This handout was created for Berkeley’s Love Your Data week (#LYD16), and is posted on our Research Data Guide. Fellow data librarians, you’re welcome to reuse this with attribution (CC-BY)!
What is qualitative data?
If you’re working with:
- audio or text files from interviews, focus groups, surveys, oral histories
- narrative observations of people and animals
…you may be working with qualitative data. “Qualitative data” also includes textual results from surveys, maps and pamphlets, photos and videos of people and places, sketches of a scene, and handwritten fieldnotes or scratch notes.
But how is this “data”?
“Research data is collected, observed, or created for purposes of analysis to produce original research results,” as the University of Edinburgh says. If you have gathered materials for the purpose of textual, conceptual, or qualitative study, you are working with qualitative data.
Why should I care about my data?
Because it may be priceless! Christine Borgman calls observational data “the most important to preserve, because these data are the least replicable” (Big Data, Little Data, No Data: 23). Qualitative researchers learn in detail about specific people a specific point in time, and what we observe, discuss, or photograph may never be captured in all its fullness again.
Many people may benefit if you manage and preserve all your data—not just your final paper.
Which qualitative data should I keep and share?
The value of your data comes from 1) its usefulness for other researchers to explore and 2) its archival or historical value for future generations. When deciding what to keep, ask yourself:
- Are there other copies?
- Could someone approximate your conclusions based on what you’ve written or recorded?
- What ethical or legal guidelines has your funding agency, IRB, or discipline provided?
But what about confidentiality?
It’s a big deal. Science is moving towards full sharing of data, but there are exceptions for:
- Sensitive data: names, dates, locations, and sensitive topics can all be obscured or removed.
- Ethics: what did you promise in an IRB application, or directly to your participants?
- Disclosure risk: the risk of a break-in goes up the more you store or share files digitally.
So how can I manage my qualitative data?
It’s messy, isn’t it? Even if you’re not ready to archive or share your project, your first step is to ‘manage’ your interview and fieldnotes, photos, and videos to ensure they can be stored or reused later:
- From the start, organize files in folders by topic or date range
- Name your files descriptively: 2015_Zambia_interview_notes_CE.txt is better than notes1.txt.
- Add a README file to every folder to explain important information or context for the files within. Could someone who doesn’t know you figure out what project this data was for and how it’s used?
- Encrypt all sensitive information at file, folder, or hard drive level – or all three. Give the password to a trusted colleague so it’s not lost!
- Back up regularly! Keep 3 copies in at least 2 locations, with at least 1 offline or offsite copy. Balance storage between secure cloud storage, local computers, backup drive, and printouts.
How can I increase data security?
Good question. You can choose not to collect identifying or sensitive information (yet we know that your research will have greater historical or genealogical benefit if all the details are included). You can also strip sensitive information before archiving or sharing, or share only a subset of your full data.
Another good step is to ask your campus’ librarians or Research Data Management team about how to encrypt computer and internet connections, and to set up secure servers for file transfer and backup.
But security doesn’t mean stuffing data under a mattress or letting it die on an old hard drive! It’s important to archive your data with a long-term archive. You can place sensitive data in a restricted archive (like ICPSR or QDR), and require time delays or ethics approval before people can access it.
Why share my data?
It’s good practice. It lets others build on your work. You get citations for it. And you’ll improve your chances on the job market:
Students: consider sharing anonymized excel sheets of data, posters, or figures on figshare.
Grad students and faculty: look up ICPSR, QDR, or your university repository as possible locations for data archiving.
Advanced researchers can also write a “data paper” which describes the data, context, methods, and how the dataset could be reused. Share your dataset or data paper with a DOI / permanent URL, and you can get credit for each time someone cites or re-uses your data.
What are my next steps?
Use DMPTool to plan ahead for your next research project.
Consider adding data management to your next research grant budget, so that you can hire assistants to organize and archive your data for you!
Contact your librarian to talk about how else you might organize, store, and share the hard-won results of your qualitative research!