” and small, global and personal. And we are also facing complicated problems like Climate Change and inequality whose stories can only be told with data. The need for public understanding of data-driven issues is higher than ever before. But raw data doesn’t make a good story… and that’s where you come in.

This is not a data visualization course.

This is not a statistics course.

This is a storytelling course.

This class is focused on how to tell stories with data to create social change. We will learn through case studies, invited guests, examples, and hands-on work with tools and technologies. We will introduce basic methods for research, cleaning and analyzing datasets, but the focus in on creative methods and media for data presentation and storytelling. We will consider the emotional, aesthetic and practical effects of different presentation methods as well as how to develop metrics for assessing impact. Over the course of the semester, students will work in small groups to create “sketches”, each using a different technique for telling a data-driven story.  Think about a sketch as a half-realized project; where you have implemented just enough of the most important details of the idea in order for us to understand your vision. A sketch is NOT a fully realized presentation of a data story. For the final project, students will have the chance to expand on one of these sketches to create fully realized presentation of a data-driven story. Why is this called a studio? This course has few lectures and lots of group project work time.

The course is open to all technical levels and backgrounds. We will prioritize students with a strong background in one or more of the following areas: journalism, software development, data analysis, documentary, visual and performing arts.

The course will have a special focus on food security data. Most examples will use data related to this topic, homework will be related to it, and sketches and final projects must be connected to it as well.  I welcome a broad definition of that topic.

Learning Objectives

  • Students will learn techniques for finding a story in data, building a basic set of tool-assisted data analysis skills
  • Students will build things that tell data-driven stories with a rich set of digital and non-digital tools, online and offline
  • Students will practice arts- and rhetoric-based approaches to telling data-driven stories
  • Students will learn to connect data stories to meaningful, situated social action
  • Students will learn basic techniques for measuring the impact of data-driven storytelling
  • Students will learn basic ethnographic and anthropological approaches to identifying and researching audiences


  • Spring 2019 Semester
  • Category: Hass Arts
  • Units: 3-0-9
  • Meets Tuesday & Thursday from 11am-12:30pm in room E15-341
  • Undergrad (CMS.631) and Graduate (MAS.784/CMS.831) meet together
  • Admission is by permission of the instructor – please fill in this quick enrollment survey


Instructor: Rahul Bhargava <rahulb@mit.edu> Research Scientist, MIT Center for Civic Media

Faculty Sponsor: Jim Paradis – Robert M. Metcalfe Professor of Writing and Comparative Media Studies