An overview of using government data for information graphics, from locating the data to visualizing it with Web 2.0 tools and desktop software.

1. David Herzog
Missouri School of Journalism and NICAR

2.  Locating the data
 Obtaining the data
 Evaluating the data
 Working with the data
 Visualizing the data

3.  “Database state of mind”
 Data has to exist. Where?
 Online
 Offline

4.  Government websites
 Data.gov
 U.S. Census Bureau
 FDIC
 Missouri Data Portal
 Missouri Accountability Portal

5.  U.S. agency FOIA pages
 Drug Enforcement Administration
 NGO sites
 Right-to-Know Network
 OpenMissouri.org
 NICAR database library
 ALA state agency databases wiki

6.  Commercial services
 Socrata
 Infochimps
 Geocommons
 Foreclosure Radar
 Oil Price Information Service
 Search Systems
 Junar

7.  Academic data catalogs
 ICPSR
 Forms
 Forms.gov
 Web forms
▪ Columbia parade permits

8.  Records retention schedules
 Reports
 State auditor
 U.S. Government Accountability Office
 U.S. Inspectors General

9.  Google advanced search
 Look for data files
 Look for key words
 Look only on government sites

11.  Data entry
 In the field
 At the office
 Printouts/reports
 Inspection forms

12.  Download it
 Write or request a scraper with ScraperWiki
 Convert a PDF with
 CometDocs
 Zamzar
 Just ask for it

13.  U.S. Freedom of Information Act
 Passed in 1966
 Amended in 1996 to include electronic records
 State open-records statutes
 Missouri Sunshine Law

14.  Get the roadmap!
 Record layout
 File layout
 Data dictionary
 Code sheet
 Metadata
 Data about the data

15.  Look at it immediately when you get it
 It is what you asked for/expected?
 How many rows/records of data?
 Is the file format OK?

16.  Does it look too good to be true?
 Beware of missing information
 Who collected the information?
 How? What are their methods?
 Why?
 What is their agenda?
 Who supports them financially or otherwise?

17.  Notepad++ for PCs
 TextMate for Mac

21.  Always keep original file
 Never overwrite data columns
 Tools
 Spreadsheets
 Database managers
 Google Refine
 Programming languages

22.  Raw numbers, without context, rarely are
interesting.
 Ask: Compared to what?

23.  Raw (amount) change
 New-Original
 Percent change
 Change/Original
 Per capita rates
 Per person
 Per x people

24.  Percent of total
 Individual/Total
 Ratio
 Apples/oranges
 Averages
 Mean
 Median

25.  Be curious!
 Cut out small slices
 Spreadsheets for simple math and
comparisons
 Spreadsheets for pivot tables
 Database managers for more robust analysis
 Always ask: Is this correct?

26.  Online software platforms
 Desktop software

32.  Contact David Herzog at
 herzogd@missouri.edu
 Twitter: @davidherzog