One major pillar of science are datasets. Collecting, analysing and understanding data is basically what research is all about. In this blogpost, Claire Treat tells a story about haunting data experiences that researchers from other fields can relate to for sure.
In honour of Halloween, I decided to regale the good readers with spooky, haunting tales related to data, a key foundation of doing science. While this topic may seem dry in most seasons, Halloween is the perfect time to discuss—ghosts, goblins, zombies and nightmares lurk behind the façade of rote and boring data management plans. The development and adoption of FAIR data standards (Findable, Accessible, Interoperable, and Reuseable data) have been required by many funding agencies and peer-reviewed journals. Along with the advent of open data repositories, scientists have been pushed to improve data documentation and consider important aspects of metadata, which are critical to science in many fields and key to enabling data reuse. These changes have opened up the possibility of undead data, data that can live on beyond its life on your local laptop or in lab books, in ways that you never imagined (for better or worse). With this in mind, data documentation, data storage, and data protocols always have the potential to become haunting horror stories and need to be carefully addressed to avoid issues of theUndead and Haunting. So, now it is time to let our imaginations roam to the darker and spookier corners appropriate for this time of year.
Haunting tales of stolen and undocumented data
Data storage and backup is the area that has the most terrifying tales. The most haunting tale related to data occurred during my PhD. Along with 40 other PhD Fellows, we were visiting a large research facility near New York. One of the PhD students who was only months away from submitting her dissertation left her laptop bag and laptop unsecured in her hotel room, where it was stolen. This is not ideal to have happen, but the other problem was that the backup copy (in these days, an external hard drive) was in the same bag as the laptop and was also stolen, making it useless. Terrifying? Absolutely. This set her back several months, but I am happy to report that she did eventually complete her PhD. Computer theft has continued since then. More recently, another PhD student had their bag with laptop stolen on the train. Fortunately, they had their work backed up on a server from the Institute and lost only 2 weeks of work. Haunting? Definitely.
Data documentation and lack thereof also have the strong potential to cause zombie scenarios and other nightmares. To use a recent example, a student on a collaborative project received data collected by another group several years ago related to soil properties, soil chemistry and environment, and greenhouse gas fluxes. Great input, but problems came with it! The datasheet collected had no units listed. And worse, this old data was collected by a student no longer at the university! Spooky! It took several months to figure out the units and quality control status of these various datasets, an issue that could have been avoided with proper data documentation and the creation of metadata. Beware the Undead data, it may come back to find you or devour the others on your team.
Goblins and gremlins disturbing data collection
Spooky and missing data can cause a real headache during analysis and can be avoided with clear chains of command, proper documentation about how to make sure that a system is running, and frequent checking on the data collected itself. Work in my field has relied on time-intensive measurements of greenhouse gas exchange between plants, soils and the atmosphere to determine rates of carbon uptake and loss as well as it’s controls. On one hand, this is nice as it provides many students an opportunity to get involved in biogeochemistry as student assistants. But the low frequency of measurements also limits our understanding about temporal dynamics and leads to large uncertainties in greenhouse gas flux budgets. As we automate measurements such as greenhouse gas fluxes (robots! Fun!), this also leads to more complicated systems that require babysitting and have several places where goblins and gremlins can wreak havoc, especially when people are on vacation and not paying attention. Data management plans can include a main responsible person and a substitute to check that the gremlins stay out of the system, document the instructions for running the systems, establish a logging system to document failures. Still, the data needs to be checked that everything looks okay and can be fixed with minimal down time to make sure that the project is going smoothly.
Waking up from data nightmares
Data storage and proper data documentation are all important elements of data management plans. Developing a data management plan is now an important part of the PhD plan. Beyond PhDs, it is important to think and implement data management protocols at the project, group, section, and even departmental levels. While this can be viewed as an annoying piece of paperwork to complete, this is also an opportunity to think about how these terrifying situations can be avoided. The creation and implementation of good data handling practices can save us all from our nightmares of losing precious data and the numerous headaches associated with that. The creation of metadata that includes key information can serve as a bridge for researchers coming after and ensure impact of this data well into the future, as new uses for datasets are identified. So, make sure to back up your data immediately after reading this and Happy Halloween! Boo!
This blogpost was adapted from the Aarhus University Department of Agroecology Biweekly Newsletter published on 2 November 2025.
