Following up on research data that dates back is impossible at worst, tedious at best. The more time has passed since acquisition, the harder it gets to find, access and understand the data. This is especially challenging if the PhD or PostDoc who worked on the project has left the research group.
“In cases of re-evaluation of published data, journals and funding agencies want to see the original data.”
Missing primary data falls back onto the PIs in charge
One could argue that experiments may be run again leading to the same results. But this is a weak solution for two reasons: Firstly, what if you cannot reproduce your own results? Secondly, in cases of re-evaluation of published data, journals and funding agencies want to see the original data. Not being able to retrieve primary data with its metadata can have a negative impact on the reputation of the PI in charge – a damage that might be permanent and impossible to recover from. Even though it might have been the PhD students who produced the data and failed to manage it properly, in the end it falls back onto the PIs who are responsible for what is going on in their research group.
This leads to a central question: Can and should PIs dictate their students, graduates, PhDs and PostDocs to follow DMPs including their rules and necessary tools?
“The inability to present primary data may result in accusations of scientific misconduct.”
There is a categorical answer to this: Yes, they have to. The inability to present primary data may result in accusations of scientific misconduct. This may lead to the deprivation of the right to apply for funding for researchers, difficulties in finding collaborators and journals to publish in.
Introduce a data management plan in order to prevent uncomfortable situations
There are precautionary steps that every PI can take: To begin with, they can come up with a Data Management Plan (DMP), which is mandatory when applying for funding anyway (see here). We all know that PIs are usually quite busy, so please find someone reliable who you can delegate this task to and who will report regularly back to you.
In order to get your students to live up to the requirements defined in the DMP, consider the following aspects:
1. Make data management as easy as possible
Make data management as simple as possible by e.g. automating processes wherever possible. Use software tools that save metadata and acquisition parameters automatically with the experimental results. This way, instead of having to sacrifice their time for data management, which they would rather invest in their research, they actually save time and effort when dealing with their data.
2. Communicate rules
Communicate an explicit and structured approach to your students to live up to the requirements of data management. Inform them about the minimum of what is expected and how its best achieved.
3. Explain the reasons for data management and GLP
Students need to understand why they have to follow specific rules and how best to do it. If they do not understand the reasons for good data management, they will have a harder time to follow up on it.
4. Get students involved
Encourage your students to suggest improvements to the data management system. It will motivate and involve them to an extent that they actually deal with the matter and understand its importance. Once their improvements are taken into account, they will more easily take care of their data, because the system has (partly) become their project.
5. Consider consequences
If your students do not obey any of your rules, you have to take more severe steps. Announce consequences such as no more measurement time or the all time favorite: cake for the group to get them to do data management. This is very strong but in the end it is your reputation that might get damaged.