DTL’s Rob Hooft has developed a Data Stewardship Wizard in collaboration with colleagues from the Czech ELIXIR node. The Data Stewardship Wizard converts a lengthy data management questionnaire into an effective flowchart, saving you research time and money, and enhancing the quality of your Data Management Plan.
A modern complete research proposal includes a Data Management Plan (DMP). However, regular DMP questionnaires consist of a series of hundreds of open-ended questions. Answering these requires a combination of expertise from different people. As a result, many researchers perceive writing a DMP as an unpleasant obligation and a time claimer at the cost of research time. In addition, regular DMP questionnaires necessarily have a restricted scope because including all potential topics would create even longer lists of questions that may largely be irrelevant to many projects.
Data Stewardship Wizard
DTL’s Rob Hooft has developed a Data Stewardship Wizard in collaboration with colleagues from the Czech ELIXIR node. He explains: “The Wizard uses a logical flowchart to guide you through a questionnaire that incorporates the full breath of relevant topics, producing answers that are relevant to your DMP as well as realistic research budgets. The Wizard offers an efficient way of working, with lower risk of forgetting essential components of data management, thereby reducing risks for the project and leaving more effective time for the research itself.”
Why make a Data Management Plan
Save time & money
Hooft: “Nowadays, handling digital data consumes around 25% of the total budget of an average life science research project, so proper data management planning from the start is worthwhile.”
Increase funding chances
“International funding organisations have made a decent DMP a precondition for funding. For instance, the European Committee has recently made the DMP a mandatory part of grant submission. In the first six months, the rules were not strictly enforced (i.e., a trial period), but it was clear that submissions that included a DMP were more likely to be honoured.”
Improve societal yield
“Properly managed and annotated research data can be re-used in other research areas, which saves time and public money for new research. For example, genetic data collected in a project often contain a treasure of information for projects with another research focus. And research data may also be of use outside the research field, for example if data can be used for policy making (e.g., which new treatments to include in health insurance).”
Obtain high quality results
“A good DMP ensures that research data are secured, efficiently annotated, and stored for (re-)use. The annotation ensures that the process to obtain the data is transparent: no forgotten steps that can even confuse yourself when a reviewer asks for additional information. There is also less risk of data loss or data theft, because of extra attention for secure storage. A decent DMP results in knowing beforehand which expertise you need for your research on several (technical) levels,” concludes Hooft.
You can find more general information about DMP on the dedicated section of the DTL website.