Qualitative Data Management

Data management is a challenging, integral, and vital part of qualitative research if it is to be successful. Good management has been identified as necessary for facilitating the coherence of a project (Huberman & Miles, 1994). Managing data well “facilitates interpretation just as good orchestration facilitates good dance music” (Meadows & Dodendorf, 1999, p. 196). Researchers need a plan from the outset to sort, summarize, analyze, and store project data, including their process of working with the data through the iterative process. The iterative progress of qualitative research means that data management and data analysis are integral to each other.

Data management in qualitative research begins with the conceptualization of the project. Although what constitutes data per se varies with some established traditions, the process of doing qualitative research, and doing it well, means that the researcher’s reflexivity is part of the project data. Formulating the research question from a topic of interest based on reflection and investigations of existing literature (and potentially theory) are central to the project. A thorough literature review is the first step in the qualitative analysis (Morse & Richards, 2002). The research question guides the data to be collected: Without good data, one cannot have a good study. In the study design stage, decisions made regarding sampling, recruitment, data collection techniques, and analytic approaches are steps in data management that need to be recorded and enveloped into the project data.

Data usually come from several sources and can be copious, including documents, pictures, media clips, and transcripts as well as field notes and reflective journals at a very early stage. These need to be documented, turned into derived text or other forms that can be analyzed, and used as data early and often. Researchers must remember to back up all data being used in the project. Descriptions of codes, categories or themes, and memos that reflect the process of moving data from description to analysis and the final interpretation and/or theory-building process are all part of the data in a project.

Qualitative analytic programs are an integral part of this process (Meadows & Dodendorf, 1999), facilitating the management of projects large or small in a way that allows the researcher to spend time on analysis and [Page 891]interpretation instead of searching for important quotes or that elusive file with important codes. Data can be managed manually in file drawers, diagrams, charts, models, and tables that can become cumbersome, preventing the research team from closely working with its data. Programs can also aid the process of asking questions of the coded data to develop theory or aid the interpretive process.

Finally, management also includes adhering to ethical standards that include anonymizing data, ensuring that only named members of research teams have access to the data, and that data in all their forms are kept secure throughout the project. Careful planning for data management at an early stage in the research process can make a significant contribution to the rigor and success of qualitative research.