Jelte Nimoth is an embedded data steward at the UG Faculty of Science and Engineering’s Stratingh Institute. He holds a PhD in inorganic chemistry from the University of Oldenburg, where he studied silicone compounds through a combination of synthetic laboratory work and quantum chemical computations.

He developed a strong interest in IT and research data management during his research, inspired by the challenges of organizing and integrating experimental and computational data. That interest led him to join the Digital Competence Center (DCC) in 2022, where he combines his scientific and technical expertise to help researchers make their data and software FAIR, while developing practical solutions for data management in the lab. In this interview, he shares more about his job and the solution he implemented in the lab.

Open Science is a priority for the UG. As an embedded data steward at FSE, how can you help researchers make their data and software FAIR?

While Open Science and FAIR data are related concepts, I'd like to focus on the FAIR aspect specifically. As an embedded data steward, I serve as researchers' primary contact for FAIR data questions and IT tool guidance. There is still some unawareness of what FAIR data entails in the research process, such as the use of data repositories, data availability statements in papers, and general good practices to increase reusability of research data. Giving advice on these topics can help get research started. 

That is why the embedded data stewards within the different faculties can help researchers navigate these sorts of questions, and discover other resources from the UG or SURF that can help them deal with their research data management. Users really appreciate having someone available whom they can directly contact for all these questions, someone who is physically present to answer their questions and who also understands their perspective by having been a researcher as well.

What kind of questions do you receive from researchers? 

The questions I receive can range from very basic to quite complex. On the simpler side, researchers might ask about the context or proper use of a data repository. On the more complex side, they often involve transferring data between different devices or systems, ideally in an automated and failsafe way. These situations can be tricky, especially when multiple devices with different operating systems are involved, but I actually enjoy the problem-solving process they require.

Researchers are also advised on internal data management plans at the UG or on plans required by larger funding agencies. At our institute, we generally don’t work with sensitive data affecting personal rights or human subjects, so questions in that area are rare. When they do arise, other DCC colleagues with more expertise are available for guidance. 

Another common topic involves the use of electronic lab notebooks, which are used extensively at the institute. Additionally, as a member of the Research Data Management System (RDMS) team, I help researchers use our internal data archiving solution correctly.

Part of the work at Stratingh Institute is to take measurements with the lab equipment. You’ve implemented a system at the institute that connects lab equipment to secure data storage. Could you tell us more about how this system works and what benefits it offers for data collection and management?

Researchers at the Stratingh Institute use a wide range of measurement devices. The PCs controlling these devices are usually not allowed direct access to the UG network, and storing data only on local hard drives carries obvious risks, like drive failures. While manual backups to external drives are possible, they’re inefficient and error-prone.

To address this, we implemented a more automated and reliable solution. All measurement devices in the same building are connected to a local network, which also includes a dedicated “Transfer PC.” This Transfer PC can access both the local network and the measurement data. Using a backup program, it periodically collects all new data from the measurement PCs and transfers it directly to a secure UG network location (the Y: drive), managed by the Institute’s analytical unit. This system ensures that data is safely stored, centrally accessible, and reduces the risk of data loss, while allowing researchers easy access to their data without manual handling.

Could you share a success story involving the system you created, or your work as a data steward at the Stratingh Institute, which made a significant difference?

We also set up a PC in our local network that is accessible both within the local network and from the UG network. Unlike the automated backup system, this PC allows researchers to transfer data from measurement PCs to its drive and make that drive accessible from their UG workstations. This enables data to move in and out of the local network without relying on USB sticks, making data management much simpler for researchers.

This solution is especially valuable because some measurement devices have processing software that is only available on the local network machines. The system was developed in collaboration with colleagues from the Linux (LWP) team of the University of Groningen’s Center for Information Technology (CIT), whose support was invaluable.

Currently, much lab equipment still relies on proprietary software. What would be the advantage of having more open source solutions for running lab instrumentation? What are the challenges to making this shift?

Many proprietary tools are not only used to run instruments but also for data processing. Reproducing results often requires access to the same software, which may be costly or unavailable to everyone. Open-source solutions could help make these workflows more accessible and reproducible. Another advantage is sustainability: if a manufacturer stops supporting its proprietary software, an open-source alternative could, in theory, continue to be maintained and developed by the community.

Of course, there are challenges. In many cases, suitable open-source alternatives simply don’t exist, or they require users to relearn workflows, something not everyone is eager to do if the proprietary solution still works. And while the idea of community-driven development sounds great in theory, it only works if there is enough capacity and engagement to keep the software alive. So while open-source can solve some of the problems, it is not automatically a complete solution.

Useful links

The UG’s Digital Competence Centre supports UG researchers throughout the entire research (data) life cycle, from grant proposal to FAIR data archiving.