I worry that ‘I don’t know what I don’t know.
That is the situation of many students when faced with research data management issues. After years of practice in the neuroscience data analysis and 6 months dealing purely with Research Data Management (RDM) in that domain, I am sometimes still faced with that fear myself.
Similar to the students who responded to a recently published survey (and in contrast with what their institutions believed they were doing), I am turning to online training and websites to know more about the subject, but I have the advantage of having a good background on why we should do RDM, its basic principles, and fear of human un-writable standards.
The study showed other interesting results. Fig.9 shows that problems during data processing and analysis is a large challenge for students, and is completely underestimated by institutions. I have been working on developing data structures by looking at the data processing (data flow) for a couple of projects now, and I am still amazed by the time wasted when researchers do not recognize (or never thought of) what data files should be archived and need to look back into different computers to collect them.
In short, RDM training requires both RDM and domain specific knowledge to be really efficient. A combination of training offered by faculty libraries and IT, by (free-lance) experts and online training websites, is probably a key to better RDM training in the future.
Pasek, J., & Mayer, J. (2019). Education Needs in Research Data Management for Science-Based Disciplines. Issues in Science and Technology Librarianship, (92). doi.org/10.29173/istl12