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Meet the data agent: Enrico Glerean

Enrico Glerean has a mission: make personal data in research as open as possible, while respecting the law and ethical principles. He teaches “good enough” practices in data management and scientific computing: “good enough” is the first step towards the “best” practices. In this article series Aalto University data agents, researchers and experts experienced in research data management are introduced.
Enrico Glerean

Enrico Glerean is a staff scientist at the School of Science (SCI), supporting the Department of Neuroscience and Biomedical Engineering as well as other departments in SCI and other schools at Aalto. He started as a data agent from the beginning of the initiative. Enrico is also one of the core team members of Aalto

How did you become a data agent? I was a data agent before I knew it was called like that. I have always tried to convince colleagues on the importance of proper data management as well as good practices in coding to make sure the whole workflow (from data collection, to publication) is reproducible. I joined the Aalto data agent network at its very beginning. 

What do you do in practice to help researchers with research data management? As my research background is in medical imaging, I decided to focus on research ethics and personal data in research. I help researchers with issues related to the technical aspects of fulfilling GDPR/ethical requirements. It often goes beyond data management, covering aspects of scientific computing (version control, reproducibility and reusability of code). I also help researchers write data management plans and grant applications that involve personal/sensitive data as well as data storage/analysis for personal/sensitive data.

What are your specialties in research data management? Data management for health/medical data, registry data, confidential data. Data anonymisation. Solutions for opening/sharing confidential data ethically and legally. Beyond data management and more about open science in general: Research ethics, research misconduct, questionable research practices (e.g. p-hacking, harking, researcher’s bias) and possible solutions (e.g. pre-registration, blind analysis, multiverse analysis). Reproducible data analysis workflows ().

Why do you think research data management is important? Sloppy data management is one of the roots of irreproducible science. Irreproducible science is not science. You win a lottery tomorrow and you disappear to a desert island and nobody can contact you anymore. If you were good with data management, your close colleague knows exactly where the data are (and the code!), which data should be used, which should be discarded, how it was collected, how you were analysing them, etc. Or maybe you won’t win the lottery, but you just move to another job and have no time to go back to your old research project. Good data management makes sure that the data and the science are not dependent on a single individual: Everything is documented and “lottery winning” scenarios are not going to stop science. Good data management is also a relief for the individual researcher: once you know that everything is documented and well organised, you don’t need to remember the obscure folder path with the latest version of the data, or the exact file name of the final script that analyses the data. You can then use your brain memory to remember what is more important in life such as friends and family and nice moments with them.   

If you had a magic wand, what would you change in research data management at Aalto University? Good enough practices take time and researchers have barely time to do what they are expected to do. Every department should have a dedicated data agent/data steward/data manager to hands-on help researchers with their data. Each department should also have a dedicated to help researchers with their analysis code development, code sharing, etc.

Your greetings ɫɫ University researchers about research data management? Come talk with us. A few minutes chat is always beneficial. We learn from you and you hopefully learn from us. You can find me (almost) daily at the “”.

Article series Meet the data agent introduces data agents, who are researchers and experts experienced in RDM.

Tasks of the data agents include:

  • Foster reuse of data
  • Help researchers, research groups and departments to manage data well
  • Help to publish data in a suitable repository

Data agents can be contacted directly, or during their consultation hours.

Data agents’ contact information Research data management support is also provided by other specialists of Aalto University. The group includes specialists from IT, Legal Services and Open Science and ACRIS team. This team of data experts can be contacted by sending e-mail to researchdata@aalto.fi

More information on research data management

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