Week 6 - Designing With Real Data

October 14, 2014


This week, we focus on extracting stories from data and crafting data sets (for those times when you don't have access to data)

Assignments Due Today

Class Activities

Extracting Information and Knowledge from Data (~30 minutes)

As a group, take one or two of the datasets below and dig into it. What did you learn about it? What stories, big or small, did you uncover?

Activity Results (Hide All Results)

Instructor Analysis (Hide Instructor Analysis)

This exploration didn't solicit the exact response I was hoping for, but it did introduce students to the idea that datasets have a story as well as some neat data visualization techniques. To make this more effective, it should probably be done in conjunction with a discussion around how real data has outliers, mins/maxes, and a story.

The Basics of Crafting Data Sets (~20 minutes)

You don't always have access to the data you want for a design. In this lecture, we'll cover some methods for crafting datasets that are realistic.

Activity Results (Hide All Results)

This talk outlined some practical steps to actually generating data that isn't readily available. After a group example, students worked on generating a sample schedule as a group.

These students told the story of a student who changed their major twice and studied away one semester.

Instructor Analysis (Hide Instructor Analysis)

Providing the sample in lecture as well as letting students all work on the same example in their groups worked well for introducing concepts gradually.

Craft a Dataset (~40 minutes)

Choose a few of the datasets listed below. Craft realistic datasets for them:
  • High and Low Temperatures in Boston for several weeks
  • Calendar appointments
  • Commit activity for an open source project
  • Commit activity for an individual
  • Open hours for a bunch of restaurants
  • Football team standings
  • Numbers of comments/likes on social media posts

Activity Results (Hide All Results)

This activity went well. Students had a bit of trouble grasping the idea of creating multiple datasets. Going forward, the concept of mapping design goals to example datasets should be introduced (see image below).

As students were working on generating a dataset for calendar appointments, they came up with a design goal. We then discussed how this design goal mapped to scenarios they needed to test this design against. Each of these scenarios become a dataset.

Instructor Analysis (Hide Instructor Analysis)

All in all, this was a good activity.

Assignments Due Next Week