Definitions and Examples

What are “data”?

According to the Oxford Dictionary, data are “facts and statistics collected together for reference or analysis.”  More generally, though, any information used to represent facts or ideas can be considered as “data.”  

This broad definition covers a wide range of data types.  “Data” include both quantitative and qualitative, and can come from either secondary or primary sources, or a combination thereof:

  • Quantitative vs. qualitative: Quantitative data can be measured and recorded with numbers Examples include height, number of exams, temperature, salary, volume, speed, etc.  Qualitative data deal more with quality and descriptions, and are observed rather than measured by numbers.  Examples include political affiliation, colors, feelings about a topic, open-ended responses on an exam, book content, etc.  Some projects use both types of data.
  • Primary vs. secondary: Primary data are collected by the researcher him/herself for the purpose of the study at hand. For example, a researcher may design and carry out an experiment to test a certain theory; the data from this experiment would be considered primary. On the other hand, secondary data come from another source and not collected specifically for the current study.    If a researchers uses a national survey collected by the U.S. Census to study economic factors, the data would be considered secondary.  Some projects use both types of data sources.

What is “data visualization”?

“Data visualization” includes any and all graphics designed to communicate results of data research or summarize findings from data.  Visualizations may include charts, graphs, tables, figures, maps, diagrams, text imagery, infographics, and other standard and non-standard graphics.  Please see our Examples page for an idea of what forms a data visualization can take.

What makes a good visualization? graphic