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Qualitative Data Analysis: Data Basics

Data Basics

Qualitative data describes qualities, characteristics, and concepts related to people, their experiences, and our socially constructed nature of reality.

Examples of research that involve qualitative data: interviews, focus groups, observation, field notes, oral histories, primary source research with items such as diaries and journals, and any other research endeavor that allows a subject to express qualities and characteristics of their experience.

Below is a list of some great resources to look at:

"Free" datasets and software may have limits on how you can use them.

Here are some of the basic types of licenses for datasets:

  • Public Domain: no intellectual property rights apply, no attribution required
  • Creative Commons (CC): the most common type of license; offer a variety of different licenses that grant different levels of permission
  • Open Data Commons (ODC): allow users to share, modify and use datasets with proper attribution
  • Community Data License Agreement (CDLA): collaborative licenses to enable access, sharing and use of data openly among individuals and organizations

"Open Source" is talking about the software involved: open source software (OSS) is freely available online for download and use; this term does not refer to a license of any kind. Some basic types of licenses for OSS include:

When you create a data set, you want to make sure that it is "good" data in that it is accurate, complete, organized, and ultimately, reusable.

Here are some tools that can help:

  • OpenRefine is a powerful free, open source tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.
  • Awesome Dataset Tools on Github: provides links to a variety of tools you can use to label your data.

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