through perhaps verbatim recording of ‘naturally occurring’ interaction, or through ethnographic interviews, or through the collection of documents generated in and of the setting. Equally, analytical strategies might emerge over the course of fieldwork, as a response to data generated in the field. For example, it may be that there are opportunities that arise during fieldwork to generate or otherwise collect photographic data that will prompt an analytical strategy that supports the analysis of visual materials; or fieldwork might reveal particular or specialized vocabularies, not anticipated at the start of the research, which suggests that a close attention to language might be helpful, perhaps including some kind of semantic analysis.
There are no right or wrong ways to analyze data from ethnographic research projects. There is variety both in relation to what is meant or understood by analysis, and also in relation to the techniques that are available to manage, store and work with ethnographic data. What is important is that early attention is paid to the possibilities of data analysis, and to attendant imperatives that analytical choices might have for fieldwork, modes of data and for the organization of data. Analysis can refer primarily to data management and data handling – incorporating tasks such as organizing, sorting, indexing, coding, retrieving and classifying data. At this level, data analysis is reliant on systematic and procedural techniques, best put in place at the outset of the project. All analysis in ethnographic research involves some kind of close and detailed reading of data, and so it is vital that early attention is given to data organization and retrieval. There should be plans put in place early on to record and store data systemically, in ways that are efficient and effective for retrieval and close working. Practically speaking, this means building into the research process times to write up or transcribe data, to upload or otherwise store data, and to add indexation or organizational tools. Moreover, this data handling work is also an important way of having regular and ongoing interaction with data and periods of reflection, which are vital to shaping ongoing and future fieldwork. Ethnographic analysis can also refer to the creative and imaginative work of the ethnographer to interpret, interrogate and speculate, to interact with but also to go beyond the data. For ethnographic research design this means being open to the creation of spaces for working with and on the data during the fieldwork process, ensuring there are times for ideas emergent from data to be developed, tested, elaborated and reworked during the research. Analysis in this sense then involves an ongoing dialogue with and between data and ideas.
Key points
Ethnography is particularly suitable for addressing research topics and questions concerned with process and practice.
The process of undertaking research in ethnography is usually referred to as fieldwork. Fieldwork can include a variety of methods for generating data.
Participant observation is a main method for conducting ethnographic research.
The ethnographic research process is non-linear; research design should recognize that data collection and data analysis are not discrete activities.
Strategies for data collection and data analysis can be planned in advance as part of research design in ethnography. They can also emerge during the research process.
Data organization and management should be considered as part of research design in ethnographic research.
Further reading
Fetterman, D.M. (2009) Ethnography: Step by Step, 3rd ed. Thousand Oaks, CA: Sage.
LeCompte, M.D. and Schensul, J.J. (2010) Designing and Conducting Ethnographic Research, 2nd ed. Lanham, MD: AltaMira Press.
Murchison, J. (2010) Ethnography Essentials: Designing, Conducting and Presenting Your Research. San Francisco, CA: Jossey Bass.
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