Data Literacy

David Herzog is an associate professor at the Missouri School of Journalism, where he also serves as the academic adviser to the National Institute for Computer-Assisted Reporting. He was a fellow at the Reynolds Journalism Institute, where he launched OpenMissouri.org, a directory of data held offline by state agencies. Before arriving at the School of Journalism in 2002, he worked as a newspaper reporter at The Providence Journal, The Baltimore Sun and The Morning Call in Allentown, PA. He is a native of Bethlehem, PA.

Chapter 1: Data Defined Climbing the pyramid A brief history of the data world Data file formats Chapter 2: Clues for uncovering data Why agencies collect, analyze, publish data Clues from data entry Clues from reports Tricks to uncover forms and reports On your own Chapter 3: Online databases Destination: data portals Statistical stockpiles Agency sites Non-governmental resources Data search tricks Don't forget the road map On your own Chapter 4: Identifying and requesting offline data Other clues for offline data Find the data nerd Requesting the data Writing the data request FOIA in action Negotiating through obstacles Getting help On your own Chapter 5: Data dirt is everywhere All data are dirty Detecting dirt in agricultural data Changed rules = changed data On your own Chapter 6: Data integrity checks Big-picture checks Detailed checks On your own Chapter 7: Getting your data in shape Column carving Concatenate to paste Date tricks Power scrubbing with OpenRefine Extracting data from PDFs On your own Chapter 8: Number summaries and comparisons Simple summary statistics Compared to what? Benchmarking On your own Chapter 9: Calculating summary statistics and number comparisons Sum crimes by year Minimum and maximum numbers Amount change Stepping up to percent change Running rates Running ratios Percent of total More summarizing On your own Chapter 10: Spreadsheets as database managers Sorting Filtering records Grouping and summarizing On your own Chapter 11: Visualizing your data Data visualization defined Some best practices Chapter 12: Charting choices Visualizing data with charts On your own Chapter 13: Charting in Excel Pie chart Horizontal bar charts Column and line charts Scatterplot Stock chart Sparklines On your own Chapter 14: Charting with Web tools Online visualization options Evaluating web visualization platforms Creating Fusion Table charts On your own Chapter 15: Taking analysis to the next level Database managers Statistical programs