Even with the best planning and preparation research projects can still take unexpected turns. It is always possible that life comes in between the researcher and the project. How could good data management practice help to mitigate the effects of any (involuntary) interruptions? Which options are there for researchers to advance science even if they decide to not continue their projects?
The example of a fatal accident of a researcher during fieldwork described in the previous blog post “Beyond Sleep” - The orphaned notebook  might sound a bit extreme for many researchers. Yet, the situation could arise that someone engaged in a research project needs to leave the project for a certain period of time due to a variety of reasons: other unforeseen professional obligations, life events, illnesses or accidents, etc. Also not all research projects that have been started will be finished and not all datasets that have been collected make it into a final publication.
This leads to questions of (1) what facilitates taking up a project after a break? and, (2) what can researchers do to not let all the efforts in unfinished project going to waste?
What facilitates taking up a project after a break? Usually it’s all about organisation and documentation. As described in the blog "Beyond Sleep” – The search for the aerial photographs the fictional researcher Alfred needs additional information to find the photographs he is looking for.
You could do a quick self-assessment with a real-life example. Go back to a dataset that you used 5 or 10 years ago - assuming that you kept them or that you still have access to the external storage location. If you’re doing a PhD, check files or papers used for your first article or chapter. If you did not collect data yourself, look at your literature and files used to write your thesis or a publication.
When you look at the folder structure and the names of the files and folders, does this still make sense to you? How easy could you identify something in your files that you refer to in your publication. Did you add any files that document the system you used and what you did with the files? If you would do the same research today, would you organize it in the same way? If not, what would you change? Has your system of organization and documentation changed since you worked on the research files you looked at for this test?
In many disciplines it would not be too difficult to imagine a research scenario in which another researcher will work with a dataset that you have collected. Maybe a PhD candidate would like to compare a newly collected dataset with yours? Or you take on more responsibilities in your department or faculty and would like to enlarge the research team to be able to delegate some of your research tasks. Also when there is a strict deadline for a contract research project, another researcher might have to continue your work in case you get ill, for example. Therefore it might be a good idea to go further than a self-assessment.
Assuming that the dataset is not sensitive, you could ask a fellow researcher in your discipline to look at your (old) files. Can he/she understand what you did and why, based on the publication and the additional files? Do you get any questions?
Your future self
Apart from any rules or disciplinary requirements, good data management includes to be kind towards your future self. Organisation and documentation will require research time and some patience and discipline, but will for sure pay off in case of having to leave the research for a while. If you would stop with your current research today, how easy would it be to pick it up again in one year’s time?
The fictional character Alfred struggles with his role and perceives a contrast between “adventurer” and “archivist”:
“I’m not cut out for this kind of monkish labour, I’m not some sort of bookkeeper in the field, I don’t want to report, I want to discover! (…) I’m not an archivist like ninety-nine out of a hundred researchers!” (p. 163)
When it comes to research documentation, what do you or your PhD candidates struggle with?
Making effort count
It can happen that projects are not being taken up again after a break, but definitely stopped. If we assume that the ending of the project had nothing to do with the quality of the data collection, how could the work that has been done still contribute to science?
In the fictional example Alfred suggested that he or a Norwegian PhD student would continue the project. In some contexts, having someone else take over can be an option. Therefore, it could be very valuable to engage a fellow researcher in reviewing the organization and documentation or your dataset during your research project.
If there is no such a possibility it could be worth looking into the possibility to deposit the dataset in a dedicated data archive (repository), such as DANS in the Netherlands . Even if the dataset is not being used in any scholarly publication this can be possible. In case personal data are being collected special attention would need to be paid to privacy and the relevant procedures, e.g. if/how consent has been obtained.
Depending on the dataset, it might be useful to – next to a dataset deposit - publish a data paper that provides information on the data the research setup, the methods used and the characteristics or the dataset, for example. Like this the work invested in the data collection and documentation becomes visible, and can be used and cited by other researchers.
In case that the quick self-assessment revealed room for improvement, data management habits can be changed step by step. For the topic of organization and documentation, the Data Management Expert Guide by CESSDA ERIC could be a starting point.
This blog post is part of the series “Research in fiction through the lens of data management”.
Boom, M.S. (2019) Research…When life gets in between . Available at: http://europeanbordercommunities.eu/blog/research-when-life-gets-in-between (Accessed [date]).
 For international readers this blog post refers to an English translation of Nooit meer slapen: Hermans, W.F. (2007). Beyond Sleep. (I. Rilke, Trans.). New York, NY: The Overlook Press. (Original work published 1966, translation of the 27th impression published in 2003 by De Bezige Bij).
 The global Registry of Research Data Repositories re3data.org, allows to search or browse for further repositories according to disciplines, countries or types of data, for example.