Mapping Irma, but not really…

We’re discussing data visualization nowadays in my course, and today’s topic was supposed to be mapping. However late last night I realized I was going to run out of time and decided to table hands on mapping exercises till a bit later in the course (after we do some data manipulation as well, which I think will work better).

That being said, talking about maps seemed timely, especially with Hurricane Irma developing. Here is how we went about it:

In addition to what’s on the slide I told the students that they can assume the map is given, and they should only think about how the forecast lines would be drawn.

Everyone came up with “we need latitude and longitude and time”. However some teams suggested each column would represent one of the trajectories (wide data), while others came up with the idea of having an indicator column for the trajectory (long data). We sketched out on the board what these two data frames would look like, and evaluated which would be easier to directly plot using tools we’ve learned so far (plotting in R with ggplot2).

While this was a somewhat superficial activity compared to a hands on mapping exercise, I thought it worked well for a variety of reasons:

  1. It was a timely example that grabbed students’ attention.
  2. It generated lively discussion around various ways of organizing data into data frames (which hopefully will serve as a good primer for the data manipulation unit where we’ll discuss how data don’t always come in the format you need and you might need to get it in shape first before you can visualize/analyze it).
  3. Working backwards from a visualization to source data (as opposed to from data to visualization) provided a different challenge/perspective, and a welcome break from “how do I get R to plot this?”.
  4. We got to talk about the fact that predictions based on the same source data can vary depending on the forecasting model (foreshadowing of concepts we will discuss in the modeling unit coming up later in the course).
  5. It was quick to prepare! And quick to work through in class (~5 mins of team discussion + ~10 mins of class discussion).

I also suggested to students that they read the underlying NYTimes article as well as this Upshot article if they’re interested in finding out more about modeling the path of a hurricane (or modeling anything, really) and uncertainty.

Data Science Webinar Announcement

I’m pleased to announce that on Monday, September 11 , 9-11 am Pacific, I’ll be leading a Concord Consortium Data Science Education Webinar. Oddly, I forgot to give it a title, but it would be something like “Towards a Learning Trajectory for K-12 Data Science”. This webinar, like all Concord webinars, is intended to be highly interactive. Participants should have their favorite statistical software at the ready. A detailed abstract as well as registration information is here
https://www.eventbrite.com/e/data-science-education-webinar-rob-gould-tickets-35216886656

At the same site you can view recent wonderful webinars by Cliff Konold, Hollylynne Lee and Tim Erickson.

Envisioning Data Science Webinar Series and Call for Input

Webinar Series: Data Science Undergraduate Education

Join the National Academies of Sciences, Engineering, and Medicine for a webinar series on undergraduate data science education. Webinars will take place on Tuesdays from 3-4pm ET starting onSeptember 12 and ending on November 14. See below for the list of dates and themes for each webinar.

This webinar series is part of an input-gathering initiative for a National Academies study on Envisioning the Data Science Discipline: The Undergraduate Perspective. Learn more about the study, read the interim report, and share your thoughts with the committee on the study webpage at nas.edu/EnvisioningDS.

Webinar speakers will be posted as they are confirmed on the webinar series website.

Webinar Dates and Topics

  • 9/12/17 – Building Data Acumen
  • 9/19/17 – Incorporating Real-World Applications
  • 9/26/17 – Faculty Training and Curriculum Development
  • 10/3/17 – Communication Skills and Teamwork
  • 10/10/17 – Inter-Departmental Collaboration and Institutional Organization
  • 10/17/17 – Ethics
  • 10/24/17 – Assessment and Evaluation for Data Science Programs
  • 11/7/17 – Diversity, Inclusion, and Increasing Participation
  • 11/14/17 – Two-Year Colleges and Institutional Partnerships

All webinars take place from 3-4pm ET.  If you plan to join us online, please register to attend.  You will have the option to register for the entire webinar series or for individual webinars.

Share Your Input

The study committee is seeking public input for consideration in their upcoming report which will set forth a vision for the emerging discipline of data science at the undergraduate level.  To share your input with the committee, please fill out this form.