Paper short abstract:

Increasing the use of tools and platforms for ethnographic research practices does not come with a stronger commitment or possibility to open up research and consequent data. Based on a discourse ethnography, the paper examines the connections between data sharing and the use of tools and platforms.

Paper long abstract:

Ethnographic research practices today are in many regards digital: we are using different types of software from text processing, audio recording or mind mapping to tools for qualitative data analysis (QDA) or capturing social media data. Furthermore, digital humanities are slowly entering ethnography and vice versa. Within the pandemic, elements of digital ethnography became more relevant to get into interaction with our fields, including an increased use of tools to interact with research participants.

But my research shows that these developments do not form a stronger commitment or possibility to open up research practices and consequent data. First, collaboration is not intended within most research infrastructures. Second, the storage and opening up of data can get even more complicated, since many tools have separate data formats. Not all of them are designed to share, making the data aggregated within the tool unavailable to the outer world – not to say fitting it to metadata standards. Third, since open source tools stay on the prototype level in many cases, data gets fragmented into different tools and formats. Fourthly, browser-based tools seldom have the possibility to store the interactions performed at all, therefore the data produced is not findable or reusable.

How do ethnographers use different tools and platforms for data generation and analysis? Which ways do they find to nevertheless open up their research? Do data sharing considerations play a role at all? The paper presents first insights on digital ethnographic research practices based on a discourse ethnography started in 2018.