Recording and collecting data: The authors urge ethnographers to be transparent about how they collect data, given the difference in accuracy between different methods (e.g. memory versus recorded interviews). They offer examples of ethnographers only using specific demarcations for speech that was audio recorded, and no demarcations for speech recounted from field notes. They also emphasize the increasing importance of taking digital spaces into account in ethnographic research.
Anonymizing: The authors encourage transparency in their work about the anonymization techniques they employed and why—both in their writing, and in communication with those participating in the study. They suggest this transparency should occur throughout the research and writing process.
Data verification: The authors encourage ethnographers to make transparent “how they know what they know” (52), in order to enable the scholarly community to evaluate the grounds on which an ethnographer is drawing conclusions.
Destroying, preserving and sharing data: Lastly, the authors argue that there is much to be gained by sharing data. They encourage ethnographers to collaborate in developing guidelines for data sharing that are consistent with ethical principles and take into account issues of positionality.
“We are suggesting that the time has come for ethnographers to work together to develop their own set of guidelines for data sharing that are consistent with research ethics principles and that account for issues revolving around positionality” (Murphy et al, 2021:55)
