Notes on Data Visualization

This week we look at data visualization (dv), a topic that seems deceptively easy, but if you coded HTML pages in the past, then you will know first hand how difficult it was to display data on the web. Sure, you could set up tables of numbers, but to set up some kind of visual display of those numbers; now that was difficult because you first had to create a graphic somehow, then digitize it, then code the graphic onto the page. Fortunately, there are emerging more and more online apps and software tools that allow graphic visualizations of data. After all, for many people it is easier to see data patterns when that data is displayed in some sort of graphical format, such as a line or bar chart, than just looking at a lot of numbers.

DV is really a subset of Infographics (Information graphics) which are "graphic visual representations of information, data or knowledge intended to present complex information quickly and clearly." The wiki entry on infographic used to have the Washington DC Metro map as a good example of an infographic. The Metro map is something that we are all familiar with, but also something that conveys a lot of complicated information very simply. The last half of the wiki entry on infographic is devoted to a good definition of data visualization, including a list of different types of dv. You can have a look at some other examples of infographics/DVs at Pinterest, Mashable or even the examples on the Bill and Melinda Gates Foundation.

Tools

• Many Eyes, which was a very convenient service offered by IBM for several years, is no longer available.
• Google Charts Tools (I discovered that the Google charts tools can be very powerful, and very easy to use, if you are going to embed a chart directly on a website. There is a code programming tool that allows you to play with the code and different kinds of charts to figure out which one will work for you. See, for example, the column chart example. Here is a quick example that I put together using Google charts.
• Tableau Public might be easy to use. Here is an example by Maria Arango, The World Population in BCE. According to Maria:
  • Tableau is a data visualization software. It usually costs a lot of money but the students can get up to 1 year for free. They only need to create an account with their student's credentials.
  • The use of Tableau requires a basic knowledge of Excel spreadsheets because that feeds the data into the software. Moreover, making the graphs is not a hard task. The things you need to know are the following:
    1. how to upload an spreadsheet into Tableau
    2. a set of categorical and numerical variables
    3. an idea on how you want the graph to look like
    4. how to create a dashboard or a story
    5. how to upload your dashboard into Tableau Public
  • I know this sounds like a lot but there are many free tutorials in Youtube and in the Tableau website. It is a very user-friendly platform.
• You may be able to use Visme.
• Bernard Marr (2017), The 7 Best Data Visualization Tools Available Today
• Here is a list of data visualization tools, Great Tools for Data Visualization. There is another list compiled by Sharon Machlis, Chart and image gallery: 30+ free tools for data visualization and analysis.
• Resource: Catalog of Visualization Types to Find the One that Fits Your Dataset illustrates different types of data visualization, but I could not find the how to do for each visualization.
• I have also come across Visualizing.org (a new data visualization tool available on the web). You can program your own visualization and then upload it there.
• Create a Graph
• Google Analytics Solutions
• Widgenie (graph maker)
• Protovis: a graphical approach to visualization (a javascript tool)
• Time Flow (this is a more complicated, interactive data visualization tool)
• Daytum personal data recorder and visualizer
• ChartAccent, create annotated charts
• Information is beautiful
• Shanti Interactive is a suite of tools for visualizations.

Some statistics sources

• U.S. Census Bureau does have some historical information.
• Enslaved: Peoples of the Historical Slave Trade
• National Center for Health Statistics: Here you can search birth, death, marriage and divorce records by state
• National Historical Geographic Information System
• World Bank
• UN Data
• U.S. Government's Open Data
• Cornell University Library, Data and Statistical Sources: Labor and Employment: Historical Statistics
• World Resources Institute
• The World Factbook
• Historical Data 1900-1960 on international merchandise trade statistics
• Mitchell's Historical Statistics
• Crowdsourcing.org
• Virginia Elections Database
• Fairfax County Historical Economic and Demographic Reports (The county also has a Data Visualization Gallery.)
• Arlington County, Demographics
• Open Data DC
• NYC OpenData
• Estimated Population of American Colonies 1610 to 1780
• Please let me know if other Northern Virginia options
• I have also had some success by searching for "international historical statistics" and/or "historical statistics collections." There is some very interesting statistical information out there; you just have to dig for it.

Some Examples (more to be added)

• 10 Data Visualizations You Must See for Black History Month
• HIS 101 Enrollment Data (This is not a java-based example.)
• My experiments with data visualizations
• U.S. Census, Data Visualization Gallery (hundreds of great examples based on census data)
• Caitlin Belue, Population Growth in Northern Virginia Counties, 1900-2000
• Alexandria Starr, City of Alexandria, VA Demographics
• Visualization Emancipation
• Mining the Dispatch
• Stanford University, Spatial History Project
• All of our earlier examples, based on Many Eyes, are no longer accessible:
  • Iron Ore Production in the United States (line graph) and Iron Ore Production in the United States (bar chart), which are based on this data
  • U.S. Military Personnel during World War II (Sonia Deana)
  • Labor Force Data
  • Amanda Allard's example of a word cloud of favorite movies
  • Jennifer Tillman, US Population Growth before, during & after World War II, by age (Jennifer had also written up some comments and recommendations on creating a data visualization.)
  • Simi Van Scoy, a line graph and a bar graph showing the population increase in India between 1990 and 2010.
  • Amber Laskowsky, Fluctuating Tax Rates for the Highest Tax Bracket by Year (bar graph or line graph format)
  • Willie Pan, National Death Tolls in World War II

Some more reading, which you should probably read before starting on a data projects

• Journalism in the Age of Data
• Lincoln Mullen, Digital History Methods in R
• The Semantic Web
• Just Plain Data Analysis
• Michael J. Kramer, Digital History As Data Transliteration
  
• Seth Denbo, Data Storytelling and Historical Knowledge
• Making Big Data Human
• Nathan Yau, Statistical literacy guides for the basics