Qualitative research yields large amount of qualitative data which requires effective management and organization. Research data management is an important aspect of empirical research that is important in enhancing its ability to advance scientific inquiry (Johnson et al. 2010). Management of this data involves a number of steps such as identifying potential data sources, collection of the data, organizing and processing, creating relevant documentation, storage of the data, and preserving the data. Effective data management requires a researcher to develop a data management plan (DMP). This outlines the strategy for handling research data in a systematic manner throughout the research lifestyle. The goal of qualitative data management and organization is to order, structure and give meaning to the large volume of qualitative data.
In organizing qualitative data, it is important to first ensure that all the data required is accurate and inclusive. In this process, it is important to establish a clear file naming system which makes data identification easy by giving each set of data an identity. The next step should involve developing a data tracking system which allows the coordination of different actors who make up the research team. The tracking system needs to be customized into the data with details of individuals, sites, and dates. Another important step necessary in data organization is putting in place document transcription and translation procedures. This ensures that the standards of data are maintained throughout the research project. It is important to establish quality control proceduresthat facilitates the monitoring of the entire process (Marshall& Rossman, 2014). In organizing the qualitative data, it is critical to set realistic timelines that ensure that work is done systematically.
Management of qualitative data involves steps such as; maintaining copies of all relevant information by keeping back ups and updating them; arranging field notes in a chronological manner, per genre, per events, or topical data schema; developing a system of labelling and storing interviews; creating catalogues for documents and artifacts, storing the data in safe place, establishing completeness of data; and coming up with a strategy of reviewing the data.
Reference
Johnson, B. D., Dunlap, E., & Benoit, E. (2010). Structured Qualitative Research: Organizing “Mountains of Words” for Data Analysis, both Qualitative and Quantitative. Substance Use & Misuse, 45(5), 648–670.
Marshall, C., & Rossman, G. B. (2014). Designing qualitative research. Sage publications.