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Data Analysis For Ethnography And Grounded Theory

Data Analysis in Ethnography

Ethnographic research may be regarded as a qualitative method that presupposes researchers’ observation and interaction with participants of a study in their natural and real-life environment. Ethnography helps investigate highly complicated and even critical design challenges aiming to provide an in-depth understanding of a problem to a researcher, including audiences, processes, contexts, domain, and goals. Available ethnographic methods of data collection include interviews, surveys, and participant observation. Used for critical and complex design problems, ethnography is frequently applied at the initial stages of a project to form the understanding of these problems and support future design-related decisions.

In general, data analysis begins with the process of coding and ends with theory development and interpretive assertions. For ethnography, thematic analysis may be regarded as the most appropriate and common method. It presupposes the separation of data into topical themes or its organization into the format of outline with subordinate and superordinate categories on the basis of their significance and relevance to the subject (Sundler et al., 2019). Examining data in order to gain comprehension from the perspective of participants, thematic analysis provides an opportunity to understand data in detail by identifying patterns within it and promoting coding measures (Braun & Clarke, 2021). Without any limitations to participants’ responses, this method is regarded as the most useful for the analysis of qualitative data. Thus, thematic analysis is especially valuable for the examination of response content received from interviews and survey questions. All in all, as the solution of a particular problem requires its in-depth examination and understanding, ethnographic research is applied to collect data from real-life participants without limitations. In turn, thematic analysis contributes to the solution of this issue as well as it allows to systematize and categorize data for problem patterns become visible for potential solution.

Data Analysis for the Grounded Theory

As a matter of fact, the grounded theory refers to the collection of data and its analysis without relying on a particular theory –the goal of the research process is to develop a theory on the basis of collected data. The methods of data collection include interviews with open-ended questions, observation, and the study of texts or artefacts. The grounded theory differs from other approaches by the fact that in it, data collection and analysis occur simultaneously. For the grounded theory, data analysis methods include coding and comparative analysis.

Open coding is the initial step of data analysis applying the grounded theory. It presupposes dividing collected textual data into discrete parts. Subsequently, axial coding implies drawing connections between codes, while selective coding refers to the selection of one critical and central category as the study’s essence that will connect all data codes. At the same time, the grounded theory approach presupposes constant comparison. It means that data categories, property, emerging codes, and dimensions should be constantly compared between each other to detect similarities, differences, and other variations (Tie et al., 2019). This analysis strategy is helpful for researchers as it explores the content of the data and its meaning. All in all, it is possible to conclude that the grounded theory is used when a researcher needs to develop a theory on the basis of data. Thus, data collected via interviews, observations, and text reviews should be divided into codes that should be constantly compared with each other to identify the ability to create a new theory.


Braun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis?. Qualitative Research in Psychology, 18(3), 328-352.

Chun Tie, Y., Birks, M., & Francis, K. (2019). Grounded theory research: A design framework for novice researchers. SAGE Open Medicine, 7, 2050312118822927.

Sundler, A. J., Lindberg, E., Nilsson, C., & Palmér, L. (2019). Qualitative thematic analysis based on descriptive phenomenology. Nursing Open, 6(3), 733-739.

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