Strategies to help Researcher Manage and Organize the Data

Introduction

Qualitative data poses management and organization challenges that are unique from those of quantitative data. Qualitative data like photographs, written responses to questions, field notes, transcribed interviews, recorded interviews and video recordings contain several layers of information which will require to be peeled during data analysis (Ulin, Robinson, & Tolley, 2005). Yet the greater the volume of data, the greater the intricacy of managing or organizing it.  Good organization and management of data facilitates the most objective conclusion. The purpose of this paper is to describe two strategies that could help with organization and management of data.   

Strategies to Manage and Organize Voluminous Qualitative Data

One strategy of organizing and managing large volume of data set is the use of computer textual software programs to help with quick coding, sorting, storing and organizing of data. After developing codes for textual data, data analysis software programs can be used to manage, organize, store and retrieve data. Coding is a process of classifying and grouping text data parts into a set of concepts (codes), constructs (categories) and relationships (Johnson, Dunlap, & Benoit, 2010). Coding is focused on identifying key ideas and concepts that are concealed within textual data and these concepts are potentially linked to phenomenon of interest. There are standard software programs capable of organizing complex qualitative data sets. They provide tools which helps with transcription analysis, coding, content analysis, grounded theory, discourse analysis and recursive abstract. They also help researchers save time by providing tools to manage large amounts of data. These program allow the researcher to decide where to store their data files. For instance, if the researcher is performing research of two-stage multisite with at least two varied data collection instruments/tools per stage, these software programs allows data to be hierarchically organized in folders to mirror the fundamental logic of data collection design.  Software programs like QDA Miner, ATLAS.ti.5 and NVivo can efficiently organize large amounts of qualitative data employing user-defined rules (Ulin et l. 2005).  

Another strategy of organizing qualitative data is using semi-quantitative coding. This process involves defining categories for the varied themes and assigning numeric value to each category (Johnson, Dunlap, & Benoit, 2010). Semi-quantitative codes grossly simplifies the responses given by respondents or subjects. The respondent’s response is encoded according to such themes and the responses classified into numbers.  This analytic approach allows for some numerical counts to be reported in conjunction with typical quotes from respondents. A segment of voluminous amount of data is partially converted from textual data set into assigned numerical values that can be counted and used like quantitative data sets (Johnson et al. 2010). To develop semi-quantitative codes, well-trained coders identify the varied themes from collected numerical data and classify them into categories. These codes are then assigned numerical value.  One advantage of semi-quantitative coding is that the codes can be analyzed quantitatively together with voluminous qualitative data.  This data conversion facilitates measurement comparisons.

Conclusion

Management and organization of voluminous qualitative data is both complex and changes. Thanks to the development and use of data analysis software programs, now it becomes easier to organize and manage such data. These programs simply the coding process making it easy to organize, sort, store and retrieve qualitative. Semi-quantitative coding is also helpful in organization of data whereby qualitative data is converted to quantitative data for easy analysis.  

References

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.

Ulin, P. R., Robinson, E. T., & Tolley, E. E. (2005). Qualitative methods in public health: A field guide for applied research. San Francisco, CA: Jossey-Bass.