Data can be confusing when it comes to your literature review. Does your literature review have data? Do you deal with data when you are writing it? If your literature review has to be an analysis rather than a description -- which it does -- what are you analyzing, exactly? Today's blog is about these questions. First, though, let's offer a definition of data. Data, in a broad sense, is any information we collect systematically to answer a question. In research, we usually think of data as the stuff we deal with in our analysis and results chapters. That is, data is what we have elicited from our participants, be they texts or people, to answer our research question. This is sometimes called our primary data and it is of course crucial and essential.
But collecting and analyzing data also applies when you are doing your literature review. While we tend to think of literature reviews as a very long exercise in reading, you are doing much more than that, so it can be useful to think about your literature review chapter as another place in your dissertation where you are collecting and dealing with data. What you collect for your literature review is not your primary data, and it won't answer your research question. But remember that in your literature review you are nevertheless answering a question: Why does my research need to be done? To answer this question, you go to the literature in your field, and maybe adjacent fields, and gather information. This information is the data you collect, and then analyze, to figure out why your research needs to be done. It is much more than just reading and taking notes. You are are systematically searching for sources that relate to your project, not cherry picking studies that confirm what you believe. You are then systematically capturing information from those studies. What did they ask? What did they find? How did they proceed? How do the findings relate to the research you want to do? This information, when you are doing your literature review, is your data. And if you've read my blog on how your literature review is like a qualitative research project, you know that you can corral this material (or analyze it, to use the formal term), by thematically coding it to identify the patterns and trends in previous work that add up to why your research needs to be done. It should be a purposeful endeavor, even if it takes you a bit of time to see the path through the data that leads to why your research should be asked.
So the next time you look at that unwieldly stack of papers you need to read, or that bulging computer file (can a computer file bulge? I think you know what I mean 😊), and want to run away, remember: you are not just reading. You are collecting data to figure out why your research question needs to be asked.
