Data management and curation practices in the long tail of research data: the case of survey research

While large research collaborations can dedicate vast resources to the storage, analysis and sharing of data, the majority of scientists are working in small teams and have only limited funds to dedicate to data management, in particular this is true for doctoral students and other early career researchers. In social science research, the advent of free online (survey) data collection tools has enabled researchers to collect responses in an inexpensive way; however, a lot of the resulting data is not shared with other researchers and/or preserved for long-term use. One of the reasons is that this data is often of low quality and/or is not reusable due to incomplete metadata. In this presentation I overview data sharing challenges I encountered while working on my own long-tail social science projects and assisting other researchers with data collection, analysis and sharing in their projects. Moreover, I provide suggestions on how to improve the reusability of long tail survey research. In particular, I argue that the use of data management plans and other data management practices should be encouraged among social science researchers.