Hi everyone. My name is Alexandra and I'm a researcher in Social Sciences at Risbo, which is Research and Training Institute at the Erasmus University in Rotterdam. In the previous week, you learned about different methods of data collection. This week, we will learn how to analyze primary qualitative data. The analysis of qualitative data is a research phase that can be divided into three steps. Step one, data management. Step two is your data coding, and the last step is data analysis. Now in this first video, I will discuss data management, the first step. You will learn how to structure and order your data before taking the next steps in the process. So let's start. Imagine your research is on a water management project in neighborhoods A and neighborhood B. You want to know if people in these two neighborhoods participate in the projects, and why they do, or why they don't. So for the research, you interviewed 14 people. You interviewed a representative from the local government that finances the projects. You also interviewed the project leader, the two team leaders in both neighborhoods, two chairman from the neighborhood associations, and you interviewed eight inhabitants of neighborhoods A and B. Let's imagine every interview took about 45 minutes and you've recorded all the interviews on a sound recording device. Of course, you first asked for permission of interviewees to do so. Now you use the recordings to transcribe the interviews on your computer. Transcribing means you write down as literally as possible, word by word what the interviewee or the respondent has said. After transcribing all 14 interviews, you end up with more than 100 pages of transcribed data, and that is a lot of data. Now the question is, how do we analyze this data? The magic word here is, just as it is through the whole research process, structure. Before you start analyzing your data, you need to already structure your data. You structure data by saving and storing it in a sensible way. So imagine, you did your 14 interviews for your research on a water management project and you saved your interviews by these titles or names. Question, are these handy names to save your documents? Well, no, they're not. Right after the interview, you might still know that Mary lives in neighborhood B and participated in the water management project. But will you still remember this after three weeks? Maybe not. That's why I recommend you to use file names with important information in it. So, I would save the interview with Mary as AP_Mary_22 March 2018. A refers to neighborhood A. P refers to the fact that Mary is a participant, and the date is to remember when the interview took place. Now, take Pravini. She lives in neighborhood B and is a non-participant. How will we save the transcript of her interview? I would say BN_Provini 24 April 2018. B referring to neighborhood B, and N referring to the fact that Provini is a non-participant, and the date, of course, again referring to when the interview took place. So, if you save your interviews in this way, you get the following structured list of file names. T stands for team leader, PL for project leader, and LG for the representative of the local government. Now, you can see right away that Mike was the team leader of neighborhood A, Yassim is a participant in neighborhood B, Keiko is the project leader. Once you have saved and stored your interviews, it's tempting to just start reading your interviews and try to make something out of it, right? Although tempting, this method has a few pitfalls. By just reading interviews, there's a real chance that by the fifth interview, you will have already forgotten what was said in the first interview. Now you might think, why don't we make a summary for each interview. That could be a possible solution. However, in summaries, information is always lost due to your interpretations as a researcher. In this stage, it is really way too early to use interpretations of your data. Information that might seem irrelevant at first, may become super important pieces of the puzzle in the final stage of your research. So, in other words, it's important to manage and structure your original, or your raw data in such a way that they remain unedited. We've now come to the end of the first video on analyzing primary qualitative data. We've talked about the idea and the importance of data management within the process. I would like to thank you for your attention, and we will meet again in the next video. In the next video, I will tell you more about coding your data. But for now, goodbye.
