COMM 273D | Fall 2014

Thursday, October 2

Data in the newsroom

Phillip Reese of the Sacramento Bee will discuss how he uses data in his investigative reporting projects.


  • Phillip Reese speaks


  • Create a Github Pages repository Due by next class
  • Find 10 interesting online maps Due by next class
  • Read these essays about maps Due by next class
  • Look over my comments on your data beat memos Due by next class

Jump to the full details on homework assignments

About Phillip: He and his colleague, Cynthia Hubert, were finalists for the 2014 Pulitzer in Investigative Reporting for their reporting on a Las Vegas mental hospital that bused more than 1,500 psychiatric patients out to 48 states in 5 years. Their investigation resulted in ending the practice, as well as the hospital being stripped of its accreditation.

From its Pulitzer application:

Hubert and Reese sifted through stacks of bus records acquired through public records act requests and found Rawson-Neal Psychiatric Hospital in Las Vegas had bused about 1,500 patients via Greyhound over the last five years to cities nationwide. The reporting showed that the hospital, dealing with funding cuts, simply got rid of patients, dispatching them on buses with bottles of Ensure for journeys to cities where some had never been.

Hubert and Reese spent months tracking down former patients and others from California to Maryland. They found and interviewed former patients serving prison time, staying in nursing homes and living on the street. They spent days knocking on doors of current and former Rawson-Neal employees in Las Vegas. Reese crisscrossed California researching criminal files and public records. They interviewed hundreds of people on the periphery and at the heart of the story.

Some of Reese's work:

Notes from his discussion

Reese uses a Chrome extension called "Page Monitor" to quickly see if, among the hundreds of sites he's interested in, any have changed for the day.


  • Create a Github Pages repository

    Due by next class

    Time to create a new repository. Follow the tutorial here Email me if you’re running into problems. You don’t have to make some special just make something and make it visible on the web.

  • Find 10 interesting online maps

    Due by next class

    Go onto the Internet. Find 10 maps that are interesting to you and do a writeup, in Markdown, in a file named:

    For each map you find:

    1. Write a short paragraph about why the map is interesting to you.
    2. Include the URL
    3. Take a screengrab, upload it somewhere online (such as imgur), and include it, e.g. using this kind of markup -

        ![image caption here](
  • Look over my comments on your data beat memos

    Due by next class

    I’ll read your memos over the weekend and have some comments and suggestions on them. We’ll continue to revise these over the next week.

Course schedule

  • Tuesday, September 23

    The singular of data is anecdote

    An introduction to public affairs reporting and the core skills of using data to find and tell important stories.
    • Count something interesting
    • Make friends with math
    • The joy of text
    • How to do a data project
  • Thursday, September 25

    Bad big data

    Just because it's data doesn't make it right. But even when all the available data is flawed, we can get closer to the truth with mathematical reasoning and the ability to make comparisons, small and wide.
    • Fighting bad data with bad data
    • Baltimore's declining rape statistics
    • FBI crime reporting
    • The Uber effect on drunk driving
    • Pivot tables
  • Tuesday, September 30

    DIY Databases

    Learn how to take data in your own hands. There are two kinds of databases: the kind someone else has made, and the kind you have to make yourself.
    • The importance of spreadsheets
    • Counting murders
    • Making calls
    • A crowdsourced spreadsheet
  • Thursday, October 2

    Data in the newsroom

    Phillip Reese of the Sacramento Bee will discuss how he uses data in his investigative reporting projects.
    • Phillip Reese speaks
  • Tuesday, October 7

    The points of maps

    Mapping can be a dramatic way to connect data to where readers are and to what they recognize.
    • Why maps work
    • Why maps don't work
    • Introduction to Fusion Tables and TileMill
  • Thursday, October 9

    The shapes of maps

    A continuation of learning mapping tools, with a focus on borders and shapes
    • Working with KML files
    • Intensity maps
    • Visual joins and intersections
  • The first in several sessions on learning SQL for the exploration of large datasets.
    • MySQL / SQLite
    • Select, group, and aggregate
    • Where conditionals
    • SFPD reports of larceny, narcotics, and prostitution
    • Babies, and what we name them
  • Thursday, October 16

    A needle in multiple haystacks

    The ability to join different datasets is one of the most direct ways to find stories that have been overlooked.
    • Inner joins
    • One-to-one relationships
    • Our politicians and what they tweet
  • Tuesday, October 21

    Haystacks without needles

    Sometimes, what's missing is more important than what's there. We will cover more complex join logic to find what's missing from related datasets.
    • Left joins
    • NULL values
    • Which Congressmembers like Ellen Degeneres?
  • A casual midterm covering the range of data analysis and programming skills acquired so far.
    • A midterm on SQL and data
    • Data on military surplus distributed to U.S. counties
    • U.S. Census QuickFacts
  • Tuesday, October 28

    Campaign Cash Check

    The American democratic process generates loads of interesting data and insights for us to examine, including who is financing political campaigns.
    • Polling and pollsters
    • Following the campaign finance money
    • Competitive U.S. Senate races
  • Thursday, October 30

    Predicting the elections

    With Election Day coming up, we examine the practices of polling as a way to understand various scenarios of statistical bias and error.
    • Statistical significance
    • Poll reliability
    • Forecasting
  • Tuesday, November 4

    Election day (No class)

    Do your on-the-ground reporting
    • No class because of Election Day Coverage
  • While there are many tools and techniques for building data graphics, there is no magic visualization tool that will make a non-story worth telling.
    • Review of the midterm
    • The importance of good data in visualizations
    • How visualization can augment the Serial podcast
  • Tuesday, November 11

    Dirty data, cleaned dirt cheap

    One of the most tedious but important parts of data analysis is just cleaning and organizing the data. Being a good "data janitor" lets you spend more time on the more fun parts of journalism.
    • Dirty data
    • OpenRefine
    • Clustering
  • Thursday, November 13

    Guest speaker: Simon Rogers

    Simon Rogers, data editor at Twitter, talks about his work, how Twitter reflects how communities talk to each other, and the general role of data journalism.
    • Ellen, World Cup, and other masses of Twitter data
  • Tuesday, November 18

    What we say and what we do

    When the data doesn't directly reveal something obvious, we must consider what its structure and its metadata implies.
    • Proxy variables
    • Thanks Google for figuring out my commute
    • How racist are we, really?
    • How web sites measure us
  • Thursday, November 20

    Project prep and discussion

    Discussion of final projects before the Thanksgiving break.
  • Tuesday, November 25

    Thanksgiving break

    Holiday - no class
  • Thursday, November 27

    Thanksgiving break

    Holiday - no class
  • Tuesday, December 2

    Project wrapup

    Last-minute help on final projects.
  • Thursday, December 4

    Project Show-N-Tell

    In-class presentations of our final data projects.