Today’s post is a very short one as I’m swamped with work and getting ready for NCA. I’d like to share the link to an article that was mentioned on the Media Anthropology mailing list. The article, which was published by the BBC a few months ago, is on applied research in organizational settings. Specifically, it’s a tantalizing glimpse into the world of corporate anthropology, written up by Genevieve Bell, a researcher at Intel.
Dedoose, which I’ve written about before, is a web-based platform for qualitative data analysis. I recently had another look at it when two of my colleagues elected to try it out for their current research project. (Thanks for the inspiration, Colin and Damon!)
Dedoose works on a subscription model, where you pay a monthly fee to use the services. Once you have an account you upload your data onto their cloud-based system, and then you code, organize, and analyze much the way you would with computer-based tools such as TAMS and Atlas.ti.
So why would you use Dedoose rather than another software package? Well, the unique strength of Dedoose is that it facilitates collaborative coding and analysis.
With Dedoose you can share projects and/or data sets with a few simple clicks. What this means is that you can easily bring your research colleagues on board for the coding and analysis. Because all of the material is web-based, you can see the coding work that your teammates are doing in real time. There’s no need to ever merge coded documents or email updates back and forth, since everyone can access all the materials, all the time, in their real time state. For collaborative projects, a tool like Dedoose is really ideal.
What are the drawbacks? First, from what I know Dedoose currently cannot work with audio, video, or pdfs. It can handle images but only if they are embedded in text files. If you have a data set that is heavily comprised of audio, video, pdf, or image data, you will probably want to use another software package. (Tip: I’ve heard rave reviews about Transana, which is geared towards the analysis of video and audio data.)
Second, files can’t be edited once they are uploaded. This isn’t necessarily a big deal, but it does mean that you need to have your data clean before you upload and start coding, since you won’t be able to do this on the fly. Also, Dedoose undoubtedly does a great deal to protect its clients’ data, but for safety’s sake you’ll want to anonymize everything before uploading.
Finally, while the subscription model has certain advantages (you only have to pay for it as long as you need it), remember that when you finish your subscription you lose access to the tool, so there’ll be no going back and coding extra data unless you extend your membership.
I’m sure there are other pros and cons I’ve missed. Have you used Dedoose? Let me know if you have — I’d be interested in hearing about your experience with it.