Mac and Linux-based qualitative researchers have a potential new tool available to them in dedoose, a multiplatform browser-based system for coding and analyzing qualitative data. It makes dealing with data on any platform pretty straightforward, and was built for big teams. All data and analysis occur online, making projects easily accessible to many users working from nearly anywhere with an internet connection.
That said, my initial experiences with dedoose (a name that makes me cringe whenever I have to type it), weren’t great. One reason I love ATLAS.ti for qualitative analysis is that it handles a broad range of file types; specifically, it allows you to code directly onto pdfs without a hitch. Dedoose wasn’t too crazy about loading the pdfs of 1960s newspaper articles that I’m working with. As a historical sociologist, this is pretty crucial for my work, though it’s much less important for most qualitative researchers. Additionally, the dedoose web app crashed when I tried to load Word .doc and .docx files. While it’s easy to convert these into .rtf or plain text files, it’s a frustration, especially considering dedoose’s claim that it supports these file types natively. Its user interface also feels a bit stiff and outdated, though aesthetics admittedly are never the first thing you look for in research software.
On the positive side, dedoose blows away its major competitors, NVivo and ATLAS.ti, in its account-based collaborative environment. While collaborative work is possible with both ATLAS and NVivo, it requires a license for each user, a dedicated server to host the files, and a little finagling. Dedoose was created for groups. Scalable licenses, easy permission management, and browser-based software make it an easy choice for any researcher starting up a group-based project that relies on transcripts or plain text for data.
Dedoose’s analysis tools also give it a small edge over the competition. Generating quantitative measures from qualitative data is a snap with dedoose. It can produce attractive graphs easily, show you co-occurrences, and spit out any spreadsheet you could possibly want to describe your data. Its suite of tools to qualitatively analyze coded data aren’t as robust as those in ATLAS.ti, specifically its query and network tools. But if quantifying qualitative data is your main goal, this will work great. However, for work in grounded theory or more interpretive analysis, you may want to stick with what you’re already using.
Dedoose offers potential users a no-risk, thirty-day test-drive for free. If you’re working with interview or focus group transcripts, as most qualitative researchers are, and especially if you’re working in a team, dedoose may be just what you want. But for work with audiovisual data or pdfs that you want to keep in their original formatting, ATLAS.ti probably remains your best option.